Seamless Variability Management With the Virtual Platform

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 variant-rich systems, exploiting a spectrum between both opposing strategies. We design, formalize, and prototype the variability-management framework virtual platform. It bridges clone & own and platform-oriented development. Relying on programming-language-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.Comment: 13 pages, 10 figures; accepted for publication at the 43rd International Conference on Software Engineering (ICSE 2021), main technical trac

Activities and costs of re-engineering cloned variants into an integrated platform

Many software systems need to exist in multiple variants. Organizations typically develop variants using clone & own-copying and adapting systems towards new requirements. However, while clone & own is a simple and readily available strategy, it does not scale with the number of variants, and then requires a costly re-engineering of the cloned variants into a configurable software platform (a.k.a., software product line). Ideally, organizations could rely on decision models or at least on substantial empirical data to assess the costs and benefits of such a re-engineering. Unfortunately, despite decades of research on product lines and platforms, such data is scarce, not least because obtaining it from industrial re-engineering efforts is challenging. We address this gap with a study on re-engineering two cases of cloned variants of open-source Android and Java games. Student developers re-engineered the clones into software product lines, logging their activities and costs. They performed the types of activities typically associated with re-engineering, but the activities were intertwined and done iteratively. The costs were relatively similar among both cases, but the used variability mechanism had a substantial impact. Interestingly, beyond a common diffing tool, no dedicated re-engineering tool was particularly useful. We hope that our results support researchers working on re-engineering techniques and decision models, as well as practitioners trying to assess the costs and activities involved in re-engineering a software platform