Statechart Slicing

The paper discusses how to reduce a statechart model by slicing. We start with the discussion of control dependencies and data dependencies in statecharts. The and-or dependence graph is introduced to represent control and data dependencies for statecharts. We show how to slice statecharts by using this dependence graph. Our slicing approach helps systems analysts and system designers in understanding system specifications, maintaining software systems, and reusing parts of systems models

Fault Localization in Multi-Threaded C Programs using Bounded Model Checking (extended version)

Software debugging is a very time-consuming process, which is even worse for multi-threaded programs, due to the non-deterministic behavior of thread-scheduling algorithms. However, the debugging time may be greatly reduced, if automatic methods are used for localizing faults. In this study, a new method for fault localization, in multi-threaded C programs, is proposed. It transforms a multi-threaded program into a corresponding sequential one and then uses a fault-diagnosis method suitable for this type of program, in order to localize faults. The code transformation is implemented with rules and context switch information from counterexamples, which are typically generated by bounded model checkers. Experimental results show that the proposed method is effective, in such a way that sequential fault-localization methods can be extended to multi-threaded programs.Comment: extended version of paper published at SBESC'1

Search-based amorphous slicing

Amorphous slicing is an automated source code extraction technique with applications in many areas of software engineering, including comprehension, reuse, testing and reverse engineering. Algorithms for syntax-preserving slicing are well established, but amorphous slicing is harder because it requires arbitrary transformation; finding good general purpose amorphous slicing algorithms therefore remains as hard as general program transformation. In this paper we show how amorphous slices can be computed using search techniques. The paper presents results from a set of experiments designed to explore the application of genetic algorithms, hill climbing, random search and systematic search to a set of six subject programs. As a benchmark, the results are compared to those from an existing analytical algorithm for amorphous slicing, which was written specifically to perform well with the sorts of program under consideration. The results, while tentative at this stage, do give grounds for optimism. The search techniques proved able to reduce the size of the programs under consideration in all cases, sometimes equaling the performance of the specifically-tailored analytic algorithm. In one case, the search techniques performed better, highlighting a fault in the existing algorith