article

On the role of semantics in automated requirements tracing

Authors:

Nan NiuAuthors Info & Claims

Requirements Engineering, Volume 20, Issue 3

Pages 281 - 300

https://doi.org/10.1007/s00766-013-0199-y

Published: 01 September 2015 Publication History

Abstract

In this paper, we investigate the potential benefits of utilizing natural language semantics in automated traceability link retrieval. In particular, we evaluate the performance of a wide spectrum of semantically enabled information retrieval methods in capturing and presenting requirements traceability links in software systems. Our objectives are to gain more operational insights into these methods and to provide practical guidelines for the design and development of effective requirements tracing and management tools. To achieve our research objectives, we conduct an experimental analysis using three datasets from various application domains. Results show that considering more semantic relations in traceability link retrieval does not necessarily lead to higher quality results. Instead, a more focused semantic support, that targets specific semantic relations, is expected to have a greater impact on the overall performance of tracing tools. In addition, our analysis shows that explicit semantic methods, that exploit local or domain-specific sources of knowledge, often achieve a more satisfactory performance than latent methods, or methods that derive semantics from external or general-purpose knowledge sources.

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Keim JCorallo SFuchß DHey TTelge TKoziolek ARoychoudhury APaiva AAbreu RStorey M(2024)Recovering Trace Links Between Software Documentation And CodeProceedings of the IEEE/ACM 46th International Conference on Software Engineering10.1145/3597503.3639130(1-13)Online publication date: 20-May-2024
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cover image Requirements Engineering

Requirements Engineering Volume 20, Issue 3

September 2015

130 pages

ISSN:0947-3602

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Copyright © Copyright © 2015 Springer-Verlag London.

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Keim JCorallo SFuchß DHey TTelge TKoziolek ARoychoudhury APaiva AAbreu RStorey M(2024)Recovering Trace Links Between Software Documentation And CodeProceedings of the IEEE/ACM 46th International Conference on Software Engineering10.1145/3597503.3639130(1-13)Online publication date: 20-May-2024
https://dl.acm.org/doi/10.1145/3597503.3639130
Pauzi ZCapiluppi A(2023)Applications of natural language processing in software traceabilityJournal of Systems and Software10.1016/j.jss.2023.111616198:COnline publication date: 1-Apr-2023
https://dl.acm.org/doi/10.1016/j.jss.2023.111616
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https://dl.acm.org/doi/10.1145/3551349.3556948
Liu YLin JAnuyah OMetoyer RCleland-Huang JDwyer MDamian DZeller A(2022)Generating and visualizing trace link explanationsProceedings of the 44th International Conference on Software Engineering10.1145/3510003.3510129(1033-1044)Online publication date: 21-May-2022
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