The AETG System: An Approach to Testing Based on Combinatorial Design
IEEE Transactions on Software Engineering
Generative programming: methods, tools, and applications
Generative programming: methods, tools, and applications
Software product lines: practices and patterns
Software product lines: practices and patterns
Commonality and Variability in Software Engineering
IEEE Software
Feature-Oriented Project Line Engineering
IEEE Software
Software Product Line Engineering: Foundations, Principles and Techniques
Software Product Line Engineering: Foundations, Principles and Techniques
Supporting Product Derivation by Adapting and Augmenting Variability Models
SPLC '07 Proceedings of the 11th International Software Product Line Conference
An empirical study of the effect of time constraints on the cost-benefits of regression testing
Proceedings of the 16th ACM SIGSOFT International Symposium on Foundations of software engineering
SAT-based analysis of feature models is easy
Proceedings of the 13th International Software Product Line Conference
Automated analysis of feature models 20 years later: A literature review
Information Systems
A Theoretical and Empirical Study of Search-Based Testing: Local, Global, and Hybrid Search
IEEE Transactions on Software Engineering
Automated and Scalable T-wise Test Case Generation Strategies for Software Product Lines
ICST '10 Proceedings of the 2010 Third International Conference on Software Testing, Verification and Validation
Proceedings of the 33rd International Conference on Software Engineering
Regression testing minimization, selection and prioritization: a survey
Software Testing, Verification & Reliability
An algorithm for generating t-wise covering arrays from large feature models
Proceedings of the 16th International Software Product Line Conference - Volume 1
Evolutionary search-based test generation for software product line feature models
CAiSE'12 Proceedings of the 24th international conference on Advanced Information Systems Engineering
Strategies for testing products in software product lines
ACM SIGSOFT Software Engineering Notes
Pairwise testing for software product lines: comparison of two approaches
Software Quality Control
Generating better partial covering arrays by modeling weights on sub-product lines
MODELS'12 Proceedings of the 15th international conference on Model Driven Engineering Languages and Systems
Modelling and multi-objective optimization of quality attributes in variability-rich software
Proceedings of the Fourth International Workshop on Nonfunctional System Properties in Domain Specific Modeling Languages
Towards automated testing and fixing of re-engineered feature models
Proceedings of the 2013 International Conference on Software Engineering
ICSTW '13 Proceedings of the 2013 IEEE Sixth International Conference on Software Testing, Verification and Validation Workshops
Towards statistical prioritization for software product lines testing
Proceedings of the Eighth International Workshop on Variability Modelling of Software-Intensive Systems
Automated generation of computationally hard feature models using evolutionary algorithms
Expert Systems with Applications: An International Journal
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Software Products Lines (SPLs) are families of products sharing common assets representing code or functionalities of a software product. These assets are represented as features, usually organized into Feature Models (FMs) from which the user can configure software products. Generally, few features are sufficient to allow configuring millions of software products. As a result, selecting the products matching given testing objectives is a difficult problem. The testing process usually involves multiple and potentially conflicting testing objectives to fulfill, e.g. maximizing the number of optional features to test while at the same time both minimizing the number of products and minimizing the cost of testing them. However, most approaches for generating products usually target a single objective, like testing the maximum amount of feature interactions. While focusing on one objective may be sufficient in certain cases, this practice does not reflect real-life testing situations. The present paper proposes a genetic algorithm to handle multiple conflicting objectives in test generation for SPLs. Experiments conducted on FMs of different sizes demonstrate the effectiveness, feasibility and practicality of the introduced approach.