Seamless Variability Management with the Virtual Platform

Abstract

Customization is a general trend in software engineering, demanding systems that support variable stakeholder requirements. Two opposing strategies are commonly used to create variants: software clone&own and software configuration with an integrated platform. Organizations often start with the former, which is cheap, agile, and supports quick innovation, but does not scale. The latter scales by establishing an integrated platform that shares software assets between variants, but requires high up-front investments or risky migration processes. So, could we have a method that allows an easy transition or even combine the benefits of both strategies? We propose a method and tool that supports a truly incremental development of variantrich systems, exploiting a spectrum between both opposing strategies. We design, formalize, and prototype the variabilitymanagement framework virtual platform. It bridges clone&own and platform-oriented development. Relying on programminglanguage-independent conceptual structures representing software assets, it offers operators for engineering and evolving a system, comprising: traditional, asset-oriented operators and novel, feature-oriented operators for incrementally adopting concepts of an integrated platform. The operators record meta-data that is exploited by other operators to support the transition. Among others, they eliminate expensive feature-location effort or the need to trace clones. Our evaluation simulates the evolution of a real-world, clone-based system, measuring its costs and benefits.

Visualizations for the evolution of Variant-Rich Systems: A systematic mapping study

“…While the number of variants is small, clone & own might be an effective architecture. However, as the variants increase, clone & own ends in replication and propagation challenges [2]. Engineers can opt to move to Conditional Compilation.…”

“…Setting. Compared to the evolution of one-off applications, VRS evolution introduces additional challenges since the evolution should be synchronized across a potentially high number of variants [2]. The inter-dependency between these variants varies from highly-independent (e.g., the clone & own approach where 'clones' might evolve totally independently from its ancestor) to totally-dependent variants (e.g., configurable software-product lines where new variant requirements should be first considered at the core platform before impacting the variants).…”

Software variability in service robotics

“…This strategy is simple and cheap, but does not scale with the number of variants (Dubinsky et al 2013;Berger et al 2020;Krueger and Berger 2020;Businge et al 2022). Clone management frameworks (Rubin et al 2013;Mahmood et al 2021) reduce this burden to some extent, but ultimately, organizations often need to re-engineer the cloned variants and integrate them into a configurable platform.…”

Simulating the Evolution of Clone-and-Own Projects with VEVOS

“…Clone-and-own research tries to address the challenges of cloneand-own and different approaches have been proposed over the years. The approaches range from the systematic support of cloneand-own development (with the aim of reducing maintenance costs) [8,11,19,24,31,34,48] to techniques that support the migration of a set of variants into an integrated platform (with the aim of eliminating duplicated code) [11,21,39]. To evaluate these approaches, suitable benchmarks are required.…”

“…Given these practical experiences, a more recent line of research focuses at better supporting clone-and-own [8,11,19,21,24,31,34,37,39,48]. Clone-and-own research focuses on developing methods and tools with the ultimate goal of either migrating a clone-andown project to a software product line, or systematically supporting clone-and-own development through better automation.…”