Markov Model-Based Effectiveness Predicting for Software Fault Localization: Markov Model-Based Effectiveness Predicting for Software Fault Localization

Debugging is a necessary phase in software development.Statistical fault localization techniques estimate fault locations by analyzing dynamic program spectra.They build different heuristic analytical models for different program spectra to describe the program behavior.Previous studies show that their effectiveness is related to the target faults and program types;and there is no universally effective technique.By evaluating the feasibility of predicting fault class in a unit test process,this paper employs a Markov model to select a proper such technique to apply,from a candidate set.Empirical study shows it is more effective to locate faults.