Facing the Truth: Benchmarking the Techniques for the Evolution of Variant-Rich Systems

Daniel Strüber, Mukelabai Mukelabai, Jacob Krüger, Stefan Fischer, Lukas Linsbauer, Jabier Martinez, Thorsten Berger

Research output: Chapter in Book/Report/Conference proceedingConference proceedingspeer-review

Abstract

The evolution of variant-rich systems is a challenging task. To support developers, the research community has proposed a range of different techniques over the last decades. However, many techniques have not been adopted in practice so far. To advance such techniques and to support their adoption, it is crucial to evaluate them against realistic baselines, ideally in the form of generally accessible benchmarks. To this end, we need to improve our empirical understanding of typical evolution scenarios for variant-rich systems and their relevance for benchmarking. In this paper, we establish eleven evolution scenarios in which benchmarks would be beneficial. Our scenarios cover typical lifecycles of variant-rich system, ranging from clone & own to adopting and evolving a configurable product-line platform. For each scenario, we formulate benchmarking requirements and assess its clarity and relevance via a survey with experts in variant-rich systems and software evolution. We also surveyed the existing benchmarking landscape, identifying synergies and gaps. We observed that most scenarios, despite being perceived as important by experts, are only partially or not at all supported by existing benchmarks-a call to arms for building community benchmarks upon our requirements. We hope that our work raises awareness for benchmarking as a means to advance techniques for evolving variant-rich systems, and that it will lead to a benchmarking initiative in our community.
Original languageEnglish
Title of host publication23rd International Systems and Software Product Line Conference
Place of PublicationParis, France
PublisherACM
Pages177-188
Number of pages12
DOIs
Publication statusPublished - Sept 2019

Fields of science

  • 102 Computer Sciences
  • 102022 Software development
  • 102025 Distributed systems

JKU Focus areas

  • Digital Transformation

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