Alok Mishra

• Alzoubi, Yehia Ibrahim; Mishra, Alok & Kulakli, Atik (2024). Critical Concerns of Deploying Blockchain in Internet of Things Applications. TEM JOURNAL - Technology, Education, Management, Informatics. ISSN 2217-8309. 13(2).
• Alzoubi, Yehia Ibrahim & Mishra, Alok (2024). Techniques to alleviate blockchain bloat: Potentials, challenges, and recommendations. Computers and Electrical Engineering. ISSN 0045-7906. 116(109216). doi: 10.1016/j.compeleceng.2024.109216. Full text in Research Archive
• Alzoubi, Yehia Ibrahim & Mishra, Alok (2024). Blockchain consensus mechanisms comparison in fog computing: A systematic review. ICT Express. doi: 10.1016/j.icte.2024.02.008. Full text in Research Archive
• Alzoubi, Yehia Ibrahim & Mishra, Alok (2023). Green Blockchain – A Move Towards Sustainability. Journal of Cleaner Production. ISSN 0959-6526. 430. doi: 10.1016/j.jclepro.2023.139541. Full text in Research Archive
• Alzoubi, Yehia Ibrahim & Mishra, Alok (2023). Enterprise architecture contribution in distributed agile software development. Systems Engineering. ISSN 1098-1241. doi: 10.1002/sys.21739. Full text in Research Archive
• Rao, Rajwant Singh; Dewangan, Seema; Mishra, Alok & Gupta, Manjari (2023). A study of dealing class imbalance problem with machine learning methods for code smell severity detection using PCA-based feature selection technique. Scientific Reports. ISSN 2045-2322. 13(1), p. 1–18. doi: 10.1038/s41598-023-43380-8. Full text in Research Archive
• Mishra, Atul & Mishra, Alok (2023). Identifying and Analyzing Reduplication Multiword Expressions in Hindi Text Using Machine Learning. TEM JOURNAL - Technology, Education, Management, Informatics. ISSN 2217-8309. 12(3), p. 1732–1741. doi: 10.18421/TEM123-56. Full text in Research Archive
• Mishra, Alok; Jabar, Thr Satar; Alzoubi, Yehia Ibrahim & Mishra, Kamta Nath (2023). Enhancing privacy-preserving mechanisms in Cloud storage: A novel conceptual framework. Concurrency and Computation. ISSN 1532-0626. 35(26). doi: 10.1002/cpe.7831. Full text in Research Archive
• Mishra, Alok & Alzoubi, Yehia Ibrahim (2023). Structured software development versus agile software development: a comparative analysis. International Journal of System Assurance Engineering and Management. ISSN 0975-6809. 14. doi: 10.1007/s13198-023-01958-5. Full text in Research Archive
• Mohammed, Almashhadani; Mishra, Alok; Ali, Yazici & Muhammad, Younas (2023). Challenges in Agile Software Maintenance for Local and Global Development: An Empirical Assessment. Information. ISSN 2078-2489. 14(5). doi: 10.3390/info14050261. Full text in Research Archive
• Mishra, Deepti; Mishra, Alok & Abdalhamid, Samia (2023). Facilitators and inhibitors of Agile methods adoption: Practitioners view. Systems Engineering. ISSN 1098-1241. 26(6), p. 891–907. doi: 10.1002/sys.21702. Full text in Research Archive
• Alzoubi, Yehia Ibrahim; Gill, Asif Qumer & Mishra, Alok (2022). A systematic review of the purposes of Blockchain and fog computing integration: classification and open issues. The Journal of Cloud Computing: Advances, Systems and Applications (JoCCASA). ISSN 2192-113X. 11(1), p. 1–36. doi: 10.1186/s13677-022-00353-y. Full text in Research Archive Show summary

  The fog computing concept was proposed to help cloud computing for the data processing of Internet of Things (IoT) applications. However, fog computing faces several challenges such as security, privacy, and storage. One way to address these challenges is to integrate blockchain with fog computing. There are several applications of blockchain-fog computing integration that have been proposed, recently, due to their lucrative benefits such as enhancing security and privacy. There is a need to systematically review and synthesize the literature on this topic of blockchain-fog computing integration. The purposes of integrating blockchain and fog computing were determined using a systematic literature review approach and tailored search criteria established from the research questions. In this research, 181 relevant papers were found and reviewed. The results showed that the authors proposed the combination of blockchain and fog computing for several purposes such as security, privacy, access control, and trust management. A lack of standards and laws may make it difficult for blockchain and fog computing to be integrated in the future, particularly in light of newly developed technologies like quantum computing and artificial intelligence. The findings of this paper serve as a resource for researchers and practitioners of blockchain-fog computing integration for future research and designs. Keywords: blockchain, cloud computing, fog computing, integration, Internet of Things (IoT), security

• Kadhim, Yezi Ali; Kahn, Muhammad Umer & Mishra, Alok (2022). Deep Learning-Based Computer-Aided Diagnosis (CAD): Applications for Medical Image Datasets. Sensors. ISSN 1424-8220. 22(22), p. 1–21. doi: 10.3390/s22228999. Show summary

  Computer-aided diagnosis (CAD) has proved to be an effective and accurate method for diagnostic prediction over the years. This article focuses on the development of an automated CAD system with the intent to perform diagnosis as accurately as possible. Deep learning methods have been able to produce impressive results on medical image datasets. This study employs deep learning methods in conjunction with meta-heuristic algorithms and supervised machine-learning algorithms to perform an accurate diagnosis. Pre-trained convolutional neural networks (CNNs) or auto-encoder are used for feature extraction, whereas feature selection is performed using an ant colony optimization (ACO) algorithm. Ant colony optimization helps to search for the best optimal features while reducing the amount of data. Lastly, diagnosis prediction (classification) is achieved using learnable classifiers. The novel framework for the extraction and selection of features is based on deep learning, auto-encoder, and ACO. The performance of the proposed approach is evaluated using two medical image datasets: chest X-ray (CXR) and magnetic resonance imaging (MRI) for the prediction of the existence of COVID-19 and brain tumors. Accuracy is used as the main measure to compare the performance of the proposed approach with existing state-of-the-art methods. The proposed system achieves an average accuracy of 99.61% and 99.18%, outperforming all other methods in diagnosing the presence of COVID-19 and brain tumors, respectively. Based on the achieved results, it can be claimed that physicians or radiologists can confidently utilize the proposed approach for diagnosing COVID-19 patients and patients with specific brain tumors. Keywords: deep learning, CNN, auto-encoder, ant colony optimization, COVID-19, brain tumor

• Ehsan, Adeel; Catal, Cagatay & Mishra, Alok (2022). Detecting Malware by Analyzing App Permissions on Android Platform: A Systematic Literature Review. Sensors. ISSN 1424-8220. 22(20), p. 1–18. doi: 10.3390/s22207928. Full text in Research Archive Show summary

  Smartphone adaptation in society has been progressing at a very high speed. Having the ability to run on a vast variety of devices, much of the user base possesses an Android phone. Its popularity and flexibility have played a major role in making it a target of different attacks via malware, causing loss to users, both financially and from a privacy perspective. Different malware and their variants are emerging every day, making it a huge challenge to come up with detection and preventive methodologies and tools. Research has spawned in various directions to yield effective malware detection mechanisms. Since malware can adopt different ways to attack and hide, accurate analysis is the key to detecting them. Like any usual mobile app, malware requires permission to take action and use device resources. There are 235 total permissions that the Android app can request on a device. Malware takes advantage of this to request unnecessary permissions, which would enable those to take malicious actions. Since permissions are critical, it is important and challenging to identify if an app is exploiting permissions and causing damage. The focus of this article is to analyze the identified studies that have been conducted with a focus on permission analysis for malware detection. With this perspective, a systematic literature review (SLR) has been produced. Several papers have been retrieved and selected for detailed analysis. Current challenges and different analyses were presented using the identified articles. View Full-Text Keywords: malware detection, static analysis, hybrid analysis, permissions analysis

• Dewangan, Seema; Rao, Rajwant Singh; Mishra, Alok & Gupta, Manjari (2022). Code smell detection using ensemble machine learning algorithms. Applied Sciences. ISSN 2076-3417. 12(20), p. 1–22. doi: 10.3390/app122010321. Full text in Research Archive Show summary

  Code smells are the result of not following software engineering principles during software development, especially in the design and coding phase. It leads to low maintainability. To evaluate the quality of software and its maintainability, code smell detection can be helpful. Many machine learning algorithms are being used to detect code smells. In this study, we applied five ensemble machine learning and two deep learning algorithms to detect code smells. Four code smell datasets were analyzed: the Data class, the God class, the Feature-envy, and the Long-method datasets. In previous works, machine learning and stacking ensemble learning algorithms were applied to this dataset and the results found were acceptable, but there is scope of improvement. A class balancing technique (SMOTE) was applied to handle the class imbalance problem in the datasets. The Chi-square feature extraction technique was applied to select the more relevant features in each dataset. All five algorithms obtained the highest accuracy—100% for the Long-method dataset with the different selected sets of metrics, and the poorest accuracy, 91.45%, was achieved by the Max voting method for the Feature-envy dataset for the selected twelve sets of metrics. Keywords: code smell, code smell detection, ensemble method, deep learning, Chi-square feature extraction technique, SMOTE class balancing technique

• Mishra, Alok; Alzoubi, Yehia Ibrahim; Anwar, Memoona Javeria & Gill, Asif Qumer (2022). Attributes impacting cybersecurity policy development : an evidence from seven nations. Computers & Security. ISSN 0167-4048. 120(September), p. 1–23. doi: 10.1016/j.cose.2022.102820. Show summary

  Cyber threats have risen as a result of the growing usage of the Internet. Organizations must have effective cybersecurity policies in place to respond to escalating cyber threats. Individual users and corporations are not the only ones who are affected by cyber-attacks; national security is also a serious concern. Different nations' cybersecurity rules make it simpler for cybercriminals to carry out damaging actions while making it tougher for governments to track them down. Hence, a comprehensive cybersecurity policy is needed to enable governments to take a proactive approach to all types of cyber threats. This study investigates cybersecurity regulations and attributes used in seven nations in an attempt to fill this research gap. This paper identified fourteen common cybersecurity attributes such as telecommunication, network, Cloud computing, online banking, E-commerce, identity theft, privacy, and smart grid. Some nations seemed to focus, based on the study of key available policies, on certain cybersecurity attributes more than others. For example, the USA has scored the highest in terms of online banking policy, but Canada has scored the highest in terms of E-commerce and spam policies. Identifying the common policies across several nations may assist academics and policymakers in developing cybersecurity policies. A survey of other nations' cybersecurity policies might be included in the future research.

• Abdulwahid, Huda M. & Mishra, Alok (2022). Deployment optimization algorithms in wireless sensor networks for smart cities : a systematic mapping study. Sensors. ISSN 1424-8220. 22(14), p. 1–30. doi: 10.3390/s22145094. Full text in Research Archive Show summary

  In recent years, different types of monitoring systems have been designed for various applications, in order to turn the urban environments into smart cities. Most of these systems consist of wireless sensor networks (WSN)s, and the designing of these systems has faced many problems. The first and most important problem is sensor node deployment. The main function of WSNs is to gather the required information, process it, and send it to remote places. A large number of sensor nodes were deployed in the monitored area, so finding the best deployment algorithm that achieves maximum coverage and connectivity with the minimum number of sensor nodes is the significant point of the research. This paper provides a systematic mapping study that includes the latest recent studies, which are focused on solving the deployment problem using optimization algorithms, especially heuristic and meta-heuristic algorithms in the period (2015–2022). It was found that 35% of these studies updated the swarm optimization algorithms to solve the deployment problem. This paper will be helpful for the practitioners and researchers, in order to work out new algorithms and seek objectives for the sensor deployment. A comparison table is provided, and the basic concepts of a smart city and WSNs are presented. Finally, an overview of the challenges and open issues are illustrated. Keywords: smart city; wireless sensor network (WSN); deployment; coverage; connectivity; meta-heuristic.

• Jorayeva, Manzura; Akbulut, Akhan; Catal, Cagatay & Mishra, Alok (2022). Deep learning-based defect prediction for mobile applications. Sensors. ISSN 1424-8220. 22(13), p. 1–18. doi: 10.3390/s22134734. Show summary

  Smartphones have enabled the widespread use of mobile applications. However, there are unrecognized defects of mobile applications that can affect businesses due to a negative user experience. To avoid this, the defects of applications should be detected and removed before release. This study aims to develop a defect prediction model for mobile applications. We performed cross-project and within-project experiments and also used deep learning algorithms, such as convolutional neural networks (CNN) and long short term memory (LSTM) to develop a defect prediction model for Android-based applications. Based on our within-project experimental results, the CNN-based model provides the best performance for mobile application defect prediction with a 0.933 average area under ROC curve (AUC) value. For cross-project mobile application defect prediction, there is still room for improvement when deep learning algorithms are preferred. Keywords: software defect prediction; software fault prediction; mobile application; Android applications; deep learning; machine learning.

• Dogan, Gulin; Akbulut, Fatma Patlar; Catal, Cagatay & Mishra, Alok (2022). Stress detection using experience sampling : a systematic mapping study. International Journal of Environmental Research and Public Health (IJERPH). ISSN 1661-7827. 19(9), p. 1–39. doi: 10.3390/ijerph19095693. Full text in Research Archive
• Akbar, Muhammad Azeem; Khan, Arif Ali; Mahmood, Sajjad & Mishra, Alok (2022). SRCMIMM: the software requirements change management and implementation maturity model in the domain of global software development industry. Information Technology and Management. ISSN 1385-951X. 24(3), p. 195–219. doi: 10.1007/s10799-022-00364-w. Show summary

  The software industry has widely adopted global software development (GSD) to gain economic benefits. Organizations that engage in GSD face various challenges, the majority being associated with requirements change management (RCM). The key motive of this study is to develop a requirement change management and implementation maturity model (SRCMIMM) for the GSD industry that could help the practitioners to assess and manage their RCM activities. A systematic literature review and questionnaire survey approach are used to identify and validate the critical success factors (CSFs), critical challenges (CCHs), and the related best practices of the RCM process. The investigated CSFs and CCHs are classified into five maturity levels based on the concepts of the existing maturity models in other domains, practitioners’ feedback, and academic research. Every maturity level comprises different CSFs and CCHs that can help assess and manage a firm's RCM capability. To evaluate the effectiveness of the proposed model, four case studies are conducted in different GSD firms. The SRCMIMM has been developed to assist GSD organizations in improving their RCM process in efficiency and effectiveness.

• Jorayeva, Manzura; Akbulut, Akhan; Catal, Cagatay & Mishra, Alok (2022). Machine learning-based software defect prediction for mobile applications : a systematic literature review. Sensors. ISSN 1424-8220. 22(7), p. 1–17. doi: 10.3390/s22072551. Show summary

  Software defect prediction studies aim to predict defect-prone components before the testing stage of the software development process. The main benefit of these prediction models is that more testing resources can be allocated to fault-prone modules effectively. While a few software defect prediction models have been developed for mobile applications, a systematic overview of these studies is still missing. Therefore, we carried out a Systematic Literature Review (SLR) study to evaluate how machine learning has been applied to predict faults in mobile applications. This study defined nine research questions, and 47 relevant studies were selected from scientific databases to respond to these research questions. Results show that most studies focused on Android applications (i.e., 48%), supervised machine learning has been applied in most studies (i.e., 92%), and object-oriented metrics were mainly preferred. The top five most preferred machine learning algorithms are Naïve Bayes, Support Vector Machines, Logistic Regression, Artificial Neural Networks, and Decision Trees. Researchers mostly preferred Object-Oriented metrics. Only a few studies applied deep learning algorithms including Long Short-Term Memory (LSTM), Deep Belief Networks (DBN), and Deep Neural Networks (DNN). This is the first study that systematically reviews software defect prediction research focused on mobile applications. It will pave the way for further research in mobile software fault prediction and help both researchers and practitioners in this field. Keywords: software defect prediction; software fault prediction; mobile application; review; systematic literature review; deep learning; machine learning

• Balli, Cagla; Guzel, Mehmet Serdar; Bostanci, Erkan & Mishra, Alok (2022). Sentimental analysis of Twitter users from Turkish content with natural language processing. Computational Intelligence and Neuroscience. ISSN 1687-5265. 2022(Special Issue), p. 1–17. doi: 10.1155/2022/2455160. Full text in Research Archive Show summary

  Artificial Intelligence has guided technological progress in recent years; it has shown significant development with increased academic studies on Machine Learning and the high demand for this field in the sector. In addition to the advancement of technology day by day, the pandemic, which has become a part of our lives since early 2020, has led to social media occupying a larger place in the lives of individuals. Therefore, social media posts have become an excellent data source for the field of sentiment analysis. The main contribution of this study is based on the Natural Language Processing method, which is one of the machine learning topics in the literature. Sentiment analysis classification is a solid example for machine learning tasks that belongs to human-machine interaction. It is essential to make the computer understand people emotional situation with classifiers. There are a limited number of Turkish language studies in the literature. Turkish language has different types of linguistic features from English. Since Turkish is an agglutinative language, it is challenging to make sentiment analysis with that language. This paper aims to perform sentiment analysis of several machine learning algorithms on Turkish language datasets that are collected from Twitter. In this research, besides using public dataset that belongs to Beyaz (2021) to get more general results, another dataset is created to understand the impact of the pandemic on people and to learn about public opinions. Therefore, a custom dataset, namely, SentimentSet (Balli 2021), was created, consisting of Turkish tweets that were filtered with words such as pandemic and corona by manually marking as positive, negative, or neutral. Besides, SentimentSet could be used in future researches as benchmark dataset. Results show classification accuracy of not only up to ∼87% with test data from datasets of both datasets and trained models, but also up to ∼84% with small “Sample Test Data” generated by the same methods as SentimentSet dataset. These research results contributed to indicating Turkish language specific sentiment analysis that is dependent on language specifications.

• Sivari, Esra; Güzel, Mehmet Serdar; Bostanci, Erkan & Mishra, Alok (2022). A novel hybrid machine learning based system to classify shoulder implant manufacturers. Healthcare. ISSN 2227-9032. 10(3), p. 1–17. doi: 10.3390/healthcare10030580. Show summary

  It is necessary to know the manufacturer and model of a previously implanted shoulder prosthesis before performing Total Shoulder Arthroplasty operations, which may need to be performed repeatedly in accordance with the need for repair or replacement. In cases where the patient’s previous records cannot be found, where the records are not clear, or the surgery was conducted abroad, the specialist should identify the implant manufacturer and model during preoperative X-ray controls. In this study, an auxiliary expert system is proposed for classifying manufacturers of shoulder implants on the basis of X-ray images that is automated, objective, and based on hybrid machine learning models. In the proposed system, ten different hybrid models consisting of a combination of deep learning and machine learning algorithms were created and statistically tested. According to the experimental results, an accuracy of 95.07% was achieved using the DenseNet201 + Logistic Regression model, one of the proposed hybrid machine learning models (p < 0.05). The proposed hybrid machine learning algorithms achieve the goal of low cost and high performance compared to other studies in the literature. The results lead the authors to believe that the proposed system could be used in hospitals as an automatic and objective system for assisting orthopedists in the rapid and effective determination of shoulder implant types before performing revision surgery. Keywords: machine learning; hybrid models; shoulder implants; X-ray images.

• Kumar, Kuldeep; Sumit, -; Kumar, Sandeep; Singh, Lalit Kumar & Mishra, Alok (2022). Predicting reliability of software in industrial systems using a Petri net based approach : a case study on a safety system used in nuclear power plant. Information and Software Technology. ISSN 0950-5849. 146(June), p. 1–12. doi: 10.1016/j.infsof.2022.106895. Show summary

  Context: Software reliability prediction in the early stages of development can be propitious in many ways. The combinatorial models used to predict reliability using architectures such as fault trees, binary decision diagrams, etc. have limitations in modeling complex system behavior. On the other hand, state-based models such as Markov chains suffer from the state-space explosion problem, and they need transition probability among different system states to measure reliability. These probabilities are usually assumed or are obtained from the operational profile for which the system should be used in the field. Objective: The objective of this paper is to present a method for predicting the reliability of software in industrial systems using a generalized stochastic Petri nets based approach. The key idea is to violate the assumption of state transition probabilities in the Markov chain. The state transition probabilities are calculated using Petri net transitions’ throughput by performing stationary analysis under the consideration to identify and handle dead markings in the Petri net. Method: Initially, a generalized stochastic Petri net of the system under consideration is generated from the standard system's specification. Thereafter, dead markings are identified in the Petri net which are further removed to perform steady-state analysis. At last, a Markov model is generated based on the reachability graph of the Petri net, which is further used to predict the system reliability. Results: The presented method has been applied to a safety-critical system, Shut Down System-1, of a nuclear power plant, which is operational in the Canada Deuterium Uranium reactor. The predicted reliability of the system using this method is 99.99966% which has been validated using the specified system requirements. To further validate and generalize the results, sensitivity analysis is performed by varying different system parameters. Conclusions: The method discussed in this paper presents a step of performing structural analysis on the Petri net of the system under consideration to identify and handle dead markings on the Petri net. It further handles the issue of assuming transition probabilities among the system states by calculating them using Petri net transitions’ throughput. Keywords: software reliability, safety-critical systems, petri net, reliability model

• Guzel, Mehmet Serdar; Bostanci, Erkan & Mishra, Alok (2022). Mobile robot navigation with swarm intelligence using a decentralized strategy, 2022 IEEE/SICE International Symposium on System Integration (SII 2022) : January 9-12, 2022 (Virtual Conference) Narvik, Norway. IEEE (Institute of Electrical and Electronics Engineers). ISSN 978-1-6654-4540-5. p. 838–843. doi: 10.1109/SII52469.2022.9708908. Show summary

  Collective navigation of swarm robots is one of the most topical problems in the field of robotics. In this context, more than one robot must have the ability to simultaneously perform different tasks in a certain coordination and plan. In the solution of the related problem, it has been tried to ensure that the robots communicate and move in coordination over a central communication architecture. The most important handicap of central architectures is that the communication mechanism of the whole system collapses in case the related unit fails because the system is connected to a single unit. In this context, a novel decentralized architecture has been implemented and tested for physical robots. Several experiments have been conducted to verify the performance of the proposed architecture.

• Alkhateeb, Ahmed; Catal, Cagatay; Kar, Gorkem & Mishra, Alok (2022). Hybrid blockchain platforms for the Internet of Things (IoT) : a systematic literature review. Sensors. ISSN 1424-8220. 22(4), p. 1–19. doi: 10.3390/s22041304. Full text in Research Archive Show summary

  In recent years, research into blockchain technology and the Internet of Things (IoT) has grown rapidly due to an increase in media coverage. Many different blockchain applications and platforms have been developed for different purposes, such as food safety monitoring, cryptocurrency exchange, and secure medical data sharing. However, blockchain platforms cannot store all the generated data. Therefore, they are supported with data warehouses, which in turn is called a hybrid blockchain platform. While several systems have been developed based on this idea, a current state-of-the-art systematic overview on the use of hybrid blockchain platforms is lacking. Therefore, a systematic literature review (SLR) study has been carried out by us to investigate the motivations for adopting them, the domains at which they were used, the adopted technologies that made this integration effective, and, finally, the challenges and possible solutions. This study shows that security, transparency, and efficiency are the top three motivations for adopting these platforms. The energy, agriculture, health, construction, manufacturing, and supply chain domains are the top domains. The most adopted technologies are cloud computing, fog computing, telecommunications, and edge computing. While there are several benefits of using hybrid blockchains, there are also several challenges reported in this study. View Full-Text Keywords: Internet of Things, blockchain, cloud computing, integration, hybrid blockchains, systematic literature review

• Mishra, Alok; Alzoubi, Yehia Ibrahim; Gill, Asif Qumer & Anwar, Memoona Javeria (2022). Cybersecurity enterprises policies : a comparative study. Sensors. ISSN 1424-8220. 22(2), p. 1–35. doi: 10.3390/s22020538. Show summary

  Cybersecurity is a critical issue that must be prioritized not just by enterprises of all kinds, but also by national security. To safeguard an organization’s cyberenvironments, information, and communication technologies, many enterprises are investing substantially in cybersecurity these days. One part of the cyberdefense mechanism is building an enterprises’ security policies library, for consistent implementation of security controls. Significant and common cybersecurity policies of various enterprises are compared and explored in this study to provide robust and comprehensive cybersecurity knowledge that can be used in various enterprises. Several significant common security policies were identified and discussed in this comprehensive study. This study identified 10 common cybersecurity policy aspects in five enterprises: healthcare, finance, education, aviation, and e-commerce. We aimed to build a strong infrastructure in each business, and investigate the security laws and policies that apply to all businesses in each sector. Furthermore, the findings of this study reveal that the importance of cybersecurity requirements differ across multiple organizations. The choice and applicability of cybersecurity policies are determined by the type of information under control and the security requirements of organizations in relation to these policies. Keywords: cybersecurity (CS), cybersecurity polices, cyberspace, enterprise(s), information and communication technology (ICT)

• Kassahun, Ayalew; Bloo, Robbin; Catal, Cagatay & Mishra, Alok (2022). Dairy farm management information systems. Electronics. ISSN 2079-9292. 11(2), p. 1–18. doi: 10.3390/electronics11020239. Show summary

  Nowadays, different types of farm management information systems (FMIS) are being used in practice in several sectors of farming, such as dairy, arable, fruits, vegetables, and meat farming. The goal of this research is to identify, evaluate, and synthesize existing FMISs in the Dutch dairy sector and present the state–of–the–art. We performed a multivocal literature review (MLR) to find sources both in scientific and grey literature. A grey literature search was adopted because most of the FMISs were not reported in the scientific literature. To support and improve the effectiveness of the MLR process, an online survey was first sent to Dutch dairy farmers to identify the FMISs that are being used in practice. With the help of the MLR process, we identified 50 FMISs used by Dutch dairy farmers. We identified 33 features of these FMISs and listed the advantages and disadvantages of the FMISs. Keywords: grey literature, multivocal literature review, precision agriculture, smart agriculture, smart systems

• Abdalla, Reem & Mishra, Alok (2021). Agent-oriented software engineering methodologies : analysis and future directions. Complexity. ISSN 1076-2787. 2021, p. 1–21. doi: 10.1155/2021/1629419. Full text in Research Archive Show summary

  The Internet of Things (IoT) facilitates in building cyber-physical systems, which are significant for Industry 4.0. Agent-based computing represents effective modeling, programming, and simulation paradigm to develop IoT systems. Agent concepts, techniques, methods, and tools are being used in evolving IoT systems. Over the last years, in particular, there has been an increasing number of agent approaches proposed along with an ever-growing interest in their various implementations. Yet a comprehensive and full-fledged agent approach for developing related projects is still lacking despite the presence of agent-oriented software engineering (AOSE) methodologies. One of the moves towards compensating for this issue is to compile various available methodologies, ones that are comparable to the evolution of the unified modeling language (UML) in the domain of object-oriented analysis and design. These have become de facto standards in software development. In line with this objective, the present research attempts to comprehend the relationship among seven main AOSE methodologies. More specifically, we intend to assess and compare these seven approaches by conducting a feature analysis through examining the advantages and limitations of each competing process, structural analysis, and a case study evaluation method. This effort is made to address the significant characteristics of AOSE approaches. The main objective of this study is to conduct a comprehensive analysis of selected AOSE methodologies and provide a proposal of a draft unified approach that drives strengths (best) of these methodologies towards advancement in this area.

• Dewangan, Seema; Rao, Rajwant Singh; Mishra, Alok & Gupta, Manjari (2021). A novel approach for code smell detection : an empirical study. IEEE Access. ISSN 2169-3536. 9, p. 162869–162883. doi: 10.1109/ACCESS.2021.3133810. Full text in Research Archive Show summary

  Code smells detection helps in improving understandability and maintainability of software while reducing the chances of system failure. In this study, six machine learning algorithms have been applied to predict code smells. For this purpose, four code smell datasets (God-class, Data-class, Feature-envy, and Long-method) are considered which are generated from 74 open-source systems. To evaluate the performance of machine learning algorithms on these code smell datasets, 10-fold cross validation technique is applied that predicts the model by partitioning the original dataset into a training set to train the model and test set to evaluate it. Two feature selection techniques are applied to enhance our prediction accuracy. The Chi-squared and Wrapper-based feature selection techniques are used to improve the accuracy of total six machine learning methods by choosing the top metrics in each dataset. Results obtained by applying these two feature selection techniques are compared. To improve the accuracy of these algorithms, grid search-based parameter optimization technique is applied. In this study, 100% accuracy was obtained for the Long-method dataset by using the Logistic Regression algorithm with all features while the worst performance 95.20 % was obtained by Naive Bayes algorithm for the Long-method dataset using the chi-square feature selection technique.

• Prajapati, Amarjeet; Parashar, Anshu; Sunita, - & Mishra, Alok (2021). Entropy-driven global best selection in particle swarm optimization for many-objective software package restructuring. Complexity. ISSN 1076-2787. 2021(Special Issue), p. 1–11. doi: 10.1155/2021/3974635. Full text in Research Archive Show summary

  Many real-world optimization problems usually require a large number of conflicting objectives to be optimized simultaneously to obtain solution. It has been observed that these kinds of many-objective optimization problems (MaOPs) often pose several performance challenges to the traditional multi-objective optimization algorithms. To address the performance issue caused by the different types of MaOPs, recently, a variety of many-objective particle swarm optimization (MaOPSO) has been proposed. However, external archive maintenance and selection of leaders for designing the MaOPSO to real-world MaOPs are still challenging issues. This work presents a MaOPSO based on entropy-driven global best selection strategy (called EMPSO) to solve the many-objective software package restructuring (MaOSPR) problem. EMPSO makes use of the entropy and quality indicator for the selection of global best particle. To evaluate the performance of the proposed approach, we applied it over the five MaOSPR problems. We compared it with eight variants of MaOPSO, which are based on eight different global best selection strategies. The results indicate that the proposed EMPSO is competitive with respect to the existing global best selection strategies based on variants of MaOPSO approaches.

• Mishra, Alok; Shatnawi, Raed; Catal, Cagatay & Akbulut, Akhan (2021). Techniques for calculating software product metrics threshold values : a systematic mapping study. Applied Sciences. ISSN 2076-3417. 11(23), p. 1–25. doi: 10.3390/app112311377. Full text in Research Archive Show summary

  Several aspects of software product quality can be assessed and measured using product metrics. Without software metric threshold values, it is difficult to evaluate different aspects of quality. To this end, the interest in research studies that focus on identifying and deriving threshold values is growing, given the advantage of applying software metric threshold values to evaluate various software projects during their software development life cycle phases. The aim of this paper is to systematically investigate research on software metric threshold calculation techniques. In this study, electronic databases were systematically searched for relevant papers; 45 publications were selected based on inclusion/exclusion criteria, and research questions were answered. The results demonstrate the following important characteristics of studies: (a) both empirical and theoretical studies were conducted, a majority of which depends on empirical analysis; (b) the majority of papers apply statistical techniques to derive object-oriented metrics threshold values; (c) Chidamber and Kemerer (CK) metrics were studied in most of the papers, and are widely used to assess the quality of software systems; and (d) there is a considerable number of studies that have not validated metric threshold values in terms of quality attributes. From both the academic and practitioner points of view, the results of this review present a catalog and body of knowledge on metric threshold calculation techniques. The results set new research directions, such as conducting mixed studies on statistical and quality-related studies, studying an extensive number of metrics and studying interactions among metrics, studying more quality attributes, and considering multivariate threshold derivation. Keywords: object-oriented metrics, software metrics, object-oriented measures; thresholds; systematic mapping, software quality

• Mishra, Alok; Abdalhamid, Samia; Mishra, Deepti & Ostrovska, Sofiya (2021). Organizational issues in embracing Agile methods : an empirical assessment. International Journal of System Assurance Engineering and Management. ISSN 0975-6809. 12(6), p. 1420–1433. doi: 10.1007/s13198-021-01350-1. Full text in Research Archive Show summary

  This study provides empirical evidence to the body of knowledge in Agile methods adoption in small, medium and large organizations in international context. This research explores the factors involved in the adoption of Agile methods in software development organizations. A survey was conducted among Agile professionals to gather survey data from 52 software organizations in seven countries across the world. Statistical techniques are applied towards empirical assessment. Organizational culture, team structure and management support are found to be crucial success factors whereas lack of management support, a large organization size and traditional organizational culture are found to be detrimental for the adoption of Agile approach in an organization. The selection of an appropriate Agile method depends on the project size and, for each size, there are specific methods preferred by different enterprises. Providing better control over the work is viewed as the primary advantage of the Agile methods within large and small organizations, while for the medium-size organizations, the priority is switched to coping with changing user requirements. Majority of the respondents did not consider embracing agile methods as a reason for project failure which indicates that Agile methods are, indeed, beneficial.

• Karim, Ahmad M. & Mishra, Alok (2021). Novel COVID-19 recognition framework based on conic functions classifier. In Garg, Lalit; Chakraborty, Chinmay; Mahmoudi, Saïd & Sohmen, Victor S. Sohmen (Ed.), Healthcare informatics for fighting COVID-19 and future epidemics. Springer. ISSN 978-3-030-72751-2. p. 1–10. doi: 10.1007/978-3-030-72752-9_1. Show summary

  The new coronavirus has been declared as a global emergency. The first case was officially declared in Wuhan, China, during the end of 2019. Since then, the virus has spread to nearly every continent, and case numbers continue to rise. The scientists and engineers immediately responded to the virus and presented techniques, devices and treatment approaches to fight back and eliminate the virus. Machine learning is a popular scientific tool and is applied to several medical image recognition problems, involving tumour recognition, cancer detection, organ transplantation and COVID-19 diagnosis. It is proved that machine learning presents robust, fast and accurate results in various medical image recognition problems. Generally, machine learning-based frameworks consist of two stages: feature extraction and classification. In the feature extraction, overwhelmingly unsupervised learning techniques are applied to reduce the input data’s size. This step extracts appropriate features by reducing the computational time and increasing the performance of the classifiers. A classifier is the second step that aims to categorise the input. Within the proposed step, the unsupervised part relies on the feature extraction by using local binary patterns (LBP), followed by feature selection relying on factor analysis technique. The LBP is a kind of visual descriptor, mainly applied for image recognition problem. The aim of using LBP is to analyse the input COVID-19 image and extract salient features. Furthermore, factor analysis is a statistical technique applied to define variability among observed variables in less unnoticed variables named factors. The factor analysis applied to the LBP wavelet aims to select sensitive features from input data (LBP output) and reduce the size input. In the last stage, conic functions classifier is applied to classify two sets of data, categorising the extracted features by using LBP and factor analysis as positive or negative COVID-19 cases. The proposed solution aims to diagnose COVID-19 by using LBP and factor analysis, based on conic functions classifier. The conic functions classifier presents remarkable results compared with these popular classifiers and state-of-the-art studies presented in the literature. Keywords: COVID-19, conic functions classifier, LBP, factor analysis

• Ibrahim, Thaer & Mishra, Alok (2021). A conceptual design of smart management system for flooding disaster. International Journal of Environmental Research and Public Health (IJERPH). ISSN 1661-7827. 18(16), p. 1–14. doi: 10.3390/ijerph18168632. Full text in Research Archive Show summary

  Disasters pose a real threat to the lives and property of citizens; therefore, it is necessary to reduce their impact to the minimum possible. In order to achieve this goal, a framework for enhancing the current disaster management system was proposed, called the smart disaster management system. The smart aspect of this system is due to the application of the principles of information and communication technology, especially the Internet of Things. All participants and activities of the proposed system were clarified by preparing a conceptual design by using The Unified Modeling Language diagrams. This effort was made to overcome the lack of citizens’ readiness towards the use of information and communication technology as well as increase their readiness towards disasters. This study aims to develop conceptual design that can facilitate in development of smart management system for flooding disaster. This will assist in the design process of the Internet of Things systems in this regard. View Full-Text Keywords: information and communication technology, smart disaster management system, Internet of Things, flood, disaster

• Pande, Akshara; Pant, Vivekanand; Gupta, Manjari & Mishra, Alok (2021). Design patterns discovery in source code : novel technique using substring match. TEM JOURNAL - Technology, Education, Management, Informatics. ISSN 2217-8309. 10(3), p. 1166–1174. doi: 10.18421/TEM103-21. Full text in Research Archive Show summary

  The role of design pattern mining is a very significant strategy of re-engineering as with the help of detection one could easily understand complex systems. Of course, identifying a design pattern is not always a simple task. Additionally, pattern recovering methods often encounter problems dealing with space outburst for extensive systems. This paper introduces a new way to discover a design pattern based on an Impact Analysis matrix followed by substring match. UML diagrams corresponding to codes are created using Visual Paradigm Enterprise. Impact Analysis matrices of these UML diagrams are converted to string format. Considering system code string as main string and design pattern string as a substring, the main string is further decomposed. A substring match technique is developed here to discover design patterns in the source code. Overall, this procedure has the potential to convert the representation of system design and design pattern in ingenious shapes. In addition, this method has the advantage of moderation in the size. Therefore, this approach is beneficial for Software professionals and researchers due to its simplicity. Keywords : Design patterns, UML diagrams, Visual Paradigm Enterprise software, Impact Analysis Matrix, Substring match.

• Gangwar, Arvind Kumar; Kumar, Sandeep & Mishra, Alok (2021). A paired learner-based approach for concept drift detection and adaptation in software defect prediction. Applied Sciences. ISSN 2076-3417. 11(14), p. 1–24. doi: 10.3390/app11146663. Full text in Research Archive Show summary

  The early and accurate prediction of defects helps in testing software and therefore leads to an overall higher-quality product. Due to drift in software defect data, prediction model performances may degrade over time. Very few earlier works have investigated the significance of concept drift (CD) in software-defect prediction (SDP). Their results have shown that CD is present in software defect data and tha it has a significant impact on the performance of defect prediction. Motivated from this observation, this paper presents a paired learner-based drift detection and adaptation approach in SDP that dynamically adapts the varying concepts by updating one of the learners in pair. For a given defect dataset, a subset of data modules is analyzed at a time by both learners based on their learning experience from the past. A difference in accuracies of the two is used to detect drift in the data. We perform an evaluation of the presented study using defect datasets collected from the SEACraft and PROMISE data repositories. The experimentation results show that the presented approach successfully detects the concept drift points and performs better compared to existing methods, as is evident from the comparative analysis performed using various performance parameters such as number of drift points, ROC-AUC score, accuracy, and statistical analysis using Wilcoxon signed rank test. Keywords: concept drift; naive Bayes; random forest; software defect prediction; software quality assurance.

• Gosala, Bethany; Chowdhuri, Sripriya Roy; Singh, Jyotika; Gupta, Manjari & Mishra, Alok (2021). Automatic classification of UML class diagrams using deep learning technique : convolutional neural network. Applied Sciences. ISSN 2076-3417. 11(9), p. 1–14. doi: 10.3390/app11094267. Full text in Research Archive Show summary

  Unified Modeling Language (UML) includes various types of diagrams that help to study, analyze, document, design, or develop any software efficiently. Therefore, UML diagrams are of great advantage for researchers, software developers, and academicians. Class diagrams are the most widely used UML diagrams for this purpose. Despite its recognition as a standard modeling language for Object-Oriented software, it is difficult to learn. Although there exist repositories that aids the users with the collection of UML diagrams, there is still much more to explore and develop in this domain. The objective of our research was to develop a tool that can automatically classify the images as UML class diagrams and non-UML class diagrams. Earlier research used Machine Learning techniques for classifying class diagrams. Thus, they are required to identify image features and investigate the impact of these features on the UML class diagrams classification problem. We developed a new approach for automatically classifying class diagrams using the approach of Convolutional Neural Network under the domain of Deep Learning. We have applied the code on Convolutional Neural Networks with and without the Regularization technique. Our tool receives JPEG/PNG/GIF/TIFF images as input and predicts whether it is a UML class diagram image or not. There is no need to tag images of class diagrams as UML class diagrams in our dataset. Keywords: Unified Modeling Language, Machine Learning (ML); Object-Oriented modeling, Deep Learning (DL), Convolutional Neural Networks (CNN)

• Senirkentli, Güler Burcu; Ekinci, Fatih; Bostanci, Erkan; Güzel, Mehmet Serdar; Dağli, Özlem & Karim, Ahmed M. [Show all 7 contributors for this article] (2021). Proton therapy for mandibula plate phantom. Healthcare. ISSN 2227-9032. 9(2), p. 1–12. doi: 10.3390/healthcare9020167. Full text in Research Archive Show summary

  Purpose: In this study, the required dose rates for optimal treatment of tumoral tissues when using proton therapy in the treatment of defective tumours seen in mandibles has been calculated. We aimed to protect the surrounding soft and hard tissues from unnecessary radiation as well as to prevent complications of radiation. Bragg curves of therapeutic energized protons for two different mandible (molar and premolar) plate phantoms were computed and compared with similar calculations in the literature. The results were found to be within acceptable deviation values. Methods: In this study, mandibular tooth plate phantoms were modelled for the molar and premolar areas and then a Monte Carlo simulation was used to calculate the Bragg curve, lateral straggle/range and recoil values of protons remaining in the therapeutic energy ranges. The mass and atomic densities of all the jawbone layers were selected and the effect of layer type and thickness on the Bragg curve, lateral straggle/range and the recoil were investigated. As protons move through different layers of density, lateral straggle and increases in the range were observed. A range of energies was used for the treatment of tumours at different depths in the mandible phantom. Results: Simulations revealed that as the cortical bone thickness increased, Bragg peak position decreased between 0.47–3.3%. An increase in the number of layers results in a decrease in the Bragg peak position. Finally, as the proton energy increased, the amplitude of the second peak and its effect on Bragg peak position decreased. Conclusion: These findings should guide the selection of appropriate energy levels in the treatment of tumour structures without damaging surrounding tissues. View Full-Text Keywords: proton treatment, biomaterials, bragg peak, mandible plate phantom, dental tumour, paediatric dentistry

• Mishra, Alok & Mishra, Deepti (2021). Sustainable software engineering : curriculum development based on ACM/IEEE guidelines. In Calero, Coral; Moraga, Mª Ángeles & Piattini, Mario (Ed.), Software sustainability. Springer. ISSN 978-3-030-69970-3. p. 269–285. doi: 10.1007/978-3-030-69970-3_11. Full text in Research Archive Show summary

  Climate change risk and environmental degradation are the most critical issues of our society. Our technology-influenced daily lifestyle involves many types of software and apps which are used by society at large, and their use is increasing more than ever before. Sustainability is a significant topic for future professionals and more so for software engineers due to its impact on society. It is crucial to motivate and raise concern among students and faculty members regarding sustainability by including it in the Software Engineering (SE) curriculum. This chapter discusses how sustainability can be included in various courses of the SE curriculum by considering ACM/IEEE curriculum guidelines for the SE curriculum, literature review, and various viewpoints so that SE students can attain knowledge on sustainable software engineering. It also includes an assessment of key competences in sustainability for proposed units in the SE curriculum.

• Colakoglu, Fatima Nur; Yazici, Ali & Mishra, Alok (2021). Software product quality metrics : a systematic mapping study . IEEE Access. ISSN 2169-3536. 9, p. 44647–44670. doi: 10.1109/ACCESS.2021.3054730. Full text in Research Archive Show summary

  In the current competitive world, producing quality products has become a prominent factor to succeed in business. In this respect, defining and following the software product quality metrics (SPQM) to detect the current quality situation and continuous improvement of systems have gained tremendous importance. Therefore, it is necessary to review the present studies in this area to allow for the analysis of the situation at hand, as well as to enable us to make predictions regarding the future research areas. The present research aims to analyze the active research areas and trends on this topic appearing in the literature during the last decade. A Systematic Mapping (SM) study was carried out on 70 articles and conference papers published between 2009 and 2019 on SPQM as indicated in their titles and abstract. The result is presented through graphics, explanations, and the mind mapping method. The outputs include the trend map between the years 2009 and 2019, knowledge about this area and measurement tools, issues determined to be open to development in this area, and conformity between conference papers, articles and internationally valid quality models. This study may serve as a foundation for future studies that aim to contribute to the development in this crucial field. Future SM studies might focus on this subject for measuring the quality of network performance and new technologies such as Artificial Intelligence (AI), Internet of things (IoT), Cloud of Things (CoT), Machine Learning, and Robotics.

• Shatnawi, Raed & Mishra, Alok (2021). An empirical study on software fault prediction using product and process metrics. International Journal of Information Technologies and Systems Approach. ISSN 1935-570X. 14(1), p. 62–78. doi: 10.4018/IJITSA.2021010104. Show summary

  Product and process metrics are measured from the development and evolution of software. Metrics are indicators of software fault-proneness and advanced models using machine learning can be provided to the development team to select modules for further inspection. Most fault-proneness classifiers were built from product metrics. However, the inclusion of process metrics adds evolution as a factor to software quality. In this work, the authors propose a process metric measured from the evolution of software to predict fault-proneness in software models. The process metrics measures change-proneness of modules (classes and interfaces). Classifiers are trained and tested for five large open-source systems. Classifiers were built using product metrics alone and using a combination of product and the proposed process metric. The classifiers evaluation shows improvements whenever the process metrics were used. Evolution metrics are correlated with quality of software and helps in improving software quality prediction for future releases.

• Ateşoğulları, Dilara & Mishra, Alok (2020). Automation testing tools : a comparative view . International Journal on Information Technologies and Security (IJITS). ISSN 1313-8251. 12(4), p. 63–76. Full text in Research Archive Show summary

  Effective software testing leads to assurance towards high quality in software development. Automation testing tool facilitates in faster testing process in testing stage thus completion and implementation of software on time. One of the most significant issues for automation is to select the automation-testing tool and the appropriate framework. The objective of this paper is to assess and compare twenty-one available automation-testing tools on twenty attributes in comprehensive manner. This study will assist software testing professionals and researchers towards further insight in this area. Keywords: test automation, automation tools, software testing, automation test frameworks, test automation types

• Karim, Ahmad; Kaya, Hilal; Güzel, Mehmet Serdar; Tolun, Mehmet; Çelebi, Fatih Vehbi & Mishra, Alok (2020). A novel framework using deep auto-encoders based linear model for data classification. Sensors. ISSN 1424-8220. 20(21), p. 1–21. doi: 10.3390/s20216378. Full text in Research Archive Show summary

  This paper proposes a novel data classification framework, combining sparse auto-encoders (SAEs) and a post-processing system consisting of a linear system model relying on Particle Swarm Optimization (PSO) algorithm. All the sensitive and high-level features are extracted by using the first auto-encoder which is wired to the second auto-encoder, followed by a Softmax function layer to classify the extracted features obtained from the second layer. The two auto-encoders and the Softmax classifier are stacked in order to be trained in a supervised approach using the well-known backpropagation algorithm to enhance the performance of the neural network. Afterwards, the linear model transforms the calculated output of the deep stacked sparse auto-encoder to a value close to the anticipated output. This simple transformation increases the overall data classification performance of the stacked sparse auto-encoder architecture. The PSO algorithm allows the estimation of the parameters of the linear model in a metaheuristic policy. The proposed framework is validated by using three public datasets, which present promising results when compared with the current literature. Furthermore, the framework can be applied to any data classification problem by considering minor updates such as altering some parameters including input features, hidden neurons and output classes. Keywords: deep sparse auto-encoders, medical diagnosis, linear model, data classification, PSO algorithm

• Ibrahim, Thaer & Mishra, Alok (2020). Internet of Things (IoT) and artificial neural networks towards water pollution forecasting. Rocznik Ochrona Srodowiska. ISSN 1506-218X. 22(1), p. 117–129. Full text in Research Archive Show summary

  Water could be some-times a source of danger on people's lives and property. Although it is one of the most important elements of life on this planet. This article define the threat of water pollution in Tigris River in Iraq. by collecting a data that generated by sensors that installed in a water pollution sensing project in Baghdad city, also this article aimed to detect and analyze the behavior of water environment. It is an effort to predict the threat of pollution by using advanced scientific methods like the technology of Internet of Things (IoT) and Machine learning in order to avoid the threat and/or minimize the possible damages. This can be used as a proactive service provided by E-governments towards their own citizens. Keywords: Internet of Things, E-government, water pollution prediction, Tigris river, artificial neural network

• Mishra, Alok & Otaiwi, Ziadoon (2020). DevOps and software quality : a systematic mapping. Computer Science Review. ISSN 1574-0137. 38(November), p. 1–14. doi: 10.1016/j.cosrev.2020.100308. Full text in Research Archive Show summary

  Quality pressure is one of the factors affecting processes for software development in its various stages. DevOps is one of the proposed solutions to such pressure. The primary focus of DevOps is to increase the deployment speed, frequency and quality. DevOps is a mixture of different developments and operations to its multitudinous ramifications in software development industries, DevOps have attracted the interest of many researchers. There are considerable literature surveys on this critical innovation in software development, yet, little attention has been given to DevOps impact on software quality. This research is aimed at analyzing the implications of DevOps features on software quality. DevOps can also be referred to a change in organization cultures aimed at removal of gaps between the development and operations of an organization. The adoption of DevOps in an organization provides many benefits including quality but also brings challenges to an organization. This study presents systematic mapping of the impact of DevOps on software quality. The results of this study provide a better understanding of DevOps on software quality for both professionals and researchers working in this area. The study shows research was mainly focused in automation, culture, continuous delivery, fast feedback of DevOps. There is need of further research in many areas of DevOps (for instance: measurement, development of metrics of different stages to assess its performance, culture, practices toward ensuring quality assurance, and quality factors such as usability, efficiency, software maintainability and portability). Keywords: DevOps, development, operations, software, software quality, automation, measurement, systematic mapping

• Jæger, Bjørn; Bruckenberger, Sophie A. & Mishra, Alok (2020). Critical success factors for ERP consultancies : a case study. Scandinavian Journal of Information Systems (SJIS). ISSN 0905-0167. 32(2), p. 169–202. Full text in Research Archive Show summary

  ERP implementation is a complex and expensive project for organisations because it touches upon social, behavioural and technical issues. This article presents an in-depth case study of an ERP consultancy in order to comprehensively understand ERP implementation from the consultancy’s perspective. Interviews were conducted with consultants, project managers, senior managers and other employees. The interview responses indicate that both the client and the consultancy measure success in terms of quantifiable units of time, cost and scope. In addition, qualitative measures of client maturity and client satisfaction are central to achieving project success for the consultancy when implementing ERP systems. Through incorporating critical success factors (CSFs) in the project methodology, the consultancy can ensure repeatable implementation processes, which contribute to a higher probability of success for both the consultancy and its clients. This study contributes by identifying consultancy CSFs: project management, IT environment, training and education, change management, and maintenance and support. Furthermore, the client’s maturity, and the management of client expectations are identified as unique CSFs for the ERP consultancy. This study will be beneficial for ERP consultancies, practitioners and researchers.

• Yu, Liguo & Mishra, Alok (2020). Customer Engagement Strategies of China's E-Commerce Industry and Their Impact on China's Economy Transition. In Semeradova, Tereza & Weinlich, Petr (Ed.), Impacts of Online Advertising on Business Performance. IGI Global. ISSN 9781799816188. doi: 10.4018/978-1-7998-1618-8.ch004. Show summary

  In the past 15 years, China's e-commerce industry has grown tremendously and become the world's largest e-commerce market. This chapter studies some popular e-commerce companies of China, including Alibaba, JD, and Pindoudou. Specifically, the customer engagement strategies of these companies are described and analyzed. This chapter helps readers understand how various customer engagement strategies of China's e-commerce companies have facilitated the change of their consumers' shopping habits—switching from offline shopping centers to online marketplaces and from cash-based payment to credit-based payment. The success of these customer engagement strategies has contributed to the performance improvement of e-commerce companies and could ultimately assist China to transfer from a production economy to a consumption economy. Moreover, these customer engagement strategies developed in China might also be applied to other e-businesses or marketplaces of different regions, especially developing countries that have a similar economy structure as China.

• Jæger, Bjørn & Mishra, Alok (2020). IoT platform for seafood farmers and consumers. Sensors. ISSN 1424-8220. 20(15), p. 1–15. doi: 10.3390/s20154230. Full text in Research Archive Show summary

  There has been a strong growth in aquatic products supported by the global seafood industry. Consumers demand information transparency to support informed decisions and to verify nutrition, food safety, and sustainable operations. Supporting these needs rests on the existence of interoperable Internet of Things (IoT) platforms for traceability that goes beyond the minimum “one up, one down” scheme required by regulators. Seafood farmers, being the source of both food and food-information, are critical to achieving the needed transparency. Traditionally, seafood farmers carry the costs of providing information, while downstream actors reap the benefits, causing limited provision of information. Now, global standards for labelling, data from IoT devices, and the reciprocity of utility from collecting data while sharing them represent great potential for farmers to generate value from traceability systems. To enable this, farmers need an IoT platform integrated with other IoT platforms in the value network. This paper presents a case study of an enterprise-level IoT platform for seafood farmers that satisfies consumers’ end-to-end traceability needs while extracting data from requests for information from downstream actors. Keywords: IoT platform, seafood traceability, seafood farmer, reciprocity, supply chain, value

• Gavrilović, Nebojša & Mishra, Alok (2020). Software architecture of the internet of things (IoT) for smart city, healthcare and agriculture : analysis and improvement directions. Journal of Ambient Intelligence and Humanized Computing. ISSN 1868-5137. 12, p. 1315–1336. doi: 10.1007/s12652-020-02197-3. Show summary

  Internet of things (IoT) enables organizations to automate the process and improves service delivery through Internet technology and transferring the data at the cloud level. IoT does not allow the use of a universal software architecture for different fields in which it is used, but needs to be adjusted according to the requirements of users. This paper presents an analysis of currently available types of software architectures of the IoT systems in the field of smart cities, healthcare, and agriculture. It provides a proposal for solutions and improvements of different software architecture types, interactions between identified software architecture elements that will provide better performance and simplicity. The novelty of the study is the analysis of different types of IoT software architecture such as: layered, service-oriented and cloud-based software architecture application in these areas of IoT. Based on the analysis, the study proposed the type of software architecture of the IoT system for the relevant area of application (smart city, healthcare, and agriculture). Specific points of research are: analysis of different types of software architecture applied in IoT systems, identification of functionalities available in IoT systems through different types of software architecture, the proposal for enhancement of the above functionalities, and proposal of software architecture that is most relevant to the IoT system of a particular area.

• Aubaid, Asmaa M. & Mishra, Alok (2020). A rule-based approach to embedding techniques for text document classification. Applied Sciences. ISSN 2076-3417. 10(11), p. 1–22. doi: 10.3390/app10114009. Full text in Research Archive Show summary

  With the growth of online information and sudden expansion in the number of electronic documents provided on websites and in electronic libraries, there is difficulty in categorizing text documents. Therefore, a rule-based approach is a solution to this problem; the purpose of this study is to classify documents by using a rule-based. This paper deals with the rule-based approach with the embedding technique for a document to vector (doc2vec) files. An experiment was performed on two data sets Reuters-21578 and the 20 Newsgroups to classify the top ten categories of these data sets by using a document to vector rule-based (D2vecRule). Finally, this method provided us a good classification result according to the F-measures and implementation time metrics. In conclusion, it was observed that our algorithm document to vector rule-based (D2vecRule) was good when compared with other algorithms such as JRip, One R, and ZeroR applied to the same Reuters-21578 dataset. Keywords: text classification; rule-based; word embedding; Doc2vec.

• Mishra, Deepti & Mishra, Alok (2020). Sustainability inclusion in informatics curriculum development. Sustainability. ISSN 2071-1050. 12(14), p. 1–17. doi: 10.3390/su12145769. Full text in Research Archive Show summary

  Background: Presently, sustainability is a crucial issue for human beings due to many disasters owing to climate change. Information Technology (IT) is now part of everyday life in society due to the proliferation of gadgets such as mobile phones, apps, computers, information systems, web-based systems, etc. (2) Methods: The analysis is based on recent ACM/IEEE curriculum guidelines for IT, a rigorous literature review as well as various viewpoints and their relevance for sustainability-oriented curriculum development; it also includes an assessment of key competencies in sustainability for proposed units in the IT curriculum. (3) Results: Sustainability is a critical subject for prospective IT professionals. Therefore, it is imperative to motivate and raise awareness among students and the faculty community regarding sustainability through its inclusion in the Informatics curriculum. This paper focuses on how sustainability can be included in various courses of the Informatics curriculum. It also considers recent ACM/IEEE curriculum guidelines for IT professionals, which assert that IT students should explore IT strategies required for developing a culture of green and sustainable IT. (4) Conclusions: This paper provides guidelines for IT curriculum development by incorporating sustainable elements in courses, so that future IT professionals can learn and practice sustainability in order to develop a sustainable society. Keywords: curricula; environment; information technology (IT); informatics; sustainability.

• Mishra, Alok & Mishra, Deepti (2020). Sustainable software engineering education curricula development. International Journal on Information Technologies and Security (IJITS). ISSN 1313-8251. 12(2), p. 47–56. Full text in Research Archive Show summary

  Climate change risk and environmental degradation are the most critical issues of our society. Our technology influenced daily life style involves many software and apps which are used by large society and their use is increasing than ever before. Sustainability is a significant topic for future professionals and more so for Information Technology (IT) professionals and software engineers due to its impact on the society. It is significant to motivate and raise concern among students and faculty members regarding sustainability by including it into Software Engineering curriculum. Key words: Sustainability, Sustainable Software Engineering, Curricula, Software Engineering.

• Andersen, Terje; Jæger, Bjørn & Mishra, Alok (2020). Circularity in waste electrical and electronic equipment (WEEE) directive. Comparison of a manufacturer's Danish and Norwegian operations. Sustainability. ISSN 2071-1050. 12(13), p. 1–15. doi: 10.3390/su12135236. Full text in Research Archive Show summary

  Waste electrical and electronic equipment (WEEE) as a reverse supply chain (RSC) has a low degree of circularity, mainly focusing on recovering or recycling. Targets to increase the circularity have recently been introduced in the EU WEEE directive. In this case study, we have investigated how WEEE is handled within an electric and electronic (EE) equipment manufacturer. The case study includes findings from two different Nordic countries, Norway and Denmark, with interviews of six stakeholders. The case study shows that there are significant differences in how the case company fulfills its extended producer responsibility (EPR), especially related to reporting. The study also found that there is a mismatch between the ambitions in the WEEE directive and a company’s approach related to circularity in the end-of-life phase of an EE product. Based on the results of this case study and from the literature we propose recommendations on alignment with other directives and on a common information regime within the WEEE RSC. Keywords: waste electrical and electronic equipment (WEEE); product information flow; reverse supply chain; manufacturer; circularity.

• Ateşoğulları, Dilara & Mishra, Alok (2019). White box test tools : a comparative view. International Journal on Information Technologies and Security (IJITS). ISSN 1313-8251. 11(3), p. 79–90. Show summary

  There are multiple software testing techniques in the literature. These are white, black and gray box test techniques. Each of these has different tasks and purposes. Technical selection is decisive for these tasks and objectives. In this paper, information about white box technique and approaches are described. In addition, multiple test instruments that are currently in use are examined and a comparative view is provided. As a result of this comparison, a tabular chart is presented with an information set. This information set is intended to be valuable for software testing professionals and researchers to appreciate many tools at a glance. Keywords: testing, tools, white box testing, white box testing types, coverages

• Akbulut, Sinan; Gebreyesus, Yasmin Tesfaldet; Mishra, Alok & Yazici, Ali (2019). Systematic mapping on quality in web application testing . In Varol, Asaf; Yazici, Ali; Varol, Cihan; Aygüneş, Gül Sena & Çotur, Ahmet (Ed.), 1st International Informatics and Software Engineering Conference (IISEC-2019) : “Innovative Technologies for Digital Transformation” : Proceedings Book. IEEE (Institute of Electrical and Electronics Engineers). ISSN 978-1-7281-3992-0. doi: 10.1109/UBMYK48245.2019.8965472. Show summary

  Similar to all other fields of study, assuring the quality of web applications is very important. With the aim of increasing web applications quality in testing, our task in this paper is to reflect on the results of the literature searches made in this area. The literature survey carried out in this study searches for studies in the area of quality in application testing and retrieves 1972 papers, published within the timeframe of 2006 and 2016. The publications are systematically identified, analyzed, and classified and an overview of the trends in this specialized field is presented. Systematic mapping is applied to review and structure the body of knowledge related to quality in web application testing. To conduct our study, we selected a set of 27 papers published in the area of quality in web application testing between 2006 and 2016. The results of this work can help other researchers to obtain an overview of the existing web application testing quality trends and approaches as well as to identify areas in the field that require more attention from research point of view.

• Ibrahim, Thaer; Mishra, Alok & Bosta, Atila (2019). Role of E-government in reducing disasters . TEM JOURNAL - Technology, Education, Management, Informatics. ISSN 2217-8309. 8(4), p. 1150–1158. doi: 10.18421/TEM84-07. Show summary

  Disasters affect three-quarters of the world, they cause huge losses of life and property every year. Information and communication technology (ICT) - as the backbone of e-government is one of the factors that reduce the damage caused by these disasters. This paper discusses the impact of demographic factors on citizens' readiness towards ICTs and disaster management, by conducting a questionnaire form that tests the readiness of the Iraqi citizen and the extent of their interest in this technology being threatened by disaster. Keywords: disasters, Information and Communication Technology (ICT), E-government, readiness.

• Özkan, Deniz & Mishra, Alok (2019). Agile project management tools : a brief comprative view. Cybernetics and Information Technologies (CIT). ISSN 1311-9702. 19(4), p. 17–25. doi: 10.2478/cait-2019-0033. Show summary

  Agile methodologies are becoming popular in software development. Managers are required to understand project’s progress and product quality without development documents. During Agile practices of the teams and organizations, Agile project management tools are frequently used. The use of such tools leads to achieving speed and efficiency, affects the quality of the software. The quality of final product is mostly related with to project management. Accordingly, the paper provides brief comparative perspective about the popular project management tools for agile projects. 16 popular Agile project management tools have been presented helping agile developers to plan and manage their tasks in an efficient manner. Taiga, Axosoft, Agielan, Planbox are more appropriate for start-up projects. The most twitted and most appreciated tools are reported as Jira, Trello, and VersionOne. SpiraTeam by Inflectra and Pivotal Tracker are other pricing and popular agile tools, providing flexibility to Agile developers and increase collaboration among team members. Keywords: Agile Methodologies, Agile Project Management Tool, Tools, Software Project Management.

• Kadhim, Yezi & Mishra, Alok (2019). Radial Basis Function (RBF) based on multistage autoencoders for Intrusion Detection system (IDS) . In Varol, Asaf; Yazici, Ali; Varol, Cihan; Aygüneş, Gül Sena & Çotur, Ahmet (Ed.), 1st International Informatics and Software Engineering Conference (IISEC-2019) : “Innovative Technologies for Digital Transformation” : Proceedings Book. IEEE (Institute of Electrical and Electronics Engineers). ISSN 978-1-7281-3992-0. doi: 10.1109/UBMYK48245.2019.8965627. Show summary

  In this paper, RBF-based multistage auto-encoders are used to detect IDS attacks. RBF has numerous applications in various actual life settings. The planned technique involves a two-part multistage auto-encoder and RBF. The multistage auto-encoder is applied to select top and sensitive features from input data. The selected features from the multistage auto-encoder is wired as input to the RBF and the RBF is trained to categorize the input data into two labels: attack or no attack. The experiment was realized using MATLAB2018 on a dataset comprising 175,341 case, each of which involves 42 features and is authenticated using 82,332 case. The developed approach here has been applied for the first time, to the knowledge of the authors, to detect IDS attacks with 98.80% accuracy when validated using UNSW-NB15 dataset. The experimental results show the proposed method presents satisfactory results when compared with those obtained in this field.

• Alansari, Saeeda & Mishra, Alok (2019). Inventory system transition towards ERP. In Varol, Asaf; Yazici, Ali; Varol, Cihan; Aygüneş, Gül Sena & Çotur, Ahmet (Ed.), 1st International Informatics and Software Engineering Conference (IISEC-2019) : “Innovative Technologies for Digital Transformation” : Proceedings Book. IEEE (Institute of Electrical and Electronics Engineers). ISSN 978-1-7281-3992-0. doi: 10.1109/UBMYK48245.2019.8965516. Show summary

  To do activities effectively and generate a value chain for organization competitiveness, it is required to run supply chain in best way by logistic services information system. Supply chains in the best way using logistic services information. Supply chain management has two purposes, first to deliver the product to the end users via multiple departments and, secondly, to deliver products to last customers because as it is beneficial to manage such product with coordination and monitoring everyday supply.To improve departments by equipping them with the best strategic information system, and to avoid all the associated risks its requires to have a specific system for inventory control. Therefore, the main goal of this paper is to illustrate the transition of the existing systems towards Enterprise Resource Planning (ERP). The study also proposes inception plans to develop the necessary software and search towards the best system by keeping in view many organizational constraints. To the end, a survey is carried out to measure the relationship between management models and organizational innovativeness in internal processes as

• Kaur, Kamaldeep; Khatri, Sunil Kumar; Mishra, Alok & Datta, Rattan (2018). Statistical usage testing at different levels of testing. Journal of Universal Computer Science (J.UCS). ISSN 0948-695X. 24(12), p. 1800–1820. doi: 10.3217/jucs-024-12-1800. Show summary

  Statistical Usage Testing (SUT) is the testing technique defined in Cleanroom Software Engineering model [Runeson, 93]. Cleanroom Software Engineering model is a theory based and team oriented model that is based on development and certification of software in increments using statistical quality control [Linger 96]. SUT is a black box testing technique and concentrates on how the software completes its required function from the user's perspective [Runeson, 93]. SUT is carried out by developing usage models and assigning usage probabilities. Testing is carried out on usage models by performing statistical tests which are random sequences [Trammel 95]. Statistical testing can be viewed as a statistical experiment where random test cases are selected from all the usage models [Trammel 95]. This paper demonstrates the process and benefits of applying SUT at different levels of testing. Levels of testing include Unit level, Integration level, System level and Acceptance level. SUT is generally performed at System level and Unit testing is not the part of SUT. Unit testing makes it easier to access code and debug human errors. Detecting errors at an early stage helps reducing cost and effort. The paper proposes to allow Unit testing in Cleanroom Software Engineering Model, thus making it more flexible and suitable for varied applications. Unit testing is essentially performed to ensure that the code is working correctly and meets the user specifications [istqb, 15]. Errors may also exist when modules are integrated because of interchange of data and control information between various modules. Integration testing is performed when the modules are combined together to check their behaviour and functionality after integration. Once the Integration testing phase gets successfully completed, System testing is performed on the whole system [test-institute, 15]. The paper makes use of Student record software to demonstrate the process of performing SUT at different levels. In addition to performing SUT at System level, this paper helps in understanding the advantages of applying SUT at Unit level and Integration level. Keywords: Integration Testing, Markov chains, Statistical Usage Testing (SUT), System Testing, Unit Testing

• Kılınç, Nergiz; Sezer, Leyla & Mishra, Alok (2018). Cloud-based test tools : a brief comparative view. Cybernetics and Information Technologies (CIT). ISSN 1311-9702. 18(4), p. 3–14. doi: 10.2478/cait-2018-0044. Show summary

  The concept of virtualization has brought life to the new methods of software testing. With the help of cloud technology, testing has become much more popular because of the opportunities it provides. Cloud technologies provides everything as a service, hence the software testing is also provided as a service on cloud with the privileges of lower cost of testing, and relatively less effort. There are various cloud-based test tools focusing on different aspects of software testing such as load tests, regression tests, stress tests, performance tests, scalability tests, security tests, functional tests, browser performance tests, and latency tests. This paper investigates the cloud-based testing tools focusing on different aspects of software testing. Keywords: cloud testing, performance testing, load testing, software engineering testing strategy, verification, validation, test tools

• Abdalla, Reem & Mishra, Alok (2018). Using agent-based methodologies in healthcare information systems. Cybernetics and Information Technologies (CIT). ISSN 1311-9702. 18(2), p. 123–132. doi: 10.2478/cait-2018-0033. Show summary

  This paper carries out a comparative analysis to determine the advantages and the stages of two agent-based methodologies: Multi-agent Systems Engineering (MaSE) methodology, which is designed specifically for an agent-based and complete lifecycle approach, while also being appropriate for understanding and developing complex open systems; Agent Systems Methodology (ASEME) suggests a modular Multi-Agent System (MAS) development approach and uses the concept of intra-agent control. We also examine the strengths and weaknesses of these methodologies and the dependencies between their models and their processes. Both methodologies are applied to develop The Guardian Angle: Patient-Centered Health Information System (GA: PCHIS), which is an example of agent-based applications used to improve health care information systems. Keywords: agent-based methodologies, MaSE, ASEME

• Aubaid, Asmaa M. & Mishra, Alok (2018). Text classification using word embedding in rule-based methodologies : a systematic mapping. TEM JOURNAL - Technology, Education, Management, Informatics. ISSN 2217-8309. 7(4), p. 902–914. doi: 10.18421/TEM74-31. Show summary

  With the advancing growth of the World Wide Web (WWW) and the expanding availability of electronic text documents, the automatic assignment of text classification (ATC) has become more important in sorting out information and knowledge. One of the most crucial tasks that should be carried out is document representation using word embedding and Rule-Based methodologies. As a result, this, along with their modeling methods, has become an essential step to improve neural language processing for text classification. In this paper, a systematic mapping study is a way to survey all the primary studies on word embedding to rule-based and machine learning of automatic text classification. The search procedure identifies 20 articles as relevant to answer our research questions. This study maps what is currently known about word embedding in rule-based text classification (TC). The result shows that the research is concentrated on some main areas, mainly in social sciences, shopping products classification, digital libraries, and spam filtering. The present paper contributes to the available literature by summarizing all research in the field of TC and it can be beneficial to other researchers and specialists in order to sort information. Keywords: systematic mapping, word embedding, rule-based, text classification

• Choudhary, Garvit Rajesh; Kumar, Sandeep; Kumar, Kuldeep; Mishra, Alok & Catal, Cagatay (2018). Empirical analysis of change metrics for software fault prediction. Computers and Electrical Engineering. ISSN 0045-7906. 67(April), p. 15–24. doi: 10.1016/j.compeleceng.2018.02.043. Show summary

  A quality assurance activity, known as software fault prediction, can reduce development costs and improve software quality. The objective of this study is to investigate change metrics in conjunction with code metrics to improve the performance of fault prediction models. Experimental studies are performed on different versions of Eclipse projects and change metrics are extracted from the GIT repositories. In addition to the existing change metrics, several new change metrics are defined and collected from the Eclipse project repository. Machine learning algorithms are applied in conjunction with the change and source code metrics to build fault prediction models. The classification model with new change metrics performs better than the models using existing change metrics. In this work, the experimental results demonstrate that change metrics have a positive impact on the performance of fault prediction models, and high-performance models can be built with several change metrics. Keywords: software fault prediction, eclipse, change log, metrics, software quality, defect prediction

• Abdalla, Reem & Mishra, Alok (2018). Comparing the artifacts of agent methodologies . TEM JOURNAL - Technology, Education, Management, Informatics. ISSN 2217-8309. 7(2), p. 433–438. doi: 10.18421/TEM72-27. Show summary

  Agent-oriented software engineering (AOSE) systems are often distinguished from each other based on intelligence, autonomy, and reasoning. In this recpect, agent methodologies aim to covering all important components needed to build software systems. The success of agent methodologies depends on the development of all the necessary processes within different software stages, such as analysis, design, implementation, testing and maintenance. This work introduces a comparative study of agent approches with the purpose to asseses and compare the development lifecycle processes of four different wellknown AOSE methodologies, ADELFE, PASSI, Gaia and O-MaSE to define the similarities and differences between them. We can conclude that, the development of standard agent approach that supports Multi-Agent Systems (MAS) based has become an urgent need. Keywords: Agent-Oriented Software Engineering, ADELFE, Gaia, PASSI, O-MaSE

• Gavrilović, Nebojša; Arsić, Aleksandra; Domazet, Dragan & Mishra, Alok (2018). Algorithm for adaptive learning process and improving learners’ skills in Java programming language. Computer Applications in Engineering Education. ISSN 1061-3773. 26(5), p. 1362–1382. doi: 10.1002/cae.22043. Show summary

  Adaptive approaches within distance learning systems enable adapting teachingprocess to the needs of each learner during the learning process. This paper presentsan algorithm for creating an adaptive learning process that provides knowledge andskills improvement for learners in the Java programming language. Also, it presentsthe application of the tool that checks the learner's knowledge through solvingpractical tasks from the Java programming language. The adaptive learning process inthis work leads the learner through teaching materials and practical tasks where theacquired knowledge is required to be applied. Also, the algorithm, based on themeasurement of knowledge and time spent on a particular part of the learning processwith detailed feedback and the demonstration of observed deficiencies, directs thelearner to teaching materials that allow improving the demonstrated knowledge.Teaching materials are conceived as learning objects and, as such, allow for theapplication of adaptive approach. An analysis of the effectiveness of the algorithmand tool for practical knowledge testing from the Java programming language wasdone with a test group of learners who gave their opinions and grades. Keywords: adaptive systems, algorithm for adaptive learning process, engineering education, Java grader,learning object, online self-assessment, web based learning

• Niazi, Mahmood; Mishra, Alok & Gill, Asif Qumer (2018). What do software practitioners really think about software process improvement project success? : an exploratory study. The Arabian Journal for Science and Engineering. ISSN 1319-8025. 43(12), p. 7719–7735. doi: 10.1007/s13369-018-3140-3. Show summary

  Software practitioners have always shown a significant interest in implementing software process improvement (SPI) initiatives to ensure the delivery of quality products. Software industry and SPI methodologies have evolved over a period of time; however, still many SPI initiatives have not been successful. There is a need to understand software practitioners’ perspectives on SPI success which can be helpful for tailoring or improving effective situation-specific SPI methodologies. This research presents an exploratory study of Turkish software development organizations. The main research question is: What software practitioners’ really think about SPI project success. This study was conducted with 27 Turkish software development organizations to identity and analyse important SPI factors that contribute to the success of SPI projects. The results reveal that professional growth, increased professional recognition, project planning, monitoring of project risks, providing technical support, adoption of current technologies, strong leadership and commitment are among the highest ranked factors that contribute towards the success of SPI initiatives. The findings of this research provide a foundation for further work in tailoring and improving situation-specific SPI methodologies for software project environments.

• Yazici, Ali; Mishra, Alok; Karakaya, Ziya & Üstünkök, Tolga (2018). Informatics engineering education in Turkey and expectations of software industry. In ., , (Eds.), 3rd International Conference on Computer Science and Engineering : Sarajevo - Bosnia & Herzegovina 20-23 September 2018 . IEEE (Institute of Electrical and Electronics Engineers). ISSN 978-1-5386-7893-0. p. 151–156. doi: 10.1109/UBMK.2018.8566669. Show summary

  In this study, using the ÖSYM data, the number of intakes in Informatics Engineering programs in Turkey, accreditation data and the medium of instruction of the program are summarized for the years 2016 and 2017. In addition, the software sector's expectations from the informatics engineering graduates are reassessed based on the academic studies. The developed knowledge-skill gap set was used to evaluate the situation in Turkish informatics engineering programs. Sector expectations are discussed in the context of 2017-2019 Turkey Software Sector Strategy and Action Plan prepared by the Ministry of Science, Industry and Technology of Turkey and some proposals are made for the academia. As a result, it was observed that the expectations of the software industry were similar in all studies. Additionally, the expectations were changed in the direction of developing technologies and this change should be reflected in the informatics engineering programs.

• Mishra, Deepti; Aydin, Secil; Mishra, Alok & Ostrovska, Sofiya (2018). Knowledge management in requirement elicitation: Situational methods view. Computer Standards & Interfaces. ISSN 0920-5489. 56(February 2018), p. 49–61. doi: 10.1016/j.csi.2017.09.004. Full text in Research Archive
• Akman, Ibrahim & Mishra, Alok (2017). Factors influencing consumer intention in social commerce adoption. Information Technology and People. ISSN 0959-3845. 30(2), p. 356–370. doi: 10.1108/ITP-01-2016-0006. Show summary

  Purpose: Social media remarkably changed the way of interaction between the consumers and organizations. The increased acceptance of social media has given rise to social commerce (s-commerce) and s-commerce usage is gradually increasing over the last few years. The progressive development of technologies suggests that s-commerce will become the mainstream for marketing and a literature survey indicates that there have not been many studies in this area. The purpose of this paper is to predict the factors influencing consumer intention towards the adoption of s-commerce. Design/methodology/approach: This study uses a survey approach with reference to important behavioural factors such as satisfaction, ethics, trust, enjoyment/easiness, social pressure and awareness. The research model was developed to be in line with the available literature. The data were collected using a five-point Likert scale and the research model was tested using least square regression. Findings: The results showed that user intention is significantly and positively related to perceived trust, enjoyment/easiness, social pressure, satisfaction and awareness. Also, “intention” was found to be a significant mediating factor for actual usage. Research limitations/implications: First, the questionnaire was a “snap-shot” instead of longitudinal study. Second, future research should use other moderating variables that may affect the usage of social media. Also the study could apply a variant of research methods to include other techniques such as interviews, which allow for deeper understanding of the problem and issues. Practical implications: Social media represents an important platform for electronic commerce and has one of the most metamorphic impacts on business. Therefore, investigating the usage of s-commerce with reference to important behavioural factors could provide valuable information for companies in establishing policies and strategies. It could also be useful for management studies and researchers in understanding the consumers’ attitude towards usage of social media for commercial purposes. Social implications: S-commerce creates opportunities for firms. Based on findings this research provides insights with major implications for marketers, who would like to generate direct sales on social network platforms. Originality/value: Existing literature focusses largely on the effectiveness of social media. Only a handful has endeavoured to analyse s-commerce systems and the literature on consumers’ behaviour in using s-commerce is not mature yet. This study is one of the few studies in this field, and aims to predict and explain the user acceptance of social media for commercial purposes.

• Abdalla, Reem & Mishra, Alok (2017). Application of agent methodology in healthcare information systems. TEM JOURNAL - Technology, Education, Management, Informatics. ISSN 2217-8309. 64(1), p. 147–152. doi: 10.18421/TEM61-22. Show summary

  This paper presents a case study to describe the features and the phases of the two agent methodologies. The Gaia methodology for agent oriented analysis and design, Tropos is a detailed agent oriented software engineering methodology to explore each methodology's ability to present solutions for small problems. Also we provide an attempt to discover whether the methodology is in fact understandable and usable. In addition we were collecting and taking notes of the advantages and weaknesses of these methodologies during the study analysis for each methodology and the relationships among their models. The Guardian Angle: Patient-Centered Health Information System (GA: PCHIS) is the personal system to help track, manage, and interpret the subject's health history, and give advice to both patient and provider is used as the case study throughout the paper. Keywords: Agent Methodlogies,GA:PCHIS, Gaia, Tropos

• Abdalhamid, Samia & Mishra, Alok (2017). Factors in agile methods adoption. TEM JOURNAL - Technology, Education, Management, Informatics. ISSN 2217-8309. 6(2), p. 416–421. doi: 10.18421/TEM62-29. Show summary

  There are many factors that can affect the process of adopting Agile methods during software developing. This paper illustrates the critical factors in Agile methods adoption in software organizations. To present the success and failure factors, an exploratory study is carried out among the critical factors of success and failure from existing studies. Dimensions and Factors are introduced utilizing success and failure dimensions. The mind map was used to clarify these factors. Keywords: Agile Methodlogies, Success , Failure, Adoption, Factors

• Abdalhamid, Samia & Mishra, Alok (2017). Adopting of agile methods in software development organizations : systematic mapping . TEM JOURNAL - Technology, Education, Management, Informatics. ISSN 2217-8309. 6(4), p. 817–825. doi: 10.18421/TEM64-22. Show summary

  Adoption of agile methods in the software development organization is considered as a powerful solution to deal with the quickly changing and regularly developing business environment and fullyeducated customers with constantly rising expectation, such as shorter time periods and an extraordinary level of response and service. This study investigates the adoption of agile approaches in software development organizations by using systematic mapping. Six research questions are identified, and to answer these questions a number of research papers have been reviewed in electronic databases. Finally, 25 research papers are examined and answers to all research questions are provided. Keywords: agile, software development organization, methods, systematic mapping study, adoption

• Mishra, Alok; Münch, Jürgen & Mishra, Deepti (2016). Information systems in distributed environments 2015. Software engineering notes. ISSN 0163-5948. 41(4), p. 25–26. doi: 10.1145/2967307.2967317. Show summary

  This is a report from a one-day sixth international workshop on "Information Systems in Distributed Environments" (ISDE), which was organized in conjunction with the OnTheMove Federated Conferences & Workshops (OTM 2015) October 26-30, 2015, Rhodes, Greece. The main focus of this event was to provide a venue for the discussion of challenges related to the development, operation, and maintenance of distributed information systems, and their creation in the context of global development projects. Further dissemination of research results will lead to an improvement of distributed information system development and deployment across the globe.

• Wojciechowski, Adam & Mishra, Alok (2016). The 3rd workshop on social and algorithmic issues in business support : paradigms derived from text and converted into algorithms. Software engineering notes. ISSN 0163-5948. 41(3), p. 34–35. doi: 10.1145/2934240.2934250. Show summary

  This is a report from the 3rd International Workshop on "Social and Algorithmic Issues in Business Support" (SAIBS), which was organized in conjunction with the 7th Language and Technology Conference in Poznan, Poland, on November 28, 2015. The main issue focused in research papers presented during the workshop was deriving knowledge from various text artifacts and converting the data into algorithms to use it in a systematic way in parallel cases. Utilizing social wisdom begins with observation of human behavior, analysis of artifacts, building paradigms on statistical models and converting them into algorithms. Social trend observed in XXI century, networking and business activity has several sources. A base for rapid growth is accessible technology. But the force that drives people to active contribution is an everyday challenge to become recognizable and rich. Crowd creativity is a process of merging efforts and distributed resources in order to produce new quality and new products. Utilizing social energy and productivity provides beginning to new business paradigms, which converted into algorithms, may be applied in various domains. The 3rd SAIBS Workshop was a place to discuss methods of knowledge discovery in text resources and other artifacts as well as analysis of human behavior materialized and documented in databases and artifacts. An accent was focused on utilization and commercial benefit coming from analysis and converting knowledge into algorithms.

• Yazici, Ali; Mishra, Alok & Karakaya, Ziya (2016). Teaching parallel computing concepts using real-life applications. International Journal of Engineering Education. ISSN 0949-149X. 32(2), p. 772–781. Show summary

  The need to promote parallel computing concepts is an important issue due to a rapid advance in multi-core architectures. This paper reports experiences in teaching parallel computing concepts to computer and software engineering undergraduates. By taking a practical approach in delivering the material, students are shown to grasp the essential concepts in an effective way. This has been demonstrated by implementing small projects during the course, such as computing the sum of the terms of a geometric series using pipelines, solving linear systems by parallel iterative methods, and computing Mandelbrot set (fractal). This study shows that, it is useful to provide real-life analogies to facilitate general understanding and to motivate students in their studies as early as possible via small project implementations. The paper also describes an overall approach used to develop students’ parallel computing skills and provides examples of the analogies employed in conjunction with the approach described. This approach is also assessed by collecting questionnaires and learning outcome surveys. Keywords: parallel computing, message-passing interface, speed-up factor, Flynn’s taxonomy

• Mishra, Alok; Yazici, Ali & Cetin, Semih (2016). Software evolution in Turkey. Tehnicki Vjesnik. ISSN 1330-3651. 23(3), p. 929–925. doi: 10.17559/TV-20150303225032. Show summary

  According to a recent Gartner report, Turkey is now to be considered in one of the world’s outsourcing destinations since it has secured its place in the list of top 30 countries for Information Technology (IT), and offshore services. In the last decade, the country has made excellent progress in the software sector, and this is reflected in the rise of its exports to many countries. In this article, we present an overview of advancement of Turkey’s software sector, including current trends in software process, testing, quality, and the adoption of agile methods along with techno parks and incentives provided by the government. Keywords: software; software development; software engineering education information technology; Turkey

• Mayeh, Maral; Ramayah, T. & Mishra, Alok (2016). The role of absorptive capacity, communication and trust in ERP adoption. Journal of Systems and Software. ISSN 0164-1212. 119(September), p. 58–69. doi: 10.1016/j.jss.2016.05.025. Show summary

  The use of Enterprise Resource Planning (ERP) systems is proven to be valuable in several ways and it is considered a necessity in today’s business. However, despite the high cost and effort s required in implementing ERPs, the success rate is reported unsatisfactory in Iranian organizations. It is argued that the success of ERP implementation is significantly related to the users’ adoption behavior. As one of the most important predictors of adoption behavior, this study investigates factors affecting the intention to use ERP systems. In particular, using Technology Acceptance Model (TAM), we examined the effects of absorptive capacity, communication and trust on the intention to use ERP systems. A questionnaire was sent to ERP users in 7 organizations in Iran, and 184 responses were used for the analysis. The findings suggest that trust, together with perceived ease of use and perceived usefulness, have a positive significant relationship with intention to use ERP. Furthermore, absorptive capacity and communication have a direct effect on the perceived ease of use which, in turn, impacts the intention to use ERP. As such, this study advances the current knowledge of adoption behavior by investigating the role of trust, communication and absorptive capacity on the intention to use. Keywords: ERP, Intention to use, Absorptive capacity, Communication, Trust

• Mishra, Alok; Münch, Jürgen & Mishra, Deepti (2015). Information Systems in Distributed Environments : ISDE 2014. Software engineering notes. ISSN 0163-5948. 40(5), p. 36–38. doi: 10.1145/2815021.2815035. Show summary

  This is a report from a one-day fourth international workshop on "Information Systems in Distributed Environments" (ISDE), which was organized in conjunction with the OnTheMove Federated Conferences & Workshops (OTM 2014) October 29-30, 2014, Amantea, Calabria, Italy. The main focus of this event was to provide a venue for the discussion of challenges related to the development, operation, and maintenance of distributed information systems, and their creation in the context of global development projects. Further dissemination of research results will lead to an improvement of distributed information system development and deployment across the globe.

• Saleh, Majd; Abel, Marie-Hélène & Mishra, Alok (2015). An architectural model for system of information systems. In Ciuciu, Ioana; Panetto, Herve; Debruyne, Christophe; Aubry, Alexis; Bollen, Peter; Valencia-Garcia, Rafael; Mishra, Alok; Fensel, Anna & Ferri, Fernando (Ed.), On the Move to Meaningful Internet Systems : OTM 2015 Workshops . Springer. ISSN 978-3-319-26137-9. p. 411–420. doi: 10.1007/978-3-319-26138-6_44. Show summary

  One of the most important aspects when designing and constructing an Information System is its architecture. This also applies to complex systems such as System of Information Systems (SoIS). Thus, we aim to propose an architectural model of System of Information Systems (SoIS). Though Architecture-based approaches have been promoted as a means of controlling the complexity of systems construction and evolution, what we really look for in this paper is an architectural model to aggregate services from already constructed systems. Nevertheless, it would be a good practice to compare the presented architecture of SoIS to other architecture-based approaches such as Service Oriented Architecture (SOA). Also, it is beneficial to examine how we can use the well-established standards of SOA for the designing of SoIS. In this paper we present an architectural model for System of Information Systems, and highlight the standards of Service Oriented Architecture that might help us in this task. Keywords: system of systems, system of information systems, service oriented architecture, architectural model

• Yazici, Ali; Mishra, Alok & Kontogiorgis, Paul (2015). IT Service Management (ITSM) Education and Research: Global View . International Journal of Engineering Education. ISSN 0949-149X. 31(4), p. 1071–1080.

View all works in Cristin

• Mishra, Alok (2024). Research Collaborations – Opportunities and Challenges.
• Mishra, Alok (2024). AI-enhanced Software Engineering.
• Mishra, Alok (2023). “Business Analytics for Management Decision Making” .
• Mishra, Deepti & Mishra, Alok (2023). Projects and Research Collaboration with Indian Institutions.
• Mishra, Alok (2023). Emerging Research Areas in Software Engineering for Doctoral Students and Young Researchers.
• Mayank, Pathak; Mishra, Kamta Nath; Singh, S.P. & Mishra, Alok (2023). An Automated Smart Centralized Vehicle Security System for Controlling the Vehicle Thefts/Hacking Using IOT and Facial Recognition.
• Mishra, Alok (2022). Additive Manufacturing Ramifications On Supply Chain Resilience .
• Mishra, Alok; Khan, Arif Ali; Iribarne, Luis & Mishra, Deepti (2022). Multimedia software engineering: challenges and opportunities . Multimedia Tools and Applications. ISSN 1380-7501. 81(25), p. 35533–35533. doi: 10.1007/s11042-022-13890-0.
• Mishra, Alok (2022). Sustainability in software engineering.
• Mishra, Alok (2022). Emerging trends in software engineering.
• Abdalhamid, Samia; Mohammed, Alfaroq O. M. & Mishra, Alok (2019). Agile and quality : a systematic mapping study. In ., , (Eds.), Proceedings of 2019 International Conference of Computer Science and Renewable Energies (ICCSRE) 2019 July 22-24. IEEE (Institute of Electrical and Electronics Engineers). doi: 10.1109/ICCSRE.2019.8807763. Show summary

  Recently, agile methodologies have been adopted in many application areas of developing software. Since the quality is an inherent factor of the right agile product development, so the use of agile leads to increase the quality of software. The objective of this study is to explore the quality that gained by adopting agile methods and how can be achieved. A systematic mapping study (SMS) is conducted to answer five research questions related to the study topic.

• Mishra, Alok; Khatri, Sunil Kumar; Kapur, P. K. & Kumar, Uday (2018). Quality and reliability engineering : trends and future directions . Journal of Universal Computer Science (J.UCS). ISSN 0948-695X. 24(12), p. 1677–1679. doi: 10.3217/jucs-024-12.
• Gavrilović, Nebojša; Jovanović, Slobodan & Mishra, Alok (2017). Personalized learning system based on student behavior And learning style . In Trebinjac, Bojana; Kovačević, Sanja & Jovanović, Slobodan (Ed.), Proceedings : The Eighth International Conference on e-Learning : 28-29 September 2017. Belgrade Metropolitan University. p. 34–39. Show summary

  The paper describes advantage of system for distance learning based on the student activity in lesson and on the student results (self-assessment tests). Personalized adaptive systems represent the future for this type of learning. Based on results, system create different way through the learning process. The systems automatically check how much the student kept on certain activities in the learning process, create a student model, and after all create the learning path for the student. This avoids setting same lesson path for students with basic knowledge and those with advanced knowledge. The aim of the system is to get individual users needs, goals, and attributes, which may be important for systems that adapt to user at runtime context. Keywords: Personalized learning, Adaptive learning E-Learning, Distance learning

• Mishra, Alok (2017). Sustainable software engineering : a move towards future. In Shukla, Balvinder; Khatri, Sunil Kumar & Kapur, P. K. (Ed.), 6th International Conference on Reliability, Infocom Technologies and Optimization (Trends and Future Directions) (ICRITO) : September 20-22, 2017 . IEEE (Institute of Electrical and Electronics Engineers). ISSN 978-1-5090-3012-5. doi: 10.1109/ICRITO.2017.8342401.
• Mishra, Alok; Garbajosa, Juan; Wang, Xiaofeng; Bosch, Jan & Abrahamsson, Pekka (2017). Future directions in Agile research : alignment and divergence between research and practice. Journal of Software: Evolution and Process (JSEP). ISSN 2047-7473. 29(6), p. 1–4. doi: 10.1002/smr.1884.
• Mishra, Alok (2016). Agile methods adoption in large software development projects. In Shukla, Balvinder; Khatri, Sunil Kumar & Kapur, P. K. (Ed.), 5th International Conference on Reliability, Infocom Technologies and Optimization (ICRITO) (Trends and Future Directions) : September 7-9, 2016. IEEE (Institute of Electrical and Electronics Engineers). ISSN 978-1-5090-1489-7. doi: 10.1109/ICRITO.2016.7784913.
• Mishra, Alok; Münch, Jürgen; Lassenius, Casper & Mishra, Deepti (2016). Information systems in distributed environment. Computer Standards & Interfaces. ISSN 0920-5489. 48(November), p. 183–183. doi: 10.1016/j.csi.2016.08.001.
• Garousi, Vahid; Mishra, Alok & Yazici, Ali (2015). Üniversite Yazılım Mühendisliği programları müfredatının SWEBOK kılavuzu kullanılarak değerlendirme ve iyileştirilmesi: Türkiye’de bir vaka çalışması. In Tuglular, Tugkan & Komesli, Murat (Ed.), UYMS 2015 : Turkish National Software Engineering Symposium : Proceedings of the 9th Turkish National Software Engineering Symposium : Yasar University, Izmir, Turkey, September, 9-11, 2015 . Yasar Universitesi. ISSN 1613-0073. Show summary

  Bu makalede SWEBOK 3.0 (Yazılım Mühendisliği (YM) Bilgi Tabanı Kılavuzu 3.0) sürümü kullanılarak, Türkiye'deki bir üniversitenin YM müfredatının bir değerlendirme ve iyileştirme çalışması raporlanmaktadır. Sistematik vaka çalışması yaklaşımı ile alan derslerindeki YM konularının saat bazında nicel analizleri ve SWEBOK'un 15 bilgi alanına uyumunu incelemek üzere çapraz denetimleri yapılmıştır. Uygulanan yaklaşım ile çalışma kapsamında olan YM programına yararlı gözlemler, öneriler ve somut faydalar sağlanmıştır, örneğin: (1) Yazılım Bakımı kavramının YM derslerinde yeterli derecede işlenmediği gözlemlenmiş ve bununla ilgili olarak uygulamaların müfredata katılması önerilmiştir; (2) yapılan analize dayanarak, üst düzey YM derslerinde (3. ve 4. yılında verilen) dönem projelerinde GitHub gibi bir kod sürüm sistemi kullanımı önerilmiştir ve (3) Ekonominin yazılım projelerindeki önemi nedeni ile çeşitli YM derslerinde ekonomi-tabanlı-YM, örneğin: kullanım-vakaların fayda maliyet analizi, yazılım kalite faaliyetlerinin yatırım getirisi ve ayrıca YM ekonomisi hakkında derslerde pratik çalışmalar yapılması gerektiği raporlanmıştır. YM müfredatın değerlendirme ve iyileştirilmesi ile ilgili olarak SWEBOK bağlamında birçok çalışma yapılmıştır, ancak, bu yeni yaklaşımda öncekilerden farklı olarak, SWEBOK'un en son 2014 sürümü kullanılmış ve daha kapsamlı analizler yapılmıştır. Ayrıca, bu çalışmada önerilen yaklaşımın genelleştirilmesi ve diğer üniversitelerdeki YM programlarına uygulanması mümkündür. Anahtar sözcükler: Yazılım Mühendisliği Eğitimi, Yazılım Mühendisliği müfredatı, müfredat değerlendirme, müfredat iyileştirme, SWEBOK, vaka çalışması, Türkiye’deki üniversiteler, Türkiye’de eğitim

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