In the context of reverse-engineering project we designed a usecase specification recovery technique for legacy information systems. With our technique, we can recover the alternative flows of each use-case of the system. It is based on a dynamic (i.e. runtime) analysis of the working of the system using execution traces. But "traditional" execution trace format do not contain enough information for this approach to work. Then we designed a new execution trace format together with the associated tool to get the program's dynamic decision tree corresponding to each of the use-case scenario. These trees are then processed to find the possible variants from the main scenario of each use-case. In this paper we first present our approach to the use-case specification recovery technique and the new trace format we designed. Then the decision tree compression technique is showed with a feasibility study. The contribution of the paper is our approach to the recovery of legacy systems' use-case, the new trace format and the decision tree processing technique.

Abstract:Dynamic analysis of programs is one of the most promising techniques to reverse-engineer legacy code for software understanding. However, the key problem is to cope with the volume of data to process, since a single execution trace could contain millions of calls. Although many trace analysis techniques have been proposed, most of them are not very scalable. To overcome this problem, we developed a segmentation technique where the trace is pre-processed to give it the shape of a time series of data. Then we apply technical analysis techniques borrowed from the financial domain. In particular we show how the moving average filtering can be used to identify the "trend" of the involvement of the class in the execution of the program. Based on the comparison of the "trends" of all the classes, one can compute the coupling of classes in order to recover the hidden functional architecture of the software.