Semi-Automated Tool Support for Identification and Prioritization of Impacted Functions in Software Systems

Abstract

Change is an integral part of any software system. Predicting the impact of making changes through techniques of change impact analysis helps engineers identify and analyze those parts of the system that will be potentially affected by requested change(s). This chapter presents a semi-automated approach to (a) compute likelihood of impacted functions in a system through identification and analysis of functional dependencies between them and (b) assist software engineers in selective regression testing. This technique first classifies the impact set data into two categories based on their type of impact propagation. Next it performs prioritization on classified data to rank functions into higher and lower levels according to the degree of impact they will make. This prediction will help in lowering maintenance cost and effort of software engineers. Thus, a software engineer can first run those test cases which cover segments with higher impacted priority to minimize regression test selection.