Journal of Software-Evolution and Process最新文献

{"title":"More Than Just Game Elements—A Taxonomy of Considerations for Gamification Projects and Research","authors":"Kristina Nagel,&nbsp;Anna C. Weigand,&nbsp;Laura Meiser,&nbsp;Maria Rauschenberger,&nbsp;Maria José Escalona","doi":"10.1002/smr.70142","DOIUrl":"https://doi.org/10.1002/smr.70142","url":null,"abstract":"<p>The field of gamification research lacks consistency regarding the naming and categorization of methods and concepts. It also shows inconsistencies in terms of which influencing factors are considered and reported. These inconsistencies hinder the retrievability and comparability of gamification studies and encourage criticism of the research field. Current taxonomies investigate inconsistencies regarding game elements, but there is no research regarding the naming of other relevant factors such as the surrounding context and processes. Therefore, we conducted a systematic literature review to identify several factors that must be considered when conducting and reporting gamification research. We followed the <i>Extended Taxonomy Design Process</i> to structure our findings into a taxonomy of considerations for gamification projects and research. The result is a taxonomy with three dimensions (<i>Context and Organization</i>, <i>Project Strategy</i>, and <i>Gamification Strategy</i>), 12 categories, and 10 subcategories. This taxonomy can be used (1) as a road map for what to consider when planning a gamification project, (2) as a way to identify methods and tools for the implementation of gamification, and (3) as a guide for documentation when reporting gamification research.</p>","PeriodicalId":48898,"journal":{"name":"Journal of Software-Evolution and Process","volume":"38 6","pages":""},"PeriodicalIF":1.6,"publicationDate":"2026-06-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/smr.70142","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148324113","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Blockchain-Based Smart Contracts to Revolutionize the Information Technology Business","authors":"Muteeb Alahmari","doi":"10.1002/smr.70143","DOIUrl":"https://doi.org/10.1002/smr.70143","url":null,"abstract":"<div>\u0000 \u0000 <p>In the rapidly evolving field of information technology (IT), blockchain-based smart contracts have emerged as a transformative force, redefining the mechanisms of digital agreements and transactions. These self-executing contracts, with terms directly written into code on a blockchain, promise to enhance the automation, transparency and security of business processes. The integration of smart contracts into IT businesses stands as a critical innovation, aiming to streamline operations and foster trust in digital interactions. This paper aims to identify and prioritize the key variables influencing the adoption of blockchain-based smart contracts within IT businesses. To achieve the stated objective, initially, a systematic literature review (SLR) was conducted to identify the variables of blockchain-based smart contracts in IT businesses. Secondly, questionnaire-based survey was conducted with IT professionals and experts, to get the experts perceptions on identified variables. The study further applied the fuzzy analytic hierarchy process (AHP) to evaluate and prioritize the identified variables based on their significance and impact on the adoption process. The research successfully identified 16 critical variables that significantly influence the adoption of blockchain-based smart contracts in IT businesses. These variables were categorized and analyzed to understand their roles and interdependencies in the adoption process. The fuzzy AHP results revealed a hierarchical ranking of these variables, highlighting those with the most substantial impact on successful adoption, such as “security and privacy concerns,” “technical complexity,” and “regulatory and legal challenges.” The integration of blockchain-based smart contracts presents both opportunities and challenges for IT businesses. The identified variables and their prioritization offer a roadmap for organizations to navigate the complexities of adopting this technology.</p>\u0000 </div>","PeriodicalId":48898,"journal":{"name":"Journal of Software-Evolution and Process","volume":"38 6","pages":""},"PeriodicalIF":1.6,"publicationDate":"2026-06-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148282630","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A Systematic Review of Time Pressure and Cybersecurity Decision-Making in Software Development","authors":"Ruqaya Gilal,&nbsp;Abdul Rehman Gilal,&nbsp;Mohammad Muhiuddin Abro,&nbsp;Abdul Sattar Palli,&nbsp;Aeshah Alsughayyir,&nbsp;Abdullah Alshanqiti,&nbsp;Abdullah Almogahed,&nbsp;Mazni Omar","doi":"10.1002/smr.70147","DOIUrl":"https://doi.org/10.1002/smr.70147","url":null,"abstract":"<div>\u0000 \u0000 <p>In secure software development, time pressure has a significant impact on how people make decisions, especially when it comes to high-stakes cybersecurity activities. As development teams adopt agile workflows and short release cycles, security-related decisions are being made under progressively greater pressure. This paper examines the effects of time pressure on cognitive function and the caliber of decisions made in software development contexts related to cybersecurity. In addition, this review aims to identify recurrent patterns of bias, inaccuracy, and risky behavior, as well as to highlight gaps in current research and practice. Relevant articles published between 2015 and 2024 were chosen from six main academic databases, following the systematic literature review (SLR) guidelines of Kitchenham and Charters. Peer-reviewed research on software engineering, security decision-making, and time pressure was the emphasis of the inclusion criteria. A total of 20 core studies were analyzed using thematic synthesis. According to the review, time pressure is consistently linked to cognitive overload, stress-induced shortcuts, and heuristic-driven decisions, which frequently result in unsafe coding, insufficient patching, and inaccurate risk assessments. However, the impact varies depending on context, task type, and individual or team resilience. It is noteworthy that certain cognitive biases, including confirmation bias, seem to persist despite time limits, indicating that mitigation calls for more than just time management. While time pressure remains a significant risk factor in secure software development, it interacts with broader human and organizational factors. Validated therapies and team-based and longitudinal research are lacking in the field. This review calls for human-centered design of tools, targeted training, and cultural practices that support secure decision-making under time pressure.</p>\u0000 </div>","PeriodicalId":48898,"journal":{"name":"Journal of Software-Evolution and Process","volume":"38 6","pages":""},"PeriodicalIF":1.6,"publicationDate":"2026-06-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148282315","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Method for the Development of Biometric Systems Based on Scrum and ISO/IEC 24745 Standard","authors":"John Escobar-Ucrus,&nbsp;David Mauricio,&nbsp;Gloria Arcos-Medina","doi":"10.1002/smr.70141","DOIUrl":"https://doi.org/10.1002/smr.70141","url":null,"abstract":"<div>\u0000 \u0000 <p>Biometric systems play a crucial role in institutions where security is a priority. However, there is currently no specific guideline addressing security deficiencies during their development. This study proposes an agile method for the development of biometric systems, designed to meet the strict security and privacy requirements of the ISO/IEC 24745 standard. The method combines the five phases of the Scrum methodology (initiation, planning, implementation, retrospective, and release), 19 processes from the Scrum Body of Knowledge Guide (SBOK), 120 best practices (ABP), and 19 specific activities aimed at meeting the requirements of the standard. To evaluate its effectiveness, two biometric systems were developed: one for prison record management, using the proposed method, and another for prison visit management, using traditional Scrum. Both projects were carried out by the same team of engineers. The results showed that the proposed method increased agility by 40% and improved security by 71% compared with the traditional methodology. These results highlight the method's ability to optimize both agility and security in the development of biometric systems, emphasizing its relevance in contexts where data protection and efficiency are essential.</p>\u0000 </div>","PeriodicalId":48898,"journal":{"name":"Journal of Software-Evolution and Process","volume":"38 6","pages":""},"PeriodicalIF":1.6,"publicationDate":"2026-06-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148281970","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Factors to Foster Resilience Against Coding Stressors of Agile Software Developers","authors":"Ramón R. Palacio,&nbsp;Gilberto M. Córdova,&nbsp;Alba C. Martínez,&nbsp;Gilberto Borrego,&nbsp;Aurora Vizcaíno","doi":"10.1002/smr.70139","DOIUrl":"https://doi.org/10.1002/smr.70139","url":null,"abstract":"<p>IT workers, especially software developers, undergo high stress levels due to their intellectual activity, which requires creativity and problem-solving skills for specific situations. These circumstances often lead to a fast-paced lifestyle, including sleep deprivation, which is often worn as a badge of honor. These demanding routines can have long-term negative consequences for their health. Therefore, software developers need to understand the dimensions that positively affect resilience with respect to job demand-control. In this work, the problem of how software developers address the pressure caused by the workload through resilience was addressed; some important findings of this study are the following: (1) The greater the social support, meaning the work done by software developers is supported and recognized, the higher the level of resilience the subjects of the sample present. (2) There is a higher level of job control and social support in male programmers compared with female programmers, as well as individuals who suffer from high blood pressure have less resilience and job control. (3) The levels of resilience are proportional to the perception that the employee has about job control; it is understood that the greater job control the developer feels about his responsibilities, the greater the resilience will be.</p>","PeriodicalId":48898,"journal":{"name":"Journal of Software-Evolution and Process","volume":"38 6","pages":""},"PeriodicalIF":1.8,"publicationDate":"2026-06-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/smr.70139","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148237932","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Syn2Vec: A Semantic-Aware Initialization Method for AST Path–Based Code Representation","authors":"Xuekai Sun,&nbsp;Shi Dong,&nbsp;Xianyu Zuo","doi":"10.1002/smr.70145","DOIUrl":"https://doi.org/10.1002/smr.70145","url":null,"abstract":"<div>\u0000 \u0000 <p>Although abstract syntax tree (AST) path–based approaches have proven effective, the impact of node embedding initialization methods on model performance remains understudied. This work presents a comprehensive investigation of node embedding initialization for AST path–based code analysis models, proposing Syn2Vec, a semantic-aware initialization method. Our approach learns the semantic relationships between AST nodes in path contexts through a pre-training process, simultaneously capturing structural features and contextual dependencies. This generates initial embeddings that integrate both syntactic and semantic information. Syn2Vec effectively models the structural relatedness and semantic correlation between AST nodes, providing superior initialization for downstream code analysis models. Experimental results on standard code classification benchmarks demonstrate that Syn2Vec-initialized models achieve a 9.43% improvement in the F1-score compared with random initialization, conclusively establishing the importance of initialization strategies for the analysis of AST path–based code.</p>\u0000 </div>","PeriodicalId":48898,"journal":{"name":"Journal of Software-Evolution and Process","volume":"38 6","pages":""},"PeriodicalIF":1.8,"publicationDate":"2026-06-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148237485","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Studying the Evolution of TensorFlow Questions on Stack Overflow","authors":"Gbolahan Michael Adebesin,&nbsp;Sangeeta Sangeeta","doi":"10.1002/smr.70140","DOIUrl":"https://doi.org/10.1002/smr.70140","url":null,"abstract":"<div>\u0000 \u0000 <p>Deep learning has revolutionized various fields, including computer vision, natural language processing, and robotics. Python, with its simplicity and extensive libraries, has emerged as one of the primary programming languages for implementing deep learning models, and several frameworks like TensorFlow, Gaffe, and PyTorch are proposed by machine learning communities/companies for Python. TensorFlow is one of the most popular frameworks in Python for deep learning; hence, it is important to investigate the kind of issue that TensorFlow developers face. In this work, we analyzed 105,437 TensorFlow questions from the Stack Overflow website and answered five research questions. Our analysis reveals that, despite a decreasing trend in the number of questions asked, there is a high level of user engagement and satisfaction in the TensorFlow community. Our tag analysis reveals that “python,” “Keras,” “deep-learning,” “machine-learning,” and “neural-network” are the top tags associated with TensorFlow questions. We perform topic analysis and reveal four main topics: <i>machine learning and data processing</i>, <i>neural network and architecture</i>, <i>TensorFlow installation and usage</i>, and <i>TensorFlow manipulation and operation</i>. Further analysis reveals that <i>error</i>, <i>model training and prediction</i>, <i>optimization</i>, <i>data loading and preprocessing</i>, and <i>installation and deployment</i> are among the most frequently occurring subtopics. <i>ValueError</i> is the most common error and the <i>model training and prediction</i> subtopic is the most affected by errors. Our analysis reveals that the <i>TensorFlow installation and usage</i> is the most popular and difficult topic. Our study also reveals a high percentage (i.e., 31%) of broken links in TensorFlow questions.</p>\u0000 </div>","PeriodicalId":48898,"journal":{"name":"Journal of Software-Evolution and Process","volume":"38 6","pages":""},"PeriodicalIF":1.8,"publicationDate":"2026-06-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148237439","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Empirical Analysis of Challenges in Implementing Agile Methodologies in Global Software Development","authors":"Aiman Fatima,&nbsp;Muhammad Yaseen,&nbsp;Gohar Rahman,&nbsp;Umar Farooq Khattak,&nbsp;Sikandar Ali,&nbsp;Ahmed Alkhayyat,&nbsp;Fazal Hameed,&nbsp;Waqar Mehmood","doi":"10.1002/smr.70128","DOIUrl":"https://doi.org/10.1002/smr.70128","url":null,"abstract":"<div>\u0000 \u0000 <p>Agile processes have become a key factor in the continuously changing sector of contemporary software development, fundamentally affecting conventional project management approaches. In modern society, the global software development system has become a worldwide business, spreading daily. While integrating software engineering with agile methodologies offers benefits, it also presents several challenges. First, all possible challenges are identified from the literature via a systematic literature review (SLR). Next, these challenges are reviewed by software industries using a questionnaire survey across various types and levels of experts and then by comparing SLR and Questionnaire Survey. As a result of SLR, 18 challenges were identified from a total of 60 articles that were finalized after executing SLR protocol. The identified challenges were analyzed based on expert role, experience, and type. Further analysis of identified challenges was based on SLR result comparison with questionnaire survey results. This study tries to fill the gap between empirical results and literature findings. Results of systematic literature and empirical study will help industrial experts to have a better understanding of the effect of challenges of agile in GSD.</p>\u0000 </div>","PeriodicalId":48898,"journal":{"name":"Journal of Software-Evolution and Process","volume":"38 6","pages":""},"PeriodicalIF":1.8,"publicationDate":"2026-06-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148237562","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A Deep Learning Approach to Automated Bug Triaging: Investigating the Impact of Text Vectorization Methods on Effectiveness of CNN-LSTM","authors":"Ava Faghihi,&nbsp;Seyed Mostafa Fakhrahmad,&nbsp;Mohammad Hadi Sadreddini","doi":"10.1002/smr.70146","DOIUrl":"https://doi.org/10.1002/smr.70146","url":null,"abstract":"<div>\u0000 \u0000 <p>Manual bug triage is a significant bottleneck in modern software development, leading to costly project delays. While automated systems offer a solution, their performance is fundamentally tied to their ability to comprehend the semantic content of bug reports. The text representation methods that power these systems have evolved significantly, yet a systematic comparison to understand their true impact on triage accuracy has been lacking. This paper conducts a large-scale empirical study to fill this gap, comparing nine text vectorization methods—spanning from classical TF-IDF to state-of-the-art Sentence-Transformers (SBERT)—within a hybrid CNN-LSTM framework. We evaluate the models on six benchmark datasets from projects like Google Chromium and Mozilla. Performance is measured using Top-k accuracy, a standard metric for this recommendation-style task, which assesses whether the correct developer is ranked among the top predictions. Our findings reveal that sentence-level embeddings from SBERT consistently and significantly achieve the highest Top-k accuracy, outperforming all other techniques, including contextual models like BERT. Our SBERT-based model establishes a new state-of-the-art, demonstrating that a holistic, sentence-level semantic understanding is critical for effective bug-to-developer assignment.</p>\u0000 </div>","PeriodicalId":48898,"journal":{"name":"Journal of Software-Evolution and Process","volume":"38 6","pages":""},"PeriodicalIF":1.8,"publicationDate":"2026-06-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148174409","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Advancing Software Reliability: A Nonhomogeneous Poisson Process Model Integrating Dependent Failures, Testing Coverage, and Operational Uncertainties","authors":"Farhan Mateen Khan,&nbsp;Asim Munir,&nbsp;Shujaat Ali,&nbsp;Tahir Jameel,&nbsp;Mohammed Asmat Ullah Khan,&nbsp;Dilawar Shah,&nbsp;Muhammad Tahir","doi":"10.1002/smr.70120","DOIUrl":"https://doi.org/10.1002/smr.70120","url":null,"abstract":"<div>\u0000 \u0000 <p>Software reliability growth models are essential for assessing software quality, predicting failure behavior, and supporting release planning during the software development lifecycle. However, many existing models rely on simplifying assumptions, such as independent failures, perfect debugging, and fixed operational conditions, which may limit their predictive accuracy in real-world software systems. To address these limitations, this study proposes a generalized Software Reliability Growth Model based on the Non-Homogeneous Poisson Process framework. The proposed model integrates dependent failure behavior, testing coverage, fault detection intensity, repair intensity, and uncertainty in operational usage profiles. By incorporating fault dependency dynamics into the mean value function, the model provides a more realistic representation of how software failures occur and evolve during testing. The model parameters are estimated using the Maximum Likelihood Estimation method, and its performance is evaluated using 2 real-world software failure datasets. Comparative analysis is conducted against several established independent and dependent failure models using multiple goodness-of-fit and predictive accuracy criteria, including Mean Squared Error, Mean Absolute Error, Adjusted R-squared, Akaike Information Criterion, Root Mean Square Prediction Error, Predictive Power, Predictive Ratio Risk, and Theil Statistic. The results show that the proposed model achieves superior or highly competitive performance across both datasets, particularly in terms of error reduction and model fit. In addition, an optimal software release-time framework is developed to examine the effect of testing cost, error removal cost, installation cost, failure penalty cost, and expected usage duration on release decisions. The findings indicate that the proposed model can support more accurate reliability assessment, cost-sensitive release planning, and improved software quality management. Overall, the study provides a practical and analytically flexible framework for modeling software reliability under dependent failures, testing coverage variation, and operational uncertainty.</p>\u0000 </div>","PeriodicalId":48898,"journal":{"name":"Journal of Software-Evolution and Process","volume":"38 6","pages":""},"PeriodicalIF":1.8,"publicationDate":"2026-06-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148173956","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}