Towards a knowledge base for software developers to choose suitable traceability techniques

Haruhiko Kaiya*, Atsuo Hazeyama, Shinpei Ogata, Takao Okubo, Nobukazu Yoshioka, Hironori Washizaki

*Corresponding author for this work

Research output: Contribution to journalConference articlepeer-review

2 Citations (Scopus)


Huge amount of techniques for creating, maintaining and/or recovering traceability among software development artifacts have been proposed. It is thus not easy for a potential user of such techniques to choose a technique suitable for his/her project because too many techniques exist and projects are different from each other. In this paper, we proposed a model for characterizing a traceability technique with respect to its users. The model can become a meta-model of the knowledge base for such users. The model is designed on the basis of the contents of existing technical papers so that we can easily describe model instances on the basis of technical papers. The model is represented in a feature model, and it has four mandatory features: source, destination, consequence and process. The user can at least understand a technique is unsuitable for him/her by referring such features. If a technique estimates the traceability relationships, the instance of its feature model may contain the quality metrics of its estimation such as precision and recall. It has also several optional features: assumptions, preprocess and tool. Although we sometimes cannot obtain such optional features from technical papers, they are so helpful for a user to decide a technique suitable for him/her. On the basis of the feature model, we described model instances of several techniques in technical papers. We also examined and discussed who the suitable user for each technique is.

Original languageEnglish
Pages (from-to)1075-1084
Number of pages10
JournalProcedia Computer Science
Publication statusPublished - 2019
Event23rd International Conference on Knowledge-Based and Intelligent Information & Engineering Systems, KES 2019 - Budapest, Hungary
Duration: 2019 Sept 42019 Sept 6


  • Feature Model
  • Knowledge Base
  • Software Traceability
  • Survey
  • User Perspective

ASJC Scopus subject areas

  • Computer Science(all)


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