A lightweight process for change identification and regression test selection in using COTS components

Various regression test selection techniques have been developed and have shown fault detection effectiveness. The majority of these test selection techniques rely on access to source code for change identification. However, when new releases of COTS components are made available for integration and testing, source code is often not available. In this paper, we present a lightweight integrated-black-box approach for component change identification (I-BACCI) process for selection of regression tests for user/glue code that uses COTS components. I-BACCI is applicable when component licensing agreements do not preclude analysis of the binary files. A case study of the process was conducted on an ABB product that uses a medium-scale internal ABB software component. Five releases of the component were examined to evaluate the efficacy of the proposed process. The result of the case study indicates this process can reduce the required number of regression tests by 54% on average.