Mining Attributes Patterns of Defective Modules for Object Oriented Software

Abstract

Defect prediction is the process of predicting the fault prone module using some pre-mined patterns or rules. Several statistical and mathematical strategies have been used in recent past to mine these rules. However, the interpretability of these rules is the matter of concern. In real development process an expert is required to demonstrate the working of mined patterns which prevents the use of these mined patterns in software development process. Considering these facts, in this study we tried to find the combination of attribute-value pair which indicates the bug. These attribute-value pair is known as defect pattern. For defect pattern mining we used GUHA (General Unary Hypothesis Automaton) procedure which is oldest yet very powerful method of pattern mining. The basic idea of GUHA procedure is to mine the entire possible and interesting hypothesis supported by the data in predefined logical form. The experimental results show that the mined patterns can be used as a rule to identify the defective module. Moreover, the mined patterns do not suffer from the interpretability problems.