Software Product Line Engineering: Adoption, Tooling and AI Era Challenges

TL;DR

This survey reviews Software Product Line Engineering, covering foundations, adoption, tooling, AI challenges, and future research directions in the field.

Contribution

It provides a comprehensive synthesis of SPLE literature, comparing models, summarizing evolution, and outlining open challenges and future research directions.

Findings

Comparison of major adoption and evaluation models.

Summary of historical evolution from domain engineering to AI-assisted variability management.

Identification of open challenges in tooling, interoperability, and AI integration.

Abstract

Software Product Line Engineering enables systematic reuse across families of related software intensive systems. This survey synthesises key SPLE foundations, lifecycle concepts, adoption models, tooling and AI era challenges. Based on a structured review of the SPLE literature, we compare major adoption and evaluation models, including BAPO, FEF, PuLSE, SIMPLE, COPLIMO, PROMOTE-PL, and APPLIES. We further summarise the historical evolution of SPLE research from domain engineering foundations to AI assisted variability management. The survey also examines tool interoperability, UVL-based standardisation, SME adoption, migration from clone-and-own development, variability aware DevOps, empirical evidence gaps and assurance challenges for AI assisted SPLE. The paper provides a compact research agenda for software engineering and ICT researchers by consolidating open challenges and future research directions in contemporary SPLE.