Recovering Traceability Links between Release Notes and Related Software Artifacts
Inadequate traceability links between software artifacts can create challenges for developers in tracking the origin of bugs or issues and their corresponding code changes, leading to longer resolution times and the potential introduction of new bugs \cite{icse2020tlrreqtocode}. When changes are made without proper traceability links, inconsistencies and conflicts may arise between different artifacts \cite{icsatraceinconsistency}, such as requirements, design documents, and code, resulting in software development that fails to meet user expectations or exhibits unexpected behavior \cite{LR_TLR_softchange, icsecom2019codereq}. The lack of proper traceability links also poses challenges in maintaining software over time, making it difficult to upgrade, manage dependencies, and make changes to the software \cite{icseapiTRL}. Additionally, the lack of traceability links can make it challenging to understand the software’s evolution and developers’ decision-making process, reducing transparency and hindering collaboration.
Release notes are a document that includes details about new features, bug fixes, improvements, and known issues. They help users and developers understand the changes made to the software and their impact on workflows \cite{releasenote}. Traceability links of issues, pull requests (PRs), and commits are important in release notes as they provide context and understanding of changes made in a release \cite{RelContentHuman22}. Previous studies have identified PRs, commits, and issues as related artifacts that can be linked with release notes to generate them automatically \cite{RelContentHuman22}In our dataset, 33% of release notes are not linked with the corresponding artifacts, highlighting the need for automated traceability link recovery in release notes.
Additionally, limited traceability links can lead to duplicate bug reports, confusion, and wasted time and effort \cite{enhancingTLR}. Traceability links are crucial for version controlling and back-porting to give a clear understanding of the dependencies within different versions. Without these links, managing releases and documenting changes accurately becomes challenging, potentially damaging the reputation of the software and causing confusion among stakeholders and customers \cite{rnempirical}.
Our study begins by creating a benchmark to propose an automated traceability technique between release and related artifacts. To collect data, we use the GitHub API to gather information from 10 popular repositories, including release notes, pull-request titles, and commit messages. We analyze textual data and create a benchmark for recovering traceability links between releases and related artifacts such as commits, pull requests, and issues.
Fri 19 AprDisplayed time zone: Lisbon change
10:30 - 11:00 | |||
10:30 30mPoster | Exploring the Effectiveness of LLM based Test-driven Interactive Code Generation: User Study and Empirical Evaluation Posters Sarah Fakhoury Microsoft Research, Aaditya Naik University of Pennsylvania, Georgios Sakkas University of California at San Diego, Saikat Chakraborty Microsoft Research, Madan Musuvathi Microsoft Research, Shuvendu K. Lahiri Microsoft Research | ||
10:30 30mPoster | On the Need for Empirically Investigating Fast-Growing Programming Languages Posters Jahnavi Kumar Indian Institute of Technology Tirupati, India, Sridhar Chimalakonda Indian Institute of Technology, Tirupati | ||
10:30 30mPoster | Decoding Log Parsing Challenges: A Comprehensive Taxonomy for Actionable Solutions Posters Issam Sedki Concordia University, Wahab Hamou-Lhadj Concordia University, Montreal, Canada, Otmane Ait-Mohamed Concordia University, Naser Ezzati Jivan , Mohammed Shehab Concordia University | ||
10:30 30mPoster | Automated Code Editing with Search-Generate-Modify Posters Changshu Liu Columbia University, Pelin Cetin Columbia University, Yogesh Patodia Columbia University, Baishakhi Ray AWS AI Labs, Saikat Chakraborty Microsoft Research, Yangruibo Ding Columbia University | ||
10:30 30mPoster | Exploring the Impact of Inheritance on Test Code Maintainability Posters | ||
10:30 30mPoster | Improving Program Debloating with 1-DU Chain Minimality Posters Myeongsoo Kim Georgia Institute of Technology, Santosh Pande Georgia Institute of Technology, Alessandro Orso Georgia Institute of Technology Pre-print | ||
10:30 30mPoster | GoSpeechLess: Interoperable Serverless ML-based Cloud Services Posters Sashko Ristov University of Innsbruck, Philipp Gritsch University of Innsbruck, David Meyer University of Innsbruck, Michael Felderer German Aerospace Center (DLR) & University of Cologne | ||
10:30 30mPoster | Towards Precise Observations of Neural Model Robustness in Classification Posters Wenchuan Mu ISTD, Singapore University of Technology and Design, Kwan Hui Lim Singapore University of Technology and Design, Singapore | ||
10:30 30mPoster | Assessing AI-Based Code Assistants in Method Generation Tasks Posters Vincenzo Corso University of Milano - Bicocca, Leonardo Mariani University of Milano-Bicocca, Daniela Micucci University of Milano-Bicocca, Italy, Oliviero Riganelli University of Milano - Bicocca | ||
10:30 30mPoster | Recovering Traceability Links between Release Notes and Related Software Artifacts Posters | ||
10:30 30mPoster | Improving the Condensing of Reverse Engineered Class Diagrams using Weighted Network Metrics Posters Weifeng Pan Zhejiang Gongshang University, Wei Wu Zhejiang Gongshang University, Hua Ming Oakland University, Dae-Kyoo Kim Oakland University, Jinkai Yang Oakland University, Ruochen Liu Oakland University Media Attached | ||
10:30 30mPoster | Exploring Data Cleanness in Defects4J and Its Influence on Fault Localization Efficiency Posters Md Nakhla Rafi Concordia University, An Ran Chen University of Alberta, Tse-Hsun (Peter) Chen Concordia University, Shaohua Wang Central University of Finance and Economics | ||
10:30 30mPoster | Learning to Represent Patches Posters Xunzhu Tang University of Luxembourg, Haoye Tian University of Melbourne, Zhenghan Chen Peking University, Weiguo Pian University of Luxembourg, Saad Ezzini Lancaster University, Abdoul Kader Kaboré University of Luxembourg, Andrew Habib ABB Corporate Research, Germany, Jacques Klein University of Luxembourg, Tegawendé F. Bissyandé University of Luxembourg | ||
10:30 30mPoster | Bringing Structure to Naturalness: On the Naturalness of ASTs Posters Profir-Petru Pârțachi National Institute of Informatics, Japan, Mahito Sugiyama National Institute of Informatics, Japan |