Automated Software Engineering

, Volume 25, Issue 4, pp 703–741 | Cite as

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

  • Xiaofan ChenEmail author
  • John Hosking
  • John Grundy
  • Robert Amor


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.


Software traceability Traceability recovery Traceability visualization 



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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© Springer Science+Business Media, LLC, part of Springer Nature 2018

Authors and Affiliations

  1. 1.School of Computer Science and EngineeringNanjing University of Science and TechnologyNanjingChina
  2. 2.University of AucklandAucklandNew Zealand
  3. 3.Faculty of Information TechnologyMonash UniversityMelbourneAustralia
  4. 4.Department of Computer ScienceUniversity of AucklandAucklandNew Zealand

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