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DCTracVis: a system retrieving and visualizing traceability links between source code and documentation

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Abstract

It is well recognized that traceability links between software artifacts provide crucial support in comprehension, efficient development, and effective management of a software system. However, automated traceability systems to date have been faced with two major open research challenges: how to extract traceability links with both high precision and high recall, and how to efficiently visualize links for complex systems because of scalability and visual clutter issues. To overcome the two challenges, we designed and developed a traceability system, DCTracVis. This system employs an approach that combines three supporting techniques, regular expressions, key phrases, and clustering, with information retrieval (IR) models to improve the performance of automated traceability recovery between documents and source code. This combination approach takes advantage of the strengths of the three techniques to ameliorate limitations of IR models. Our experimental results show that our approach improves the performance of IR models, increases the precision of retrieved links, and recovers more correct links than IR alone. After having retrieved high-quality traceability links, DCTracVis then utilizes a new approach that combines treemap and hierarchical tree techniques to reduce visual clutter and to allow the visualization of the global structure of traces and a detailed overview of each trace, while still being highly scalable and interactive. Usability evaluation results show that our approach can effectively and efficiently help software developers comprehend, browse, and maintain large numbers of links.

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Acknowledgement

The authors gratefully acknowledge Alberto Bacchelli for agreeing to share his exemplar test sets and oracles of ArgoUML, Freenet and JMeter.

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Authors and Affiliations

  1. School of Computer Science and Engineering, Nanjing University of Science and Technology, Nanjing, China

    Xiaofan Chen

  2. University of Auckland, Auckland, New Zealand

    John Hosking

  3. Faculty of Information Technology, Monash University, Melbourne, Australia

    John Grundy

  4. Department of Computer Science, University of Auckland, Auckland, New Zealand

    Robert Amor

Authors
  1. Xiaofan Chen
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  2. John Hosking
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  4. Robert Amor
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Corresponding author

Correspondence to Xiaofan Chen.

Additional information

This research is financially supported by the Foundation for Research, Science and Technology, MBIE Software Process and Product Improvement project, and University of Auckland.

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Chen, X., Hosking, J., Grundy, J. et al. DCTracVis: a system retrieving and visualizing traceability links between source code and documentation. Autom Softw Eng 25, 703–741 (2018). https://doi.org/10.1007/s10515-018-0243-8

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