@inproceedings{a95a2e36679d4cd2809ad7237f0f00fe,
title = "Effective black-box testing with genetic algorithms",
abstract = "Black-box (functional) test cases are identified from functional requirements of the tested system, which is viewed as a mathematical function mapping its inputs onto its outputs. While the number of possible black-box tests for any non-trivial program is extremely large, the testers can run only a limited number of test cases under their resource limitations. An effective set of test cases is the one that has a high probability of detecting faults presenting ina computer program.In this paper, we introduce a new, computationally intelligent approach to automated generation of effective test cases based on a novel, Fuzzy-Based Age Extension of Genetic Algorithms (FAexGA). The basic idea is to eliminate {"}bad{"} test cases that are unlikely to expose any error, while increasing the number of {"}good{"} test cases that have a high probability of producing an erroneous output. The promising performance of the FAexGA-based approach is demonstrated on testing a complex Boolean expression.",
keywords = "Black-box testing, Computational intelligence, Fuzzy logic, Genetic algorithms, Test prioritization",
author = "Mark Last and Shay Eyal and Abraham Kandel",
year = "2006",
month = jul,
day = "7",
doi = "10.1007/11678779_10",
language = "English",
isbn = "3540326049",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
pages = "134--148",
booktitle = "Hardware and Software, Verification and Testing - First International Haifa Verification Conference, Revised Selected Papers",
note = "1st International Haifa Verification Conference on Hardware and Software, Verification and Testing ; Conference date: 13-11-2005 Through 16-11-2005",
}