Survey of Traceability Approaches in Model-Driven Engineering

TLDR

Models are used across engineering to manage complexity and represent information at different abstraction levels, and MDE provides principles that make software engineering simpler by using models as primary artifacts. The paper surveys traceability approaches in MDE and evaluates them against representation, mapping, scalability, change impact analysis, and tool support. The authors conduct a survey of traceability approaches in MDE, assessing them across representation, mapping, scalability, change impact analysis, and tool support. The survey identifies open issues in MDE traceability that warrant further investigation.

Abstract

Models have been used in various engineering fields to help managing complexity and represent information in different abstraction levels, according to specific notations and stakeholder's viewpoints. Model-Driven Engineering (MDE) gives the basic principles for the use of models as primary artefacts throughout the software development phases and presents characteristics that simplify the engineering of software in various domains, such as Enterprise Computing Systems. Hence, for its successful application, MDE processes must consider traceability practices. They help the understanding, capturing, tracking and verification of software artefacts and their relationships and dependencies with other artefacts during the software life-cycle. In this survey, we discuss the state-of-the-art in traceability approaches in MDE and assess them with respect to five general comparison criteria: representation, mapping, scalability, change impact analysis and tool support. As a complementary result, we have identified some open issues that can be better explored by traceability in MDE.