Using similarity metrics for mining variability from software repositories

Abstract

Much activity within software product line engineering has beenconcerned with explicitly representing and exploitingcommonality and variability at the feature level for the purpose ofa particular engineering task e.g. requirements specification,design, coding, verification, product derivation process, but notfor comparing how similar products in the product line are witheach other. In contrast, a case-based approach to softwaredevelopment is concerned with descriptions and models as a set ofsoftware cases stored in a repository for the purpose of searchingat a product level, typically as a foundation for new productdevelopment. New products are derived by finding the mostsimilar product descriptions in the repository using similaritymetrics.The new idea is to use such similarity metrics for miningvariability from software repositories. In this sense, softwareproduct line engineering could be informed by the case-basedapproach. This approach requires defining and implementingsuch similarity metrics based on the representations used for thesoftware cases in such a repository. It provides complementarybenefits to the ones given through feature-based representations ofvariability and may help mining such variability