The structural features of a code section that may indicate a more serious issue with the design of a system or code are known as code smells. Design patterns, on the other hand, are meant to describe the best reusable solution for creating object‐oriented software systems. Even though design patterns and code smells are very different, they may co‐occur. In fact, there may be a significant connection among the two, which requires further research. This study aims to (i) identify design patterns and code smells in web gaming code, (ii) investigate the co‐occurrence of the two, and (iii) analyze the effects of these co‐occurrences on internal quality aspects of code. An experiment is carried out on JavaScript (JS) web games utilizing machine learning classifiers to investigate the influence of co‐occurrence on potential code smells and design patterns to evaluate games from a quality perspective. Moreover, statistical testing is performed to identify the impact of co‐occurrences of code smells and design patterns on internal quality attributes. After examining the data, we determined that random forest is the most effective classifier, achieving an accuracy of 99.126% and 98.99% for both experimental situations, respectively. Moreover, on applying the Wilcoxon signed rank test, we found that co‐occurrence has no impact on the coupling and complexity of web games codes, whereas there is a significant impact of co‐occurrence on cohesion, size, and inheritance. Our results may guide developers in writing efficient games code to add to this swiftly growing market.

Mobile app development necessitates extracting domain-specific, essential, and innovative features that align with user needs and market trends. Determining which features provide a competitive advantage is a complex task, often managed manually by product managers. This study addresses the challenge of automating feature mining and recommendation by identifying similar apps based on user-provided descriptions. The proposed approach integrates Named Entity Recognition (NER) for feature extraction from mined Google Play app data with BERT (Bidirectional Encoder Representations from Transformers) and Topic Modeling to find comparable apps. Our top-performing model, which uses Non-negative Matrix Factorization (NMF) for Topic Modeling with Sentence-BERT (SBERT) embeddings, achieves an F1 score of 87.38%.

Abstract Cyber‐physical systems (CPS) are applicable in emerging industries such as health, energy, autonomous vehicles, and Industrial Internet of Things (IIOT). In CPS the physical assets, that is, actuators and sensors, etc. communicate with each other over a messaging protocol. This communication process of CPS makes them vulnerable to cyber‐attacks which challenge the system safety, making security and safety two major concerns for CPS. Both safety and security risks are considered separately in literature. However, the International Society of Automation (ISA) focuses on the alignment of security and safety risks of CPS. Weak or no alignment in safety and security of a system may result in an inefficient or partially protected system which could end up in disasters. This pressed the need for an integrated safety‐security risk management process. For this purpose, we used a tetra packaging case study to (i) examine the vulnerabilities of CPS by running the risk management process, (ii) identify safety‐security requirements, and (iii) align retrieved safety‐security requirements with the relevant standards. The results show (i) safety hazards and security risks along with their severity and priority, (ii) mitigation guidelines are provided by consulting IEC 61508, and (iii) 15 safety‐security requirements are identified and are aligned with ISO9001 Packaging and labeling machine standard.

Abstract The increased need for constant connectivity and complete automation of existing systems fuels the popularity of Cyber Physical Systems (CPS) worldwide. Increasingly more, these systems are subjected to cyber attacks. In recent years, many major cyber‐attack incidents on CPS have been recorded and, in turn, have been raising concerns in their users' minds. Unlike in traditional IT systems, the complex architecture of CPS consisting of embedded systems integrated with the Internet of Things (IoT) requires rather extensive planning, implementation, and monitoring of security requirements. One crucial step to planning, implementing, and monitoring of these requirements in CPS is the integration of the risk management process in the CPS development life cycle. Existing studies do not clearly portray the extent of damage that the unattended security issues in CPS can cause or have caused, in the incidents recorded. An overview of the possible risk management techniques that could be integrated into the development and maintenance of CPS contributing to improving its security level in its actual environment is missing. In this paper, we are set out to highlight the security requirements and issues specific to CPS that are discussed in scientific literature and to identify the state‐of‐the‐art risk management processes adopted to identify, monitor, and control those security issues in CPS. For that, we conducted a systematic mapping study on the data collected from 312 papers published between 2000 and 2020, focused on the security requirements, challenges, and the risk management processes of CPS. Our work aims to form an overview of the security requirements and risks in CPS today and of those published contributions that have been made until now, towards improving the reliability of CPS. The results of this mapping study reveal (i) integrity authentication and confidentiality as the most targeted security attributes in CPS, (ii) model‐based techniques as the most used risk identification and assessment and management techniques in CPS, (iii) cyber‐security as the most common security risk in CPS, (iv) the notion of “mitigation measures” based on the type of system and the underline internationally recognized standard being the most used risk mitigation technique in CPS, (v) smart grids being the most targeted systems by cyber‐attacks and thus being the most explored domain in CPS literature, and (vi) one of the major limitations, according to the selected literature, concerns the use of the fault trees for fault representation, where there is a possibility of runtime system faults not being accounted for. Finally, the mapping study draws implications for practitioners and researchers based on the findings.

Abstract Cyber physical systems (CPSs) are safety‐critical, be it weapon systems, smart medical devices, or grid stations. This makes ensuring security of all the components constituting a CPS unavoidable. The rise in the demand of interconnectedness has made such systems vulnerable to attacks, ie, cyberattacks. Over 170 cases of cyber‐security breaches in CPS were reported over the past two decades. An increase in the number of cyberattack incidents on CPS makes them more exposed and less trustworthy. However, identifying the security requirements of the CPS to pinpoint the relevant risks may help to counteract the potential attacks. Literature reveals that the most targeted security requirements of CPS are authentication, integrity, and availability. However, little attention has been paid on certain crucial security attributes such as data freshness and nonrepudiation. One major reason of security breaches in CPS is the lack of custom or generalized countermeasures. Therefore, we propose a security risk mitigation framework for a CPS focused on constraints, ie, authentication, data integrity, data freshness, nonrepudiation, and confidentiality. Furthermore, we evaluate the proposed work using a case study of a safety critical system. The results show a decrease in the severity of the identified security risks, ie, man‐in‐the‐middle attack, spoofing, and data tempering.

Requirements prioritization plays an important role in driving project success during software development. Literature reveals that existing requirements prioritization approaches ignore vital factors such as interdependency between requirements. Existing requirements prioritization approaches are also generally time-consuming and involve substantial manual effort. Besides, these approaches show substantial limitations in terms of the number of requirements under consideration. There is some evidence suggesting that models could have a useful role in the analysis of requirements interdependency and their visualization, contributing towards the improvement of the overall requirements prioritization process. However, to date, just a handful of studies are focused on model-based strategies for requirements prioritization, considering only conflict-free functional requirements. This paper uses a meta-model-based approach to help the requirements analyst to model the requirements, stakeholders, and inter-dependencies between requirements. The model instance is then processed by our modified PageRank algorithm to prioritize the given requirements. An experiment was conducted, comparing our modified PageRank algorithm's efficiency and accuracy with five existing requirements prioritization methods. Besides, we also compared our results with a baseline prioritized list of 104 requirements prepared by 28 graduate students. Our results show that our modified PageRank algorithm was able to prioritize the requirements more effectively and efficiently than the other prioritization methods.

Continuous delivery and rapidly changing requirements in agile environments force the developers to put non-functional requirements (NFRs) on halt till maintenance phase. However, neglecting NFRs during prioritization phase may lead to inaccurate estimations for software projects resulting in high maintenance cost and failures. The subjective and uncertain nature of non-functional requirements makes them unfit to be prioritized using conventional prioritization methods. Although the existing literature reports on inadequate consideration given to NFRs prioritization, still no comprehensive systematic effort has been done to report the limitations and evaluation mechanisms of existing NFRs prioritization approaches. Requirements engineering society lacks a broad understanding of NFRs prioritization approaches and the challenges which need to be overcome. Therefore, we aim to investigate (i) the existing NFR prioritization techniques and their validation mechanisms, (ii) the role of Artificial Intelligence (AI) in NFRs prioritization, and (iii) the limitations of existing NFRs prioritization techniques. For this, we reviewed the literature published from 2008 till present and extracted 30 studies. The results reveal twenty-five NFRs prioritization techniques out of which only three are AI based. The major limitations we have come across are that most of the NFRs prioritization techniques are not scalable to large datasets, inter-dependencies between functional requirements (FRs) and NFRs are ignored, and the uncertainties associated with NFRs are not considered at all. However, the literature suggests that AI-based techniques and Fuzzy logic may be used to solve issues such as uncertainties i.e. ambiguities, vagueness, and subjective opinions of stakeholders. This review adds to the existing body of knowledge on NFRs and motivates the practitioners to focus on the NFR prioritization by highlighting the limitations of the existing methods.

Software development industry is growing rapidly and so are the time and budget constraints getting stringent. After Scrum, the widely adopted agile method, agile practitioners are now shifting towards Kanban due to its effective communication facilitation, transparency and limited work in progress traits. Since, the industry is in transition from scrum to Kanban therefore we don't find many empirical studies yielding results of adopting Kanban. Therefore, in this study we aim to explore more on Kanban teams. Mainly, we aim to find the impact of Kanban team's communication patterns on their iteration performance and quality. The findings revealed that the centralization communication patterns have negative impact on iteration performance and quality of a project. However, small world communication pattern has positive impact on iteration performance and quality of a project.