Variability Management in Dynamic Software Product Lines for Self-Adaptive Systems—A Systematic Mapping

Author:

Aguayo OscarORCID,Sepúlveda SamuelORCID

Abstract

Context: Dynamic software product lines (DSPLs) have considerably increased their adoption for variability management for self-adaptive systems. The most widely used models for managing the variability of DSPLs are the MAPE-K control loop and context-aware feature models (CFMs). Aim: In this paper, we review and synthesize evidence of using variability constraint approaches, methodologies, and challenges for DSPL. Method: We conducted a systematic mapping, including three research questions. This study included 84 papers published from 2010 to 2021. Results: The main results show that open-dynamic variability shows a presence in 57.1% of the selected papers, and on the other hand, closed-dynamic variability appears in 38.1%. The most commonly used methodology for managing a DSPL environment is based on proprietary architectures (60.7%), where the use of CFMs predominates. For open-dynamic variability approaches, the MAPE-K control loop is mainly used. The main challenges in DSPL management are based on techniques (28.6%) and open variation (21.4%). Conclusions: Open-dynamic variability has prevailed over the years as the primary approach to managing variability in DSPL, where its primary methodology is the MAPE-K control loop. Response RQ3 requires further review.

Funder

Universidad de La Frontera

Publisher

MDPI AG

Subject

Fluid Flow and Transfer Processes,Computer Science Applications,Process Chemistry and Technology,General Engineering,Instrumentation,General Materials Science

Reference84 articles.

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1. Modeling variability in self-adapting robotic systems;Robotics and Autonomous Systems;2023-09

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