Recovering Trace Links Between Software Documentation And Code
Jan Keim, Sophie Corallo, Dominik Fuchß, Tobias Hey, Tobias Telge, Anne Koziolek
Abstract
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.
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Cited by top-tier papers3
- LiSSA: Toward Generic Traceability Link Recovery Through Retrieval- Augmented GenerationDominik Fuchß, Tobias Hey, Jan Keim, Haoyu Liu et al.ICSE 2025 · 8 citations
- Spec2Code: Mapping Protocol Specification to Function-Level Code ImplementationYuekun Wang, Lili Quan, Xiaofei Xie, Junjie Wang et al.ASE 2025
- LinkAnchor: An Autonomous LLM-Based Agent for Issue-to-Commit Link RecoveryArshia Akhavan, Alireza Hoseinpour, Abbas Heydarnoori, Hamid Bagheri et al.FSE 2026
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- Traceability Transformed: Generating more Accurate Links with Pre-Trained BERT ModelsJinfeng Lin, Yalin Liu, Qingkai Zeng, Meng Jiang et al.ICSE 2021 · 124 citations
- Improving the effectiveness of traceability link recovery using hierarchical bayesian networksKevin Moran, David N. Palacio, Carlos Bernal-Cárdenas, Daniel McCrystal et al.ICSE 2020 · 40 citations
- Software Architecture in Practice: Challenges and OpportunitiesZhiyuan Wan, Yun Zhang, Xin Xia, Yi Jiang et al.FSE 2023 · 29 citations
- Using Consensual Biterms from Text Structures of Requirements and Code to Improve IR-Based Traceability RecoveryHui Gao, Hongyu Kuang, Kexin Sun, Xiaoxing Ma et al.ASE 2022 · 20 citations
- Supporting Quality Assurance with Automated Process-Centric Quality Constraints CheckingChristoph Mayr-Dorn, Michael Vierhauser, Stefan Bichler, Felix Keplinger et al.ICSE 2021 · 17 citations
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