Information and Software Technology最新文献

{"title":"Reinforcement learning for test case prioritization based on LLEed K-means clustering and dynamic priority factor","authors":"Zhongsheng Qian,&nbsp;Qingyuan Yu,&nbsp;Hui Zhu,&nbsp;Jinping Liu,&nbsp;Tingfeng Fu","doi":"10.1016/j.infsof.2024.107654","DOIUrl":"10.1016/j.infsof.2024.107654","url":null,"abstract":"<div><div>Integrating reinforcement learning (RL) into test case prioritization (TCP) aims to cope with the dynamic nature and time constraints of continuous integration (CI) testing. However, achieving optimal ranking across CI cycles is challenging if the RL agent starts from an unfavorable initial environment and deals with a dynamic environment characterized by continuous errors during learning. To mitigate the influence of adverse environments, this work proposes an approach to <strong>T</strong>est <strong>C</strong>ase <strong>P</strong>rioritization which incorporates Locally Linear Embedding-based <strong>K</strong>-means Clustering and <strong>D</strong>ynamic Priority Factor into <strong>R</strong>einforcement <strong>L</strong>earning (<strong>TCP-KDRL</strong>). Firstly, we exploit the K-means clustering method with Locally Linear Embedding (LLE) to mine the relationships between test cases, followed by assigning initial priority factors to the test cases. These test cases are ranked based on their initial factors, providing an improved initial learning environment for the agent in RL. Secondly, with the agent learning the ranking strategy in various cycles, we design a comprehensive reward indicator by considering running discrepancy and the position between test cases. Additionally, based on the reward values, the dynamic priority factors for the ranked test cases in each learning round of RL are adaptively updated and the sequence is locally fine-tuned. The fine-tuning strategy provides ample feedback to the agent and enables real-time correction of the erroneous ranking environment, enhancing the generalization of RL across various cycles. Finally, the experimental results demonstrate that TCP-KDRL, as an enhanced RL-based TCP method, outperforms other competitive TCP approaches. Specifically, incorporating the reward indicator and the fine-tuning strategy components, the results are significantly better than that of combining any other two components. For instance, in 12 projects, the average improvements are 0.1548 in APFD and 0.0793 in NRPA. Compared to other TCP methods, the proposed method achieves notable enhancement, with an increase of 0.6902 in APFD and 0.3816 in NRPA.</div></div>","PeriodicalId":54983,"journal":{"name":"Information and Software Technology","volume":"179 ","pages":"Article 107654"},"PeriodicalIF":3.8,"publicationDate":"2024-12-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143091906","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"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":"Improving seed quality with historical fuzzing results","authors":"Yang Li ,&nbsp;Yingpei Zeng ,&nbsp;Xiangpu Song ,&nbsp;Shanqing Guo","doi":"10.1016/j.infsof.2024.107651","DOIUrl":"10.1016/j.infsof.2024.107651","url":null,"abstract":"<div><h3>Context:</h3><div>Coverage-guided fuzzing (CGF) has achieved great success in discovering software vulnerabilities. The efficiency of CGF highly relies on the quality of the initial seed corpus. Although there have been some works in recent years investigating the initial seed selection, usually only the corpus given by developers or downloaded from the Internet is used to get the initial seed corpus.</div></div><div><h3>Objective:</h3><div>We assess several existing corpus minimization tools and find that none of them effectively leverage information contained in historical fuzzing results. The historical fuzzing results may come from previous fuzz testing or the emerging continuous fuzzing integration in the software development cycle. Therefore, we want to utilize history fuzzing results to generate a high-quality initial corpus to enhance the fuzzing performance. Besides, the size of the initial corpus will affect the fuzzing efficiency, so using a minimization tool to extract valuable seeds from historical results is essential.</div></div><div><h3>Method:</h3><div>We propose to use historical fuzzing results to help construct the initial seed corpus and further develop a corpus minimization tool named MCM (multiple corpora minimization), which can analyze multiple fuzzing results and use information including edge appearance frequency to help seed selection.</div></div><div><h3>Results:</h3><div>We implement a prototype of MCM and evaluate it on 10 open-source programs. Our experiments show that by using historical fuzzing results to expand the size of the initial seed corpus even a small number, e.g., from 20 to only 100, the branch coverage improves up to 14%. Meanwhile, MCM can achieve higher code coverage than existing corpus minimization tools, including AFL-CMIN and OPTIMIN.</div></div><div><h3>Conclusion:</h3><div>Our study shows using historical results to generate a high-quality initial corpus is practical and can effectively improve the fuzzing performance.</div></div>","PeriodicalId":54983,"journal":{"name":"Information and Software Technology","volume":"179 ","pages":"Article 107651"},"PeriodicalIF":3.8,"publicationDate":"2024-12-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143092443","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"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":"DHG-BiGRU: Dual-attention based hierarchical gated BiGRU for software defect prediction","authors":"Ruchika Malhotra,&nbsp;Priya Singh","doi":"10.1016/j.infsof.2024.107646","DOIUrl":"10.1016/j.infsof.2024.107646","url":null,"abstract":"<div><h3>Context:</h3><div>Software defect prediction (SDP) is a prominent research area focussed on anticipating defects early in the software lifecycle. Traditional machine learning models are based on static features, which are not enough to capture contextual information in the source code. In recent years, researchers have also developed deep learning models that extract semantic information from source code using the abstract syntax tree (AST). These approaches often combine static and semantic features by a simple merger operation.</div></div><div><h3>Objective:</h3><div>The article aims to address the limitations of the existing models by utilizing advanced feature extraction and integration techniques. It develops a deep learning model that can effectively prioritize the crucial features and intelligently combine the static and semantic features to provide robust predictions</div></div><div><h3>Method:</h3><div>The article proposes a novel model namely, dual-attention-based hierarchical gated BiGRU (DHG-BiGRU). The model first employs a static feature extractor (StatFE) and a semantic feature extractor (SemFE) to capture static and semantic features, respectively. Next, the outputs from StatFE and SemFE are passed to individual BiGRUs. The BiGRU output associated with the semantic features is subsequently processed by a dual attention mechanism (DAM), that captures the complex semantic information with emphasis on the most crucial features. Afterward, the hierarchical gated fusion (HGF) meticulously merges the static and semantic features. Finally, these integrated features are passed through a sigmoid function to predict defects.</div></div><div><h3>Results:</h3><div>The extensive experiments on extensively utilized datasets from the PROMISE repository reveal that DHG-BiGRU performs significantly better than the most advanced models and consistently achieves higher precision, recall and f-measure, demonstrating a reliable prediction capability.</div></div><div><h3>Conclusion:</h3><div>The results of the study underscore the potential advanced feature extraction and integration techniques for SDP. By achieving considerable improvements over state-of-the-art techniques, the proposed approach paves the way for sophisticated defect prediction models to improve software quality and reliability.</div></div>","PeriodicalId":54983,"journal":{"name":"Information and Software Technology","volume":"179 ","pages":"Article 107646"},"PeriodicalIF":3.8,"publicationDate":"2024-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143092445","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"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":"Industry 4.0/IIoT Platforms for manufacturing systems — A systematic review contrasting the scientific and the industrial side","authors":"Holger Eichelberger ,&nbsp;Christian Sauer ,&nbsp;Amir Shayan Ahmadian ,&nbsp;Christian Kröher","doi":"10.1016/j.infsof.2024.107650","DOIUrl":"10.1016/j.infsof.2024.107650","url":null,"abstract":"<div><h3>Context:</h3><div>IIoT, Industry 4.0 or CPPS software platforms are cornerstones of smart manufacturing production systems. Such platforms integrate machines, IIoT and edge devices, realize distributed (management) functionality and provide the basis for user-defined IIoT applications. Individual instances in research and industrial practice do share commonalities while they also differ significantly.</div></div><div><h3>Objective:</h3><div>A detailed overview of the platform landscape is fundamental for innovative research. However, actual surveys and literature reviews concentrate on specific aspects and usually focus only on the research works, neglecting specific aspects of the industrial use of IIoT platforms. We aim at a systematic overview of the functionalities and approaches of scientific and industrial IIoT platforms along 16 analysis dimensions and thereby exposing gaps between the focuses of research on IIoT platforms and actual industrial IIoT platforms in use. By doing so we are able to highlight future areas of interest to research as well as indicating potentially over-researched areas which are of less interest in actual industrial IIoT platforms.</div></div><div><h3>Method:</h3><div>We combine a systematic literature review of scientific IIoT platform research with a systematic analysis of industrial IIoT platforms.</div></div><div><h3>Results:</h3><div>We start off with 1620 research papers plus 70 from snowballing that we systematically filter down to 36 papers (plus 11 added by a SLR update) providing sufficient information for a data extraction, which we analyze along 16 topics to extract actual capabilities and differences of relevant platform approaches. In a second step, we contrast these results with an analysis of 21 industrial platforms.</div></div><div><h3>Conclusion:</h3><div>Similar approaches, differences and topics for future are exhibited. In comparison with 21 industrial platforms along the same analysis topics, we distill various commonalities, differences, trends and gaps.</div></div>","PeriodicalId":54983,"journal":{"name":"Information and Software Technology","volume":"179 ","pages":"Article 107650"},"PeriodicalIF":3.8,"publicationDate":"2024-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143092559","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"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":"Why do software developers like working from the office?","authors":"Nurit Zaidman ,&nbsp;Dina Van Dijk","doi":"10.1016/j.infsof.2024.107647","DOIUrl":"10.1016/j.infsof.2024.107647","url":null,"abstract":"<div><h3>Context</h3><div>The inquiry of the optimal number of working days per week for home-based (versus office-based) work, poses a challenge for many organizations within the high-tech sector. Studies in this area tend to overlook the responses and preferences of specific populations, and there is a lack of contextualization in the discussion. Given that software developers' needs have an impact on their performance, turnover, and well-being, it is important to understand their needs in relation to where work should be accomplished. Research that illuminates this topic can lead to different presumptions regarding developers’ preferences for home and/or office work.</div></div><div><h3>Objective</h3><div>To analyze preferences for home- versus office-based work among Scrum team software developers employed in a multinational organization.</div></div><div><h3>Method</h3><div>To achieve a broad, global scope and an in-depth understanding of developers’ preferences for work that was office-based or home-based, we used a combination of two data collection methods: a survey administered to 651 employees and in-depth interviews conducted with 35 employees from the same organization.</div></div><div><h3>Results</h3><div>The results show that the employees preferred to work from home for the majority of weekdays, yet, about 70 % of them preferred to come to the office at least once a week. The main reasons for home-based preference were “no commuting,” and “more productive and concentrated work”, more time for myself, and a relaxed comfortable environment. The reasons for office-based preference were to socialize with colleagues, to engage in work interactions, and to enjoy the ambiance and facilities available at the workplace.</div></div><div><h3>Conclusions</h3><div>The study illuminates developers' social preferences and their work motivations as related to their need for peer interaction, which contrasts the dominant argument in existing research that portrays developers as having a low need for social interaction. Second, the study depicts a contextual factor, working in Scrum teams, as an explaining variable to the developers’ preferences for office social interaction.</div></div>","PeriodicalId":54983,"journal":{"name":"Information and Software Technology","volume":"179 ","pages":"Article 107647"},"PeriodicalIF":3.8,"publicationDate":"2024-12-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143092442","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"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":"Performance regression testing initiatives: a systematic mapping","authors":"Luciana Brasil Rebelo dos Santos ,&nbsp;Érica Ferreira de Souza ,&nbsp;André Takeshi Endo ,&nbsp;Catia Trubiani ,&nbsp;Riccardo Pinciroli ,&nbsp;Nandamudi Lankalapalli Vijaykumar","doi":"10.1016/j.infsof.2024.107641","DOIUrl":"10.1016/j.infsof.2024.107641","url":null,"abstract":"<div><h3>Context:</h3><div>Issues related to the performance of software systems are crucial, as they have the potential to impede the effective utilization of products, compromise user satisfaction, escalate costs, and lead to failures. Performance regression testing has been identified as a prominent research domain, since it aims to prevent anomalies and substantial slowdowns.</div></div><div><h3>Objective:</h3><div>The objective of this paper is to examine recent approaches proposed in the literature concerning performance regression testing. Our interest lies in contributing insights that offer a forward-looking perspective on what is essential in this promising research domain.</div></div><div><h3>Methods:</h3><div>We carried out a systematic mapping study with the objective of gathering information on various initiatives related to performance regression testing. Our methodology follows the state-of-the-art guidelines for systematic mappings comprising planning, conducting, and reporting activities, thus obtaining a comprehensive set of selected studies.</div></div><div><h3>Results:</h3><div>Our selection includes 68 papers, and our analysis focuses on four key research questions, delving into (i) publication trends, (ii) developed approaches, (iii) conducted evaluations, and (iv) challenges. As a result of this investigation, we present a roadmap highlighting research opportunities.</div></div><div><h3>Conclusion:</h3><div>This flourishing research field entails a broad set of challenges, such as deciding the granularity of tests and the frequency of launching the performance regression process. Consequently, there is still much work to be undertaken to trade-off between the accuracy and the efficiency of capturing complex performance issues across diverse application domains and/or execution environments.</div></div>","PeriodicalId":54983,"journal":{"name":"Information and Software Technology","volume":"179 ","pages":"Article 107641"},"PeriodicalIF":3.8,"publicationDate":"2024-12-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143128051","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"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":"Locating requirements in backlog items: Content analysis and experiments with large language models","authors":"Ashley T. van Can,&nbsp;Fabiano Dalpiaz","doi":"10.1016/j.infsof.2024.107644","DOIUrl":"10.1016/j.infsof.2024.107644","url":null,"abstract":"<div><h3>Context:</h3><div>As agile development has become mainstream, requirements are increasingly managed via issue tracking systems (ITSs). These systems provide a single point of access to the product and sprint backlogs, bugs, ideas, and tasks for the development team. ITSs do not clearly separate requirements from work items.</div></div><div><h3>Objective:</h3><div>We first tackle a <em>knowledge problem</em> concerning how requirements are formulated in ITSs, including their categorization and granularity, the presence of multiple requirements, and the existence of a motivation. Second, to assist practitioners in finding requirements in poorly organized ITSs without changing their way of working, we investigate the potential of automated techniques for identifying and classifying requirements in backlog items.</div></div><div><h3>Method:</h3><div>Through quantitative content analysis, we analyze 1,636 product backlog items sampled from fourteen projects. To explore automated techniques for identifying requirements, we experiment with large language models (LLMs) due to their recent significance in NLP.</div></div><div><h3>Results:</h3><div>The labeling of backlog items is largely inconsistent, and user-oriented functional requirements are the prevalent category. A backlog item often contains multiple requirements with different levels of granularity. The experiments with LLMs reveal that encoder-only models (BERT and RoBERTa) are most suitable for extracting and classifying requirements in backlog items compared to decoder-only models (Llama 3, Mistral 7B and ChatGPT with GPT 4).</div></div><div><h3>Conclusion:</h3><div>We reveal knowledge and patterns about requirements documentation in ITSs, leading to a better empirical understanding of Agile RE. The experimental results with LLMs provide the foundation for developing automated, unobtrusive tools that identify and classify requirements in ITSs.</div></div>","PeriodicalId":54983,"journal":{"name":"Information and Software Technology","volume":"179 ","pages":"Article 107644"},"PeriodicalIF":3.8,"publicationDate":"2024-12-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143091909","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"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":"Exploring the impact of feedback on remote SW development teams","authors":"Ana Beatriz Cavalcanti ,&nbsp;Carina Alves ,&nbsp;João Araújo","doi":"10.1016/j.infsof.2024.107649","DOIUrl":"10.1016/j.infsof.2024.107649","url":null,"abstract":"<div><h3>Context</h3><div>Feedback is essential in the routine of software development teams. It provides information on professionals’ performance, align goals, and manage conflicts. The growing adoption of the remote work model has created new challenges for the effective use of feedback by organizations. Despite the recognized importance of feedback, few studies focused on understanding how feedback practices are currently conducted in remote software development teams.</div></div><div><h3>Objective</h3><div>This work aims to explore the impact of feedback on software development teams working remotely. In addition, we aim to provide valuable insights on how teams can optimize the outcomes of feedback practices.</div></div><div><h3>Method</h3><div>We adopted a mixed-method approach to investigate how feedback practices are conducted in remote software development teams. We performed a multivocal literature review to map the benefits, challenges, and good practices mentioned in the literature. Then, we conducted semi-structured interviews with 10 leaders and managers to understand their perceptions about feedback practices. Finally, we surveyed 83 team members to understand their perceptions and feelings about receiving feedback.</div></div><div><h3>Results</h3><div>We found out that the key benefits of feedback include a boost in individual engagement and team performance. In contrast, common challenges involved in remote feedback are communication gaps due to the adoption of digital channels and difficulty in providing and receiving negative feedback. Finally, our study proposes good practices to improve the feedback outcomes, such as: using multidimensional indicators to evaluate team members, providing a tangible goal-oriented development plan, and adopting continuous feedback follow-up.</div></div><div><h3>Conclusion</h3><div>We synthesized evidence from multiple sources by adopting three research methods to understand the effects of feedback on remote software development teams. Finally, we provided a set of actionable insights on how to optimize the feedback on remote software development teams.</div></div>","PeriodicalId":54983,"journal":{"name":"Information and Software Technology","volume":"179 ","pages":"Article 107649"},"PeriodicalIF":3.8,"publicationDate":"2024-12-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143092335","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"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":"Service engineering for quantum computing: Ensuring high-quality quantum services","authors":"Ana Díaz ,&nbsp;Jaime Alvarado-Valiente ,&nbsp;Javier Romero-Álvarez ,&nbsp;Enrique Moguel ,&nbsp;Jose Garcia-Alonso ,&nbsp;Moisés Rodríguez ,&nbsp;Ignacio García-Rodríguez ,&nbsp;Juan M. Murillo","doi":"10.1016/j.infsof.2024.107643","DOIUrl":"10.1016/j.infsof.2024.107643","url":null,"abstract":"<div><h3>Context:</h3><div>Quantum computing is transforming the world and driving advanced applications in fields such as healthcare and economics. However, ensuring high-quality quantum software remains critical to its adoption across the industry. As quantum technology moves closer to practical applications, it faces significant challenges. Developers face platform-dependent complexities that make the creation of quantum applications a time-consuming process. In addition, the lack of mature tools further hampers progress and can compromise the quality of service.</div></div><div><h3>Objective:</h3><div>The objective of this paper is to address the pressing need for quantum software quality assurance, presenting a solution for defining and using quantum services, by employing classical service engineering techniques and methods.</div></div><div><h3>Methods:</h3><div>A process is presented for improving the generation, deployment, and quality assessment of quantum services using an extended OpenAPI Specification and the SonarQube tool. This process also integrates the automatic generation of code for the IBM Quantum provider and its deployment in containers ready for user consumption.</div></div><div><h3>Results:</h3><div>After a detailed and individualized evaluation of the 40 implementations of quantum algorithms using the developed environment, the results reveal significant variability in the analyzability of the algorithms. This will serve in the future as a reference and guide for the continuous improvement of quantum algorithms in terms of their performance and efficiency in solving complex problems in various quantum application areas.</div></div><div><h3>Conclusions:</h3><div>This research offers a fundamental contribution to the evolution of quantum computing by introducing a comprehensive framework for quantum software quality assurance. The proposed approach not only addresses some of the existing problems in quantum software, but also paves the way for the development of quantum algorithms and their servitization.</div></div>","PeriodicalId":54983,"journal":{"name":"Information and Software Technology","volume":"179 ","pages":"Article 107643"},"PeriodicalIF":3.8,"publicationDate":"2024-12-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143091908","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"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":"Improving bug triage with the bug personalized tossing relationship","authors":"Wei Wei ,&nbsp;Haojie Li ,&nbsp;Xinshuang Ren ,&nbsp;Feng Jiang ,&nbsp;Xu Yu ,&nbsp;Xingyu Gao ,&nbsp;Junwei Du","doi":"10.1016/j.infsof.2024.107642","DOIUrl":"10.1016/j.infsof.2024.107642","url":null,"abstract":"<div><h3>Background:</h3><div>In open-source software projects, the main task of bug triage is accurately assigning bugs to appropriate developers. Statistics indicate that about 50% of bugs are reassigned (also called “tossed”) at least once, greatly extending the time for bug fixing. Research studies have shown that combining historical tossing relationships can significantly improve bug triage performance.</div></div><div><h3>Objective:</h3><div>The current research on utilizing bug tossing relationships can be mainly divided into two categories: (1) During the reassignment phase, only developers with the highest probability of tossing relationships are selected. (2) Use attribute filtering mechanism to filter and match developers. However, these approaches fail to fully consider the matching degree between developers’ abilities and the knowledge required to fix current bugs. We are attempting to propose an approach to address the above problem.</div></div><div><h3>Approach:</h3><div>We propose an approach to improve bug triage with the Bug Personalized Tossing Relationship (BPTRM). It uses a tossing transition probability matrix derived from historical tossing paths to help recommend suitable developers for solving bug reports.</div></div><div><h3>Result:</h3><div>Experimental results from various data sets within Eclipse and Mozilla indicate that BPTRM improves average recommendation performance by at least 14.38% compared to different initial assignment approaches. In addition, compared to baselines, BPTRM improves the average accuracy by 14.66% and shortens the average bug tossing length by 16.19%.</div></div><div><h3>Conclusion:</h3><div>1. The BPTRM approach, combined with personalized bug tossing relationships, precisely matches developers’ abilities and the knowledge required to fix current bugs. 2. This effectively improves the bug triage’s accuracy and shortens the bug tossing’s length.</div></div>","PeriodicalId":54983,"journal":{"name":"Information and Software Technology","volume":"179 ","pages":"Article 107642"},"PeriodicalIF":3.8,"publicationDate":"2024-12-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143092440","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}