A Code Analysis Base Regression Test Selection Technique for D Programming Language

D is a new programming language. This is an object-oriented, imperative, multi-paradigm system programming language. Regression testing on D programming language still untouched by researchers. Our research attempts to bridge this gap by introducing a techniques to revalidate D programs. A framework is proposed which automates both the regression test selection and regression testing processes for D programming language. As part of this approach, special consideration is given to the analysis of the source code of D language. In our approach system dependence graph representation will be used for regression test selection for analyzing and comparing the code changes of original and modified program. First we construct a system dependence graph of the original program from the source code. When some modification is executed in a program, the constructed graph is updated to reflect the changes. Our approach in addition to capturing control and data dependencies represents the dependencies arising from object-relations. The test cases that exercise the affected model elements in the program model are selected for regression testing. Empirical studies carried out by us show that our technique selects on an average of 26.36. % more fault-revealing test cases compared to a UML based technique while incurring about 37.34% increase in regression test suite size.