Change Impact Analysis for Large-scale Enterprise Systems

This work is concerned with analysing the potential impact of direct changes to largescale enterprise systems, and, in particular, how to minimise testing efforts on such changes. A typical enterprise system may consist of hundreds of thousands of classes and millions of methods. Thus, it is extremely costly and difficult to apply conventional testing techniques to such a system. Retesting everything after a change is very expensive, and in practice generally not necessary. Selective testing can be more effective. However, it requires a deep understanding of the target system and a lack of that understanding can lead to insufficient test coverage. Change Impact Analysis can be used to estimate the impacts of the changes to be applied, providing developers/testers with confidence in selecting necessary tests and identifying untested entities. Conventional change impact analysis approaches include static analysis, dynamic analysis or a hybrid of the two analyses. They have proved to be useful on small or medium size programs, providing users an inside view of the system within an acceptable running time. However, when it comes to large-scale enterprise systems, the sizes of the programs are orders of magnitude larger. Conventional approaches often run into resource problems such as insufficient memory and/or unacceptable running time (up to weeks). More critically, a large number of false-negatives and false-positives can be generated from those approaches.