Title :
A stochastic combinatorial optimization model for test sequence optimization
Author :
Wang, Shuai ; Ji, Yindong ; Yang, Shiyuan
Author_Institution :
Dept. of Autom., Tsinghua Univ., Beijing, China
Abstract :
Traditional test sequence optimization methods for path testing have three problems: 1) fake test results may occur; 2) unnecessary repetitive tests may exist; 2) actual test coverage rate could be low. These problems are because the effects of the faults on the test sequence execution are not considered by traditional methods. To solve these problems, we defined a stochastic combinatorial optimization model in this paper. At the same time, we constructed a multistage dynamic combinatorial optimization model to solve it. In each stage, the stochastic optimization is transferred into a deterministic optimization and the faults are taken as the stage changing factors. Simulation results show that the effective test efficiency and test coverage rate are evidently increased by this stochastic combinatorial optimization model.
Keywords :
combinatorial mathematics; optimisation; program testing; software quality; stochastic processes; deterministic optimization; fake test result; multistage dynamic combinatorial optimization model; path testing; software quality; software testing; stochastic combinatorial optimization model; test sequence execution; test sequence optimization; unnecessary repetitive test; Automatic control; Automation; Communication system control; Information science; Laboratories; Mathematical model; Optimization methods; Software testing; Stochastic processes; System testing; stochastic combinatorial optimization model; test coverage rate; test efficiecy; test sequence optimization;
Conference_Titel :
Computing, Communication, Control, and Management, 2009. CCCM 2009. ISECS International Colloquium on
Conference_Location :
Sanya
Print_ISBN :
978-1-4244-4247-8
DOI :
10.1109/CCCM.2009.5270436