Varflix: A Flexible Approach for Variability Mining

Variability mining is a process to perform extractive adoption of Software Product Lines (SPLs).This process becomes necessary when manual variability management in existing products is no longer possible due to the size and complexity of the system and/or too many variants resulting from clone-and-own reuse.A key factor for satisfying variability mining results is the extensive involvement of experts of the domain or system under analysis.In existing approaches, this aspect is addressed to a limited extent and tools are highly automatic.Integrating checks for validation of the mining results is another aspect with little to no support in this context.In this paper, we present our work to design a framework for artifact-independent variability mining addressing these shortcomings called Varflix.The idea is to perform mining in multiple automatic steps but include user input after each step to adapt the result to user needs.This should not only improve the quality of the mining result, but also other aspects such as scalability or complexity.Varflix produces a variability model based on the input variants.

Authors

Institutions

Publication Details

Published
2025-09-01
DOI
https://doi.org/10.1145/3748269.3748594
Primary Topic
Software Engineering Research
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Varflix: A Flexible Approach for Variability Mining

Alexander Stummer
Software Engineering Research
article

Varflix: A Flexible Approach for Variability Mining

Alexander Stummer
article en

Abstract

Variability mining is a process to perform extractive adoption of Software Product Lines (SPLs).This process becomes necessary when manual variability management in existing products is no longer possible due to the size and complexity of the system and/or too many variants resulting from clone-and-own reuse.A key factor for satisfying variability mining results is the extensive involvement of experts of the domain or system under analysis.In existing approaches, this aspect is addressed to a limited extent and tools are highly automatic.Integrating checks for validation of the mining results is another aspect with little to no support in this context.In this paper, we present our work to design a framework for artifact-independent variability mining addressing these shortcomings called Varflix.The idea is to perform mining in multiple automatic steps but include user input after each step to adapt the result to user needs.This should not only improve the quality of the mining result, but also other aspects such as scalability or complexity.Varflix produces a variability model based on the input variants.

Johannes Kepler University of Linz (AT)
Österreichische Nationalstiftung für Forschung, Technologie und Entwicklung, Bundesministerium für Digitalisierung und Wirtschaftsstandort
Openalex Percentile: Top 66%
Software Engineering Research
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Varflix: A Flexible Approach for Variability Mining — Alexander Stummer · (2025) | TGRS Research Map | TGRS