Harmonized Temporal Feature Modeling to Uniformly Perform, Track, Analyze, and Replay Software Product Line Evolution

Daniel Hinterreiter, Michael Nieke, Lukas Linsbauer, Christoph Seidl, Herbert Prähofer, Paul Grünbacher

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

Abstract

A feature model (FM) describes commonalities and variability within a software product line (SPL) and represents the configuration options at one point in time. A temporal feature model (TFM) additionally represents FM evolution, e.g., the change history or the planning of future releases. The increasing number of different TFM notations hampers research collaborations due to a lack of interoperability regarding notations, editors, and analyses. We present a common API for TFMs, which provides the core of a TFM ecosystem, to harmonize notations. We identified the requirements for the API based on systematically classifying and comparing the capabilities of existing TFM approaches. Our approach allows to work seamlessly with different TFM notations to perform, track, analyze and replay evolution. Our evaluation investigates two research questions on the expressiveness (RQ1) and utility (RQ2) of our approach by presenting implementations for several existing FM and TFM notations and replaying evolution histories from two case study systems.
Original languageEnglish
Title of host publicationProceedings of the 18th International Conference on Generative Programming: Concepts & Experiences (GPCE)
PublisherACM
Pages115-128
Number of pages14
DOIs
Publication statusPublished - Oct 2019

Fields of science

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

JKU Focus areas

  • Digital Transformation

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