Advancements in Bug Traceability: A Systematic Mapping Study

Traceability refers to the potential for traces to be established (i.e., created and maintained) and used. Bug Traceability (BT) is critical for enhancing software quality, reducing maintenance costs, and boosting team efficiency. To explore the trends and advancements of BT, we conduct a systematic mapping study (SMS). We initially retrieve 4674 citations from 7 databases spanning 2014 to 2023, and 24 primary studies meet the rigorous selection criteria. Our study identifies 6 types of bug trace links, 8 traceability strategies, and 47 bug traceability recovery (BTR) techniques. Among them, 47 BTR techniques can be further classified into 6 categories. At the same time, we perform statistics on 113 datasets and 16 evaluation metrics used to assess the performance of BTR techniques proposed in the primary studies. In evaluating the overall quality of the primary studies, 8 dimensions are utilized to support technology transfer, categorizing the overall quality into 4 levels: poor, middle, good, and excellent, with 79% of primary studies evaluated at a good level. This study not only furnishes a clear definition of BT for scholarly reference, but also highlights that information retrieval (IR), machine learning (ML) and deep learning (DL) techniques are the mainstream techniques used for BTR.

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Published
2024-10-06
DOI
https://doi.org/10.1109/smc54092.2024.10831060
Citations
1
Primary Topic
Software Engineering Research
Type
article
Field-Weighted Citation Impact
0.78
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Advancements in Bug Traceability: A Systematic Mapping Study

Hongyan Wan, Bangchao Wang, Zhiyuan Zou, S. David Hu et al.
1 citations
Software Engineering Research
0.78
article

Advancements in Bug Traceability: A Systematic Mapping Study

Hongyan Wan, Bangchao Wang, Zhiyuan Zou, S. David Hu, Xiaoxiao Li, Jing Zhu, Luyao Ye
article en
1 citations

Abstract

Traceability refers to the potential for traces to be established (i.e., created and maintained) and used. Bug Traceability (BT) is critical for enhancing software quality, reducing maintenance costs, and boosting team efficiency. To explore the trends and advancements of BT, we conduct a systematic mapping study (SMS). We initially retrieve 4674 citations from 7 databases spanning 2014 to 2023, and 24 primary studies meet the rigorous selection criteria. Our study identifies 6 types of bug trace links, 8 traceability strategies, and 47 bug traceability recovery (BTR) techniques. Among them, 47 BTR techniques can be further classified into 6 categories. At the same time, we perform statistics on 113 datasets and 16 evaluation metrics used to assess the performance of BTR techniques proposed in the primary studies. In evaluating the overall quality of the primary studies, 8 dimensions are utilized to support technology transfer, categorizing the overall quality into 4 levels: poor, middle, good, and excellent, with 79% of primary studies evaluated at a good level. This study not only furnishes a clear definition of BT for scholarly reference, but also highlights that information retrieval (IR), machine learning (ML) and deep learning (DL) techniques are the mainstream techniques used for BTR.

Wuhan Textile University (CN)
Openalex Percentile: Top 17%
Software Engineering Research
0.78
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