Genetic Micro-Programs for Automated Software Testing with Large Path Coverage

Created by W.Langdon from gp-bibliography.bib Revision:1.7615

@InProceedings{Goschen:2022:CEC,

• author = "Jarrod Goschen and Anna S. Bosman and Stefan Gruner",
• title = "Genetic Micro-Programs for Automated Software Testing with Large Path Coverage",
• booktitle = "2022 IEEE Congress on Evolutionary Computation (CEC)",
• year = "2022",
• editor = "Carlos A. Coello Coello and Sanaz Mostaghim",
• address = "Padua, Italy",
• month = "18-23 " # jul,
• keywords = "genetic algorithms, genetic programming, SBSE, Software testing, Codes, Instruments, Software algorithms, Evolutionary computation, Software systems, Software testing, input domain partitioning, automated data generation",
• isbn13 = "978-1-6654-6708-7",
• DOI = "doi:10.1109/CEC55065.2022.9870310",
• abstract = "Ongoing progress in computational intelligence (CI) has led to an increased desire to apply CI techniques for the purpose of improving software engineering processes, particularly software testing. Existing state-of-the-art automated software testing techniques focus on using search algorithms to discover input values that achieve high execution path coverage. These algorithms are trained on the same code that they intend to test, requiring instrumentation and lengthy search times to test each software component. We outline a novel genetic programming framework, where the evolved solutions are not input values, but microprograms that can repeatedly generate input values to efficiently explore a software components input parameter domain. We also argue that our approach can be generalised such as to be applied to many different software systems, and is thus not specific to merely the particular software component on which it was trained.",
• notes = "Also known as \cite{9870310} ‘pilot study’ GMP = ADF = ‘micro-programs'. lenience. fitness = path coverage on 5 tests. Types same as types of input SUT function to be tested. 'only uniform input type' (ie no mixed types tried). Loop <=250 iterations. If. SUT has no side-effects (ie non OO?) bloat",

}

Genetic Programming entries for Jarrod Goschen Anna S Bosman Stefan Gruner

Citations