Abstract: Software testing is arguably the least understood part of a software development process. One of the major reasons for this status is that various strategies are defined and analyzed, but rarely a software testing strategy is designed and optimized. In response to this status, the controlled Markov chains (CMC) approach to software testing treats the software testing as a control problem. The software under test serves as a controlled object that is modeled as a controlled Markov chain, and the software testing strategy serves as the corresponding controller. They constitute a closed loop feedback system, and the testing strategy is designed and optimized in accordance with testing goals given a priori in the setting of the theory of controlled Markov chains. The CMC approach justifies the idea of software cybernetics, which is defined as the interplay between software theory/engineering and control theory/engineering. This paper presents an adaptive approach to the software testing problem and then compares adaptive software testing with random testing by simulation examples. Simulation results show that the adaptive software testing is feasible and is superior to the random testing.

Key words: software cybernetics, controlled Markov chain, software testing, adaptive testing, random testing