Article
We’re Not Gonna Break It! Consistency-Preserving Operators for Efficient Product Line Configuration
Author/s | Horcas Aguilera, José Miguel
Strüber, Daniel Burdusel, Alesandru Martínez, Javier Zschaler, Steffen |
Department | Universidad de Sevilla. Departamento de Lenguajes y Sistemas Informáticos |
Publication Date | 2022 |
Deposit Date | 2022-07-04 |
Published in |
|
Abstract | When configuring a software product line, finding a good trade-off between multiple orthogonal quality concerns is a
challenging multi-objective optimisation problem. State-of-the-art solutions based on search-based ... When configuring a software product line, finding a good trade-off between multiple orthogonal quality concerns is a challenging multi-objective optimisation problem. State-of-the-art solutions based on search-based techniques create invalid configurations in intermediate steps, requiring additional repair actions that reduce the efficiency of the search. In this work, we introduce consistency-preserving configuration operators (CPCOs)—genetic operators that maintain valid configurations throughout the entire search. CPCOs bundle coherent sets of changes: the activation or deactivation of a particular feature together with other (de)activations that are needed to preserve validity. In our evaluation, our instantiation of the IBEA algorithm with CPCOs outperforms two state-of-the-art tools for optimal product line configuration in terms of both speed and solution quality. The improvements are especially pronounced in large product lines with thousands of features. |
Funding agencies | Ministerio de Ciencia, Innovación y Universidades (MICINN). España Junta de Andalucía European Union (UE). H2020 |
Project ID. | RTI2018- 099213-B-I00
P18-FR-1081 H2020-101017109 RTI2018-101204-B-C22 (OPHELIA) |
Citation | Horcas Aguilera, J.M., Strüber, D., Burdusel, A., Martínez, J. y Zschaler, S. (2022). We’re Not Gonna Break It! Consistency-Preserving Operators for Efficient Product Line Configuration. IEEE Transactions on Software Engineering, April 2022 |
Files | Size | Format | View | Description |
---|---|---|---|---|
2204.12918.pdf | 2.172Mb | [PDF] | View/ | |