Model Based Test Case Prioritization Using Association Rule Mining

Regression testing has gained importance due to increase in frequency of change requests made for software during maintenance phase. The retesting criteria of regression testing leads to increasing cost and time. Prioritization is an important procedure during regression testing which makes the debugging easier. This paper discusses a novel approach for test case prioritization using Association Rule Mining (ARM). In this paper, the system under test is modelled using UML Activity Diagram (AD) which is further converted into an Activity Graph (AG). A historical data store is maintained to keep details about the system which revealing more number of faults. Whenever a change is made in the system, the frequent patterns of highly affected nodes are found out. These frequent patterns reveal the probable affected nodes i.e. used to prioritize the test cases. This approach effectively prioritizes the test cases with a higher Average Percentage of Fault Detection (APFD) value.