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Recovering Traceability Links between Release Notes and Related Software Artifacts

Published: 23 May 2024 Publication History

Abstract

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 [5]. When changes are made without proper traceability links, inconsistencies and conflicts may arise between different artifacts [4], such as requirements, design documents, and code, resulting in software development that fails to meet user expectations or exhibits unexpected behavior. 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 [3]. 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 [1]. 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 [6]. 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 [7]. 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 [2].
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. Next, we investigate the feasibility of automated traceability approaches for software release notes in GitHub using rule-based and information retrieval (IR)-based classifier. To the best of our knowledge, our techniques are the first to automatically recover traceability links between software releases and related artifacts (i.e., commits, pull requests, and issues). This approach can help keep track of changes and improve the quality of release notes by collecting all useful information automatically in real-time. By using this approach, we aim to identify areas of improvement and refine our proposed technique to make it more usable and effective in practice.

References

[1]
Surafel Lemma Abebe, Nasir Ali, and Ahmed E. Hassan. An empirical study of software release notes. Empirical Softw. Engg., 21(3):1107--1142, June 2016.
[2]
Tingting Bi, Xin Xia, David Lo, John Grundy, and Thomas Zimmermann. An empirical study of release note production and usage in practice. IEEE Transactions on Software Engineering, 48(6):1834--1852, 2022.
[3]
Barthélémy Dagenais and Martin P. Robillard. Recovering traceability links between an api and its learning resources. In 2012 34th International Conference on Software Engineering (ICSE), pages 47--57, 2012.
[4]
Jan Keim, Sophie Corallo, Dominik Fuchß, and Anne Koziolek. Detecting inconsistencies in software architecture documentation using traceability link recovery. In 2023 IEEE 20th International Conference on Software Architecture (ICSA), pages 141--152, 2023.
[5]
Kevin Moran, David N. Palacio, Carlos Bernal-Cárdenas, Daniel McCrystal, Denys Poshyvanyk, Chris Shenefiel, and Jeff Johnson. Improving the effectiveness of traceability link recovery using hierarchical bayesian networks. In Proceedings of the ACM/IEEE 42nd International Conference on Software Engineering, ICSE '20, page 873--885, New York, NY, USA, 2020. Association for Computing Machinery.
[6]
Sristy Sumana Nath and Banani Roy. Exploring relevant artifacts of release notes: The practitioners' perspective. In 2022 IEEE International Conference on Software Analysis, Evolution and Reengineering (SANER), pages 1270--1277, 2022.
[7]
Jianfei Zhu, Guanping Xiao, Zheng Zheng, and Yulei Sui. Enhancing traceability link recovery with unlabeled data. In 2022 IEEE 33rd International Symposium on Software Reliability Engineering (ISSRE), pages 446--457, 2022.

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cover image ACM Conferences
ICSE-Companion '24: Proceedings of the 2024 IEEE/ACM 46th International Conference on Software Engineering: Companion Proceedings
April 2024
531 pages
ISBN:9798400705021
DOI:10.1145/3639478
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

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  • Faculty of Engineering of University of Porto

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Association for Computing Machinery

New York, NY, United States

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Published: 23 May 2024

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