Variability management and software product line knowledge in software companies

  • Antonio Gutierrez
  • , Ana Eva Chacón-Luna
  • , David Benavides
  • , Lidia Fuentes
  • , Rick Rabiser

Research output: Contribution to journalArticlepeer-review

Abstract

Software product line engineering aims to systematically generate similar products or services within a given domain to reduce cost and time to market while increasing reuse. Various studies recognize the success of product line engineering in different domains. Software variability have increased over the years in many different domains such as mobile applications, cyber–physical systems or car control systems to just mention a few. However, software product line engineering is not as widely adopted as other software development technologies. In this paper, we present an empirical study conducted through a survey distributed to many software development companies. Our goal is to understand their need of software variability management and the level of knowledge the companies have regarding software product line engineering. The survey was answered by 127 participants from more than a hundred of different software development companies. Our study reveals that most of companies manage a catalog of similar products in a way or another (e.g. clone-and-own, common modules that are statically imported,etc.), they mostly document the features of products using text or spreed sheet based documents and more than 66% of companies identify a base product from which they derive other similar products. We also found a correlation between the lack of Software Product Line (SPL) knowledge and the absence of reuse practices. Notably, this is the first study that explore software variability needs regardless of a company’s prior knowledge of SPL. The results encourages further research to understand the reason for the limited knowledge and application of software product line engineering practices, despite the growing demand of variability management.
Original languageEnglish
Article number112114
Number of pages14
JournalJournal of Systems and Software
Volume216
Publication statusPublished - Oct 2024

Fields of science

  • 202017 Embedded systems
  • 102 Computer Sciences
  • 102022 Software development
  • 102025 Distributed systems
  • 102029 Practical computer science
  • 202003 Automation
  • 202041 Computer engineering

JKU Focus areas

  • Digital Transformation

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