Recovering Trace Links Between Software Documentation And Code
Jan Keim, Sophie Corallo, Dominik Fuchß, Tobias Hey, Tobias Telge, Anne Koziolek
摘要
Introduction Software development involves creating various artifacts at different levels of abstraction and establishing relationships between them is essential. Traceability link recovery (TLR) automates this process, enhancing software quality by aiding tasks like maintenance and evolution. However, automating TLR is challenging due to semantic gaps resulting from different levels of abstraction. While automated TLR approaches exist for requirements and code, architecture documentation lacks tailored solutions, hindering the preservation of architecture knowledge and design decisions. Methods This paper presents our approach TransArC for TLR between architecture documentation and code, using componentbased architecture models as intermediate artifacts to bridge the semantic gap. We create transitive trace links by combining the existing approach ArDoCo for linking architecture documentation to models with our novel approach ArCoTL for linking architecture models to code. Results We evaluate our approaches with five open-source projects, comparing our results to baseline approaches. The model-to-code TLR approach achieves an average F 1 -score of 0.98, while the documentation-to-code TLR approach achieves a promising average F 1 -score of 0.82, significantly outperforming baselines. Conclusion Combining two specialized approaches with an intermediate artifact shows promise for bridging the semantic gap. In future research, we will explore further possibilities for such transitive approaches.
问问这篇 Paper
智能体会读完全文。
Lune 把这篇 Paper 索引到了每一个公式,引用它的顶会 Paper 也一样。你提问,回答直接引用原文。
引用它的顶会 Paper3
- LiSSA: Toward Generic Traceability Link Recovery Through Retrieval- Augmented GenerationDominik Fuchß, Tobias Hey, Jan Keim, Haoyu Liu 等ICSE 2025 · 被引用 8 次
- Spec2Code: Mapping Protocol Specification to Function-Level Code ImplementationYuekun Wang, Lili Quan, Xiaofei Xie, Junjie Wang 等ASE 2025
- LinkAnchor: An Autonomous LLM-Based Agent for Issue-to-Commit Link RecoveryArshia Akhavan, Alireza Hoseinpour, Abbas Heydarnoori, Hamid Bagheri 等FSE 2026
它引用的顶会 Paper5
- Traceability Transformed: Generating more Accurate Links with Pre-Trained BERT ModelsJinfeng Lin, Yalin Liu, Qingkai Zeng, Meng Jiang 等ICSE 2021 · 被引用 124 次
- Improving the effectiveness of traceability link recovery using hierarchical bayesian networksKevin Moran, David N. Palacio, Carlos Bernal-Cárdenas, Daniel McCrystal 等ICSE 2020 · 被引用 40 次
- Software Architecture in Practice: Challenges and OpportunitiesZhiyuan Wan, Yun Zhang, Xin Xia, Yi Jiang 等FSE 2023 · 被引用 29 次
- Using Consensual Biterms from Text Structures of Requirements and Code to Improve IR-Based Traceability RecoveryHui Gao, Hongyu Kuang, Kexin Sun, Xiaoxing Ma 等ASE 2022 · 被引用 20 次
- Supporting Quality Assurance with Automated Process-Centric Quality Constraints CheckingChristoph Mayr-Dorn, Michael Vierhauser, Stefan Bichler, Felix Keplinger 等ICSE 2021 · 被引用 17 次
相关 Paper
- Establishing multilevel test-to-code traceability linksRobert White, Jens Krinke, Raymond TanICSE 2020 · 被引用 37 次
- TRIAD: Automated Traceability Recovery based on Biterm-enhanced Deduction of Transitive Links among ArtifactsHui Gao, Hongyu Kuang, Wesley K. G. Assunção, Christoph Mayr-Dorn 等ICSE 2024 · 被引用 8 次
- Co-evolving code with evolving metamodelsDjamel Eddine Khelladi, Benoît Combemale, Mathieu Acher, Olivier Barais 等ICSE 2020 · 被引用 11 次
- SSAR: A Novel Software Architecture Recovery Approach Enhancing Accuracy and ScalabilityWei Ding, Ran Mo, Chaochao Wu, Haopeng SongICSE 2026
- INTERTRANS: Leveraging Transitive Intermediate Translations to Enhance LLM-Based Code TranslationMarcos Macedo, Yuan Tian, Pengyu Nie, Filipe Roseiro Côgo 等ICSE 2025 · 被引用 7 次
