Using Data Mining to Assess Sofwtare Reliability

The paper investigates the applicability of data mining in software reliability assessment and maintenance. The proposed methodology comprises three steps. First the input models are defined by selecting parts of the source code, such as functions, routines and variables, to populate a database. Then Clustering is applied to identify sub-sets of source code that are grouped together according to custom-made similarity metrics. Finally Association rules are used to establish inter-group and intra-group relationships. Experimental results show that the methodology can assess modularity, detect complexity and predict the impact of changes.