Domain Knowledge Discovery Guided by Software Trace Links
Abstract
Software-intensive projects are specified and modeled using domain terminology. Knowledge of the domain terminology is necessary for performing many Software Engineering tasks such as impact analysis, compliance verification, and safety certification. However, discovering domain terminology and reasoning about their interrelationships for highly technical software and system engineering domains is a complex task which requires significant domain expertise and human effort. In this paper, we present a novel approach for leveraging trace links in software intensive systems to guide the process of mining facts that contain domain knowledge. The trace links which drive our mining process, define relationships between artifacts such as regulations and requirements and enable a guided search through high-yield combinations of domain terms. Our proof-of-concept evaluation shows that our approach aids in the discovery of domain facts even in highly complex technical domains. These domain facts can provide support for a variety of Software Engineering activities. As a use case, we demonstrate how the mined facts can facilitate the task of project Q&A.
Cite
@article{arxiv.1808.05209,
title = {Domain Knowledge Discovery Guided by Software Trace Links},
author = {Jin L. C. Guo and Natawut Monaikul and Jane Cleland-Huang},
journal= {arXiv preprint arXiv:1808.05209},
year = {2018}
}
Comments
International Workshop on Artificial Intelligence for Requirements Engineering (AIRE'18)