IEEE Transactions on Software Engineering最新文献

{"title":"Detecting Build Dependency Errors by Dynamic Analysis of Build Execution Against Declaration","authors":"Jun Lyu;Shanshan Li;Bohan Liu;He Zhang;Guoping Rong;Chenxing Zhong;Xiaodong Liu","doi":"10.1109/TSE.2025.3566225","DOIUrl":"10.1109/TSE.2025.3566225","url":null,"abstract":"Incompletely declared build dependencies in <sc>MAKE</small>-based build scripts can result in incorrect or inefficient incremental builds and parallel builds for C/C++ projects. In this sense, developing <sc>MAKE</small>-based build scripts (<italic>e</i>.<italic>g</i>., Makefile) is a nontrivial task, since practitioners need to manually enumerate the dependencies between the parts involved in one build, which may result in serious dependency errors such as missing dependencies or redundant dependencies. To tackle this challenge, the software engineering community has invested considerable effort in dependency error detection. However, due to issues such as incomplete or even missing static dependencies (<italic>i</i>.<italic>e</i>., dependencies by users declared in Makefile), existing solutions either miss certain critical dependency errors or consume significant time when parsing build dependencies, posing a major challenge to ensure both detection effectiveness and efficiency. We propose a novel approach called BuildChecker to detect the above two critical types of dependency errors in <sc>MAKE</small> dependencies that leverages a dynamically generated build execution-declaration model to improve error detection performance and reduce detection time. We evaluate BuildChecker with state-of-the-art tools (Mkcheck, Buildfs, VeriBuild, and VirtualBuild) on 30 projects. The experimental results show that BuildChecker is able to detect a total of 13,579 dependency errors with only 29 false positives, fewer than all the state-of-the-art tools. In terms of detection efficiency, BuildChecker outperforms Buildfs by 1.38 times and Mkcheck by 66.24 times. All dependency errors had been submitted to the practitioners and maintainers of these projects. At the time of writing this article, we received responses from the maintainers of four projects, who confirmed our error reports and fixes. BuildChecker demonstrates a great potential to support practitioners effectively detect build dependency errors.","PeriodicalId":13324,"journal":{"name":"IEEE Transactions on Software Engineering","volume":"51 6","pages":"1745-1761"},"PeriodicalIF":6.5,"publicationDate":"2025-03-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143901419","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"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":"OptSE: Toward Optimal Symbolic Execution","authors":"Shunkai Zhu;Jun Sun;Jingyi Wang;Xingwei Lin;Peng Cheng","doi":"10.1109/TSE.2025.3564666","DOIUrl":"10.1109/TSE.2025.3564666","url":null,"abstract":"Symbolic execution is a powerful technique that can accurately synthesize program inputs for program testing. However, the scalability of symbolic execution is often limited by the capability of the constraint solver and time for testing. With limited time budget, it is desirable to optimally select paths for symbolic execution and furthermore variables for symbolization in order to achieve the maximum code coverage. In this work, we make two technical contributions towards solving this problem. First, different from most existing solving strategies based on heuristic path selection, we formally define the ‘optimal’ strategy based on <italic>the reward of executing a given program path considering both possible code coverage and the cost of constraint solving.</i> We further prove that the problem of identifying the optimal strategy for symbolic execution can be reduced to a classic knapsack problem, whose decision problem form is NP-complete. Second, in view of the complexity in identifying the optimal strategy, we design a practical greedy algorithm, named <sc>OptSE</small>, for approximating the optimal strategy. We implemented <sc>OptSE</small> in KLEE and extensively evaluate it on a diverse set of programs. The results show that <sc>OptSE</small> is effective, i.e., achieving 12% more code coverage and detects 17% more security violations than the state-of-the-art symbolic execution tool and outperforming a collection of strategies that only consider either path selection, solving strategies or simply superimpose them.","PeriodicalId":13324,"journal":{"name":"IEEE Transactions on Software Engineering","volume":"51 7","pages":"1934-1949"},"PeriodicalIF":6.5,"publicationDate":"2025-03-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143901453","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"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 Retrieval-Augmented Deep Assertion Generation via Joint Training","authors":"Quanjun Zhang;Chunrong Fang;Yi Zheng;Ruixiang Qian;Shengcheng Yu;Yuan Zhao;Jianyi Zhou;Yun Yang;Tao Zheng;Zhenyu Chen","doi":"10.1109/TSE.2025.3545970","DOIUrl":"10.1109/TSE.2025.3545970","url":null,"abstract":"Unit testing attempts to validate the correctness of basic units of the software system under test and has a crucial role in software development and testing. However, testing experts have to spend a huge amount of effort to write unit test cases manually. Very recent work proposes a retrieve-and-edit approach to automatically generate unit test oracles, &lt;italic&gt;i.e.,&lt;/i&gt; assertions. Despite being promising, it is still far from perfect due to some limitations, such as splitting assertion retrieval and generation into two separate components without benefiting each other. In this paper, we propose AG-RAG, a retrieval-augmented automated assertion generation (AG) approach that leverages external codebases and joint training to address various technical limitations of prior work. Inspired by the plastic surgery hypothesis, AG-RAG attempts to combine relevant unit tests and advanced pre-trained language models (PLMs) with retrieval-augmented fine-tuning. The key insight of AG-RAG is to simultaneously optimize the retriever and the generator as a whole pipeline with a joint training strategy, enabling them to learn from each other. Particularly, AG-RAG builds a dense retriever to search for relevant test-assert pairs (TAPs) with semantic matching and a retrieval-augmented generator to synthesize accurate assertions with the focal-test and retrieved TAPs as input. Besides, AG-RAG leverages a code-aware language model CodeT5 as the cornerstone to facilitate both assertion retrieval and generation tasks. Furthermore, AG-RAG designs a joint training strategy that allows the retriever to learn from the feedback provided by the generator. This unified design fully adapts both components specifically for retrieving more useful TAPs, thereby generating accurate assertions. AG-RAG is a generic framework that can be adapted to various off-the-shelf PLMs. We extensively evaluate AG-RAG against six state-of-the-art AG approaches on two benchmarks and three metrics. Experimental results show that AG-RAG significantly outperforms previous AG approaches on all benchmarks and metrics, &lt;italic&gt;e.g.,&lt;/i&gt; improving the most recent baseline &lt;sc&gt;EditAS&lt;/small&gt; by 20.82% and 26.98% in terms of accuracy. AG-RAG also correctly generates 1739 and 2866 unique assertions that all baselines fail to generate, 3.45X and 9.20X more than &lt;sc&gt;EditAS&lt;/small&gt;. We further demonstrate the positive contribution of our joint training strategy, &lt;italic&gt;e.g.,&lt;/i&gt; AG-RAG improving a variant without the retriever by an average accuracy of 14.11%. Besides, adopting other PLMs can provide substantial advancement, &lt;italic&gt;e.g.,&lt;/i&gt; AG-RAG with four different PLMs improving EditAS by an average accuracy of 9.02%, highlighting the generalizability of our framework. Overall, our work demonstrates the promising potential of jointly fine-tuning the PLM-based retriever and generator to predict accurate assertions by incorporating external knowledge sources, thereby reducing the manual efforts of unit ","PeriodicalId":13324,"journal":{"name":"IEEE Transactions on Software Engineering","volume":"51 4","pages":"1232-1247"},"PeriodicalIF":6.5,"publicationDate":"2025-02-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143506985","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"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":"Robotic Visual GUI Testing for Truly Non-Intrusive Test Automation of Touch Screen Applications","authors":"Ju Qian;Guizhou Lv;Yiming Jin;Zhengyu Shang;Shuoyan Yan;Yan Wang;Lin Chen","doi":"10.1109/TSE.2025.3544441","DOIUrl":"10.1109/TSE.2025.3544441","url":null,"abstract":"Test automation intrusive to the devices under test is difficult to apply on closed or uncommon touch screen systems, e.g., a Switch game console or a digital instrument running a self-defined operating system. There is a lack of non-intrusive test automation techniques for situations where intrusive testing is impossible or not easy to apply. This paper presents RoScript, a novel robotic visual GUI testing system for truly non-intrusive test automation of touch screen applications. RoScript expresses GUI actions in visual test scripts and executes them via a physical robot. A key innovation of RoScript is a test engine armed with environment calibration techniques to achieve automated test execution without manually setting any environment parameter or adjusting the robot arms for a new subject under test. Additionally, two complementary computer vision-based methods are also introduced to record test scripts from videos of human actions on a touch screen. The RoScript test automation does not rely on the internal system of a device under test, making it truly non-intrusive and suitable for touch screen applications running on almost any platform. We evaluated RoScript on a diverse range of devices--including three Android/iOS phones, a Windows tablet, a Linux-based Raspberry Pi, a GoPro camera, and a Switch game console--across over 1100 GUI actions in 160 test scenarios. The results demonstrate RoScript’s high accuracy in test execution: 94% for executing test scripts and 97% for replicating GUI actions. Furthermore, RoScript accurately recorded about 85% of human touch screen actions into test code. These results highlight RoScript’s potential as a truly non-intrusive, cross-platform solution for GUI test automation.","PeriodicalId":13324,"journal":{"name":"IEEE Transactions on Software Engineering","volume":"51 4","pages":"1205-1231"},"PeriodicalIF":6.5,"publicationDate":"2025-02-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143470760","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"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":"Automated Co-Evolution of Metamodels and Code","authors":"Zohra Kaouter Kebaili;Djamel Eddine Khelladi;Mathieu Acher;Olivier Barais","doi":"10.1109/TSE.2025.3540545","DOIUrl":"10.1109/TSE.2025.3540545","url":null,"abstract":"<bold><i>Context.</i> </b> In Software Engineering, Model-Driven Engineering (MDE) is a methodology that considers Metamodels as a cornerstone. As an abstract artifact, a metamodel plays a significant role in the specification of a software language, particularly, in generating other artifacts of lower abstraction level, such as code. Developers then enrich the generated code to build their language services and tooling, e.g., editors, and checkers. <bold><i>Problem.</i> </b> When a metamodel evolves, the generated code is automatically updated. As a consequence, the developers’ additional code is impacted and needs to be co-evolved accordingly. <bold><i>Contribution.</i> </b> This paper proposes a new fully automatic code co-evolution approach with the evolution of the Ecore metamodel. The approach relies on pattern matching of the additional code errors. This process aims to analyze the abstraction gap between the evolved metamodel elements and the code errors to co-evolve them. <bold><i>Evaluation and Results.</i> </b> We evaluated our approach on nine Eclipse projects from OCL, Modisco, and Papyrus over several evolved versions of three metamodels. Results show that we automatically co-evolved 771 errors due to metamodel evolution with 631 matched and applied resolutions. Our approach reached an average of 82% of precision and 81% of recall, varying from 48% to 100% for precision and recall respectively. To check the effect of the co-evolution and its behavioral correctness, we rely on generated test cases before and after co-evolution. We observed that the percentage of passing, failing, and erroneous tests remained the same with insignificant variations in some projects. Thus, suggesting the behavioral correctness of the co-evolution Moreover, we conducted a comparison with the use of quick fixes that represent a usual tool for correcting code errors in an IDE. We found that our automatic co-evolution approach outperforms the use of quick fixes that lacked the context of metamodel evolution. Finally, we also compared our approach with the state-of-the-art semi-automatic co-evolution approach. As expected, precision and recall are slightly better with semi-automation, but with the burden of manual intervention, which is alleviated with our automatic co-evolution.","PeriodicalId":13324,"journal":{"name":"IEEE Transactions on Software Engineering","volume":"51 4","pages":"1067-1085"},"PeriodicalIF":6.5,"publicationDate":"2025-02-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143462505","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"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":"Understanding Security Issues in the DAO Governance Process","authors":"Junjie Ma;Muhui Jiang;Jinan Jiang;Xiapu Luo;Yufeng Hu;Yajin Zhou;Qi Wang;Fengwei Zhang","doi":"10.1109/TSE.2025.3543280","DOIUrl":"10.1109/TSE.2025.3543280","url":null,"abstract":"The Decentralized Autonomous Organization (DAO) has emerged as a popular governance solution for decentralized applications (dApps), enabling them to manage their members across the world. This structure ensures that no single entity can arbitrarily control the dApp without approval from the majority of members. However, despite its advantages, DAOs face several challenges within their governance processes that can compromise their integrity and potentially lead to the loss of dApp assets. In this paper, we first provided an overview of the DAO governance process within the blockchain. Next, we identified issues within 3 key components of the governance process: the Governance Contract, Documentation, and Proposal. Regarding the Governance Contract, malicious developers could embed backdoors or malicious code to manipulate the governance process. In terms of Documentation, inadequate or unclear documentation from developers may prevent members from effectively participating, increasing the risk of undetected governance attacks or enabling a small group of members to dominate the process. Lastly, with Proposals, members could submit malicious proposals with embedded malicious code in an attempt to gain control of the DAO. To address these issues, we developed automated methods to detect such vulnerabilities. To investigate the prevalence of these issues within the current DAO ecosystem, we constructed a state-of-the-art dataset that includes 3,348 DAOs, 144 documentation, and 65,436 proposals across 9 different blockchains. Our analysis reveals that many DAO developers and members have not given sufficient attention to these issues. For the Governance Contract, 176 DAOs allow external entities to control their governance contracts, while one DAO permits developers to arbitrarily change the contract's logic. In terms of Documentation, only 71 DAOs provide adequate guidance for their members on governance processes. As for Proposals, over 90% of the examined proposals (32,500) fail to provide consistent descriptions and code for their members, highlighting a significant gap in transparency within the DAO governance process. For a better DAO governance ecosystem, DAO developers and members can utilize the methods to identify and address issues within the governance process.","PeriodicalId":13324,"journal":{"name":"IEEE Transactions on Software Engineering","volume":"51 4","pages":"1188-1204"},"PeriodicalIF":6.5,"publicationDate":"2025-02-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143443467","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"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":"SoapFL: A Standard Operating Procedure for LLM-Based Method-Level Fault Localization","authors":"Yihao Qin;Shangwen Wang;Yiling Lou;Jinhao Dong;Kaixin Wang;Xiaoling Li;Xiaoguang Mao","doi":"10.1109/TSE.2025.3543187","DOIUrl":"10.1109/TSE.2025.3543187","url":null,"abstract":"Fault Localization (FL) is an essential step during the debugging process. With the strong capabilities of code comprehension, the recent Large Language Models (LLMs) have demonstrated promising performance in diagnosing bugs in the code. Nevertheless, due to LLMs’ limited performance in handling long contexts, existing LLM-based fault localization remains on localizing bugs within a <italic>small code scope</i> (i.e., a method or a class), which struggles to diagnose bugs for a <italic>large code scope</i> (i.e., an entire software system). To address the limitation, this paper presents S<sc>oap</small>FL, which builds an LLM-driven standard operating procedure (SOP) to automatically localize buggy methods from the entire software. By simulating the behavior of a human developer, S<sc>oap</small>FL models the FL task as a three-step process, which involves comprehension, navigation, and confirmation. Within specific steps, S<sc>oap</small>FL provides useful test behavior or coverage information to LLM through program analysis. Particularly, we adopt a series of auxiliary strategies such as Test Behavior Tracking, Document-Guided Search, and Multi-Round Dialogue to overcome the challenges in each step. The evaluation on the widely used Defects4J-V1.2.0 benchmark shows that S<sc>oap</small>FL can localize 175 out of 395 bugs within Top-1, which outperforms the other LLM-based approaches and exhibits complementarity to the state-of-the-art learning-based techniques. Additionally, we confirm the indispensability of the components in S<sc>oap</small>FL with the ablation study and demonstrate the usability of S<sc>oap</small>FL through a user study. Finally, the cost analysis shows that S<sc>oap</small>FL spends an average of only 0.081 dollars and 92 seconds for a single bug.","PeriodicalId":13324,"journal":{"name":"IEEE Transactions on Software Engineering","volume":"51 4","pages":"1173-1187"},"PeriodicalIF":6.5,"publicationDate":"2025-02-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143443466","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"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":"What Makes a Great Software Quality Assurance Engineer?","authors":"Roselane Silva Farias;Iftekhar Ahmed;Eduardo Santana de Almeida","doi":"10.1109/TSE.2025.3542763","DOIUrl":"10.1109/TSE.2025.3542763","url":null,"abstract":"Software Quality Assurance (SQA) Engineers play a critical role in evaluating products throughout the software development lifecycle to ensure that the outcomes of each phase and the final product possess the desired quality standards. In general, a great SQA engineer requires a different set of abilities from development engineers to effectively oversee the entire product development process. While recent empirical studies have explored the attributes of software engineers and managers, the quality assurance role is overlooked. As software quality gains increasing priority in the development cycles, both employers seeking skilled professionals and new graduates aspiring to excel in Software Quality Assurance (SQA) roles face a critical question: What makes a great SQA Engineer? To address this gap, we conducted 25 semi-structured interviews and surveyed 363 SQA engineers from diverse companies worldwide. We use the data collected from these activities to derive a comprehensive set of attributes for great SQA Engineers, categorized into five key areas: personal, social, technical, management, and decision-making attributes. Among these, curiosity, effective communication, and critical thinking emerged as defining characteristics of great SQA engineers. These findings offer valuable insights for future research with SQA practitioners, contextual considerations, and practical implications for research and practice.","PeriodicalId":13324,"journal":{"name":"IEEE Transactions on Software Engineering","volume":"51 4","pages":"1153-1172"},"PeriodicalIF":6.5,"publicationDate":"2025-02-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143443468","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"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":"Trustworthy Distributed Certification of Program Execution","authors":"Alex Wolf;Marco Edoardo Palma;Pasquale Salza;Harald C. Gall","doi":"10.1109/TSE.2025.3541810","DOIUrl":"10.1109/TSE.2025.3541810","url":null,"abstract":"Verifying the execution of a program is complicated and often limited by the inability to validate the code's correctness. It is a crucial aspect of scientific research, where it is needed to ensure the reproducibility and validity of experimental results. Similarly, in customer software testing, it is difficult for customers to verify that their specific program version was tested or executed at all. Existing state-of-the-art solutions, such as hardware-based approaches, constraint solvers, and verifiable computation systems, do not provide definitive proof of execution, which hinders reliable testing and analysis of program results. In this paper, we propose an innovative approach that combines a prototype programming language called Mona with a certification protocol OCCP to enable the distributed and decentralized re-execution of program segments. Our protocol allows for certification of program segments in a distributed, immutable, and trustworthy system without the need for naive re-execution, resulting in significant improvements in terms of time and computational resources used. We also explore the use of blockchain technology to manage the protocol workflow following other approaches in this space. Our approach offers a promising solution to the challenges of program execution verification and opens up opportunities for further research and development in this area. Our findings demonstrate the efficiency of our approach in reducing the number of program executions by up to 20-fold, while maintaining resilience against various malicious attacks compared to existing state-of-the-art methods, thus improving the efficiency of certifying program executions. Additionally, our approach handles up to 40% malicious workers effectively, showcasing resilience in detecting and mitigating malicious behavior. In the <small>EquivalentRegistersAttack</small> scenario, it successfully identifies divergent executions even when register values and results appear identical. Moreover, our findings highlight improvements in time and gas efficiency for longer-running problems (scaled with a multiplier of <inline-formula><tex-math>$1{,}000$</tex-math></inline-formula>) compared to baseline methods. Specifically, adopting an informed step size reduces execution time by up to 43-fold and gas costs by up to 12-fold compared to the baseline. Similarly, the informed step size approach reduces execution time by up to 6-fold and gas costs by up to 26-fold compared to a non-informed variation using a step size of <inline-formula><tex-math>$1{,}000$</tex-math></inline-formula>.","PeriodicalId":13324,"journal":{"name":"IEEE Transactions on Software Engineering","volume":"51 4","pages":"1134-1152"},"PeriodicalIF":6.5,"publicationDate":"2025-02-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143417835","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"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":"Towards measurement-based Software Engineering","authors":"Victor Basili, David Weiss, Dieter Rombach","doi":"10.1109/tse.2025.3541922","DOIUrl":"https://doi.org/10.1109/tse.2025.3541922","url":null,"abstract":"","PeriodicalId":13324,"journal":{"name":"IEEE Transactions on Software Engineering","volume":"3 1","pages":""},"PeriodicalIF":7.4,"publicationDate":"2025-02-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143417831","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}