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Towards an intelligent domain-specific traceability solution

Jin Guo, Natawut Monaikul, Cody Plepel, Jane Cleland-Huang

Abstract

State-of-the-art software trace retrieval techniques are unable to perform the complex reasoning that a human analyst follows in order to create accurate trace links between artifacts such as regulatory codes and requirements. As a result, current algorithms often generate imprecise links. To address this problem, we present the Domain-Contextualized Intelligent Traceability Solution (DoCIT), designed to mimic some of the higher level reasoning that a human trace analyst performs. We focus our efforts on the complex domain of communication and control in a transportation system. DoCIT includes rules for extracting ``action units'' from software artifacts, a domain-specific knowledge base for relating semantically similar concepts across action units, and a set of link-creation heuristics which utilize the action units to establish meaningful trace links across pairs of artifacts. Our approach significantly improves the quality of the generated trace links. We illustrate and evaluate DoCIT with examples and experiments from the control and communication sector of a transportation domain.

BibTeX
@inproceedings{Guo-al:ASE14,
  author    = {Jin Guo and
               Natawut Monaikul and
               Cody Plepel and
               Jane Cleland{-}Huang},
  title     = {Towards an intelligent domain-specific traceability solution},
  booktitle = {ASE},
  pages     = {755--766},
  publisher = {{ACM}},
  year      = {2014},
}

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