Argumentation-based design rationale: what use at what cost?
International Journal of Human-Computer Studies
From object-oriented to goal-oriented requirements analysis
Communications of the ACM
Code Factoring And The Evolution Of Evolvability
GECCO '02 Proceedings of the Genetic and Evolutionary Computation Conference
Fitness Function Design To Improve Evolutionary Structural Testing
GECCO '02 Proceedings of the Genetic and Evolutionary Computation Conference
GPTesT: A Testing Tool Based On Genetic Programming
GECCO '02 Proceedings of the Genetic and Evolutionary Computation Conference
Using Heuristic Search Techniques To Extract Design Abstractions From Source Code
GECCO '02 Proceedings of the Genetic and Evolutionary Computation Conference
Search Heuristics, Case-based Reasoning And Software Project Effort Prediction
GECCO '02 Proceedings of the Genetic and Evolutionary Computation Conference
A New Representation And Crossover Operator For Search-based Optimization Of Software Modularization
GECCO '02 Proceedings of the Genetic and Evolutionary Computation Conference
Converging on the Optimal Attainment of Requirements
RE '02 Proceedings of the 10th Anniversary IEEE Joint International Conference on Requirements Engineering
IEEE Transactions on Software Engineering
Evolutionary testing in the presence of loop-assigned flags: a testability transformation approach
ISSTA '04 Proceedings of the 2004 ACM SIGSOFT international symposium on Software testing and analysis
Metrics Are Fitness Functions Too
METRICS '04 Proceedings of the Software Metrics, 10th International Symposium
Evolving Transformation Sequences using Genetic Algorithms
SCAM '04 Proceedings of the Source Code Analysis and Manipulation, Fourth IEEE International Workshop
Search-based software test data generation: a survey: Research Articles
Software Testing, Verification & Reliability
Data Mining
The multi-objective next release problem
Proceedings of the 9th annual conference on Genetic and evolutionary computation
Optimizing requirements decisions with keys
Proceedings of the 4th international workshop on Predictor models in software engineering
Optimized Resource Allocation for Software Release Planning
IEEE Transactions on Software Engineering
Using automated search to generate test data for matlab
Proceedings of the 11th Annual conference on Genetic and evolutionary computation
Finding robust solutions in requirements models
Automated Software Engineering
A Theoretical and Empirical Study of Search-Based Testing: Local, Global, and Hybrid Search
IEEE Transactions on Software Engineering
Formal analysis of the effectiveness and predictability of random testing
Proceedings of the 19th international symposium on Software testing and analysis
Automatically finding the control variables for complex system behavior
Automated Software Engineering
On the number and nature of faults found by random testing
Software Testing, Verification & Reliability
Ant colony system: a cooperative learning approach to the traveling salesman problem
IEEE Transactions on Evolutionary Computation
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Background: Search-based Software Engineering (SBSE) uses a variety of techniques such as evolutionary algorithms or meta-heuristic searches but lacks a standard baseline method. Aims: The KEYS2 algorithm meets the criteria of a baseline. It is fast, stable, easy to understand, and presents results that are competitive with standard techniques. Method: KEYS2 operates on the theory that a small sub-set of variables control the majority of the search space. It uses a greedy search and a Bayesian ranking heuristic to fix the values of these variables, which rapidly forces the search towards stable high-scoring areas. Results: KEYS2 is faster than standard techniques, presents competitive results (assessed with a rank-sum test), and offers stable solutions. Conclusions: KEYS2 is a valid candidate to serve as a baseline technique for SBSE research.