State-Model-Based Regression Test Reduction for Component-Based Software

Abstract EN

We present a novel regression test selection approach based on analysis of state and dependence models of components.

Our technique targets to select a smaller regression test suite compared to the pure dependence-based RTS approaches while maintaining the fault revealing effectiveness.

In our approach, after a modification, control and data dependencies are analyzed to identify the potentially affected statements.

Subsequently, the state model of the component is analyzed to compute a precise publishable change information to support efficient regression test selection by the application developers.