Towards Efficient Analysis of Variation in Time and Space

Abstract

Variation is central to today's software development. There are two fundamental dimensions to variation: Variation in time refers to the fact that software exists in numerous revisions that typically replace each other (i.e., a newer version supersedes an older one). Variation in space refers to differences among variants that are designed to coexist in parallel. There are numerous analyses to cope with variation in space (i.e., product-line analyses) and others that cope with variation in time (i.e., regression analyses). The goal of this work is to discuss to which extent product-line analyses can be applied to revisions and, conversely, where regression analyses can be applied to variants. In addition, we discuss challenges related to the combination of product-line and regression analyses. The overall goal is to increase the efficiency of analyses by exploiting the inherent commonality between variants and revisions.