Title: Supporting feature model evolution by suggesting constraints from code-level dependency analyses
Abstract: Feature models are a de facto standard for representing the commonalities and variability of product lines and configurable software systems. Requirements-level features are commonly implemented in multiple source code artifacts, which results in complex dependencies at the code level. As developers change and evolve features frequently, it is challenging to keep feature models consistent with their implementation. We thus present an approach combining feature-to-code mappings and code dependency analyses to inform engineers about possible inconsistencies. Our focus is on code-level changes requiring updates in feature dependencies and constraints. Our approach uses static code analysis and a variation control system to lift complex code-level dependencies to feature models. We present the suggested dependencies to the engineer in two ways: directly as links between features in a feature model and as a heatmap visualizing the dependency changes of all features in a model. We present results of an evaluation on the Pick-and-Place Unit system, which demonstrates the utility and performance of our approach and the quality of the suggestions.
Publication Year: 2019
Publication Date: 2019-10-10
Language: en
Type: article
Indexed In: ['crossref']
Access and Citation
Cited By Count: 4
AI Researcher Chatbot
Get quick answers to your questions about the article from our AI researcher chatbot