Paper Info
Title
Testing of concurrent programs using genetic algorithms
Abstract
Noise injection disturbs the scheduling of program threads in order to increase the probability that more of their different legal interleavings occur during the testing process. However, there exist many different types of noise heuristics with many different parameters that are not easy to set such that noise injection is really efficient. In this paper, we propose a new way of using genetic algorithms to search for suitable types of noise heuristics and their parameters. This task is formalized as the test and noise configuration search problem in the paper, followed by a discussion of how to represent instances of this problem for genetic algorithms, which objectives functions to use, as well as parameter tuning of genetic algorithms when solving the problem. The proposed approach is evaluated on a set of benchmarks, showing that it provides significantly better results than the so far preferred random noise injection.
Year
DOI
Venue
2012
10.1007/978-3-642-33119-0_12
SSBSE
Keywords
Field
DocType
concurrent program,different legal interleavings,better result,genetic algorithm,different parameter,random noise injection,objectives function,noise injection,noise heuristics,different type,noise configuration search problem
Scheduling (computing),Computer science,Random noise,Theoretical computer science,Thread (computing),Heuristics,Artificial intelligence,Search problem,Quality control and genetic algorithms,Machine learning,Genetic algorithm
Conference
Citations 
PageRank 
References 
4
0.39
20
Authors
5
Name
Order
Citations
PageRank
Vendula Hrubá1101.54
Bohuslav Křena2645.15
Zdeněk Letko3683.79
Shmuel Ur4885101.32
Tomáš Vojnar553332.06