Large Scale Variability

Software variability studies the variation points and commonality that exists within a family of software products or a configurable software system. In the MUSCAT group, we study large scale management of variability-aware software, composition of feature models, relationships to software architectures, reverse engineering of variability models from source code and build systems. We particurlarly apply our approaches and techniques on cyber-physical systems machine learning pipelines, and more generally very-large software systems.

Ongoing and recent projects:

Smart Identification and Visualization of Variability in Very Large Software Architectures (2023-2026)
Usage-driven software tailoring (2021-2024)
Understanding large object-oriented variability-rich systems by automatic detection in the source code and the build systems (2019-2022)
Variability-intensive applications over highly-configurable platforms: early feasibility and optimality analysis (2016-2020)
SmartIoT (2018-2019)