Symbiotic 8: Parallel and Targeted Test Generation

The setup of Symbiotic 8 for Test-Comp 2021 brings radical changes in the test generation for property. Similarly as in Symbiotic 7, we generate tests by running our fork of symbolic executor Klee on the analyzed program. Symbiotic 8, however, runs several instances of Klee in parallel. We run one instance of Klee on the original program and, simultaneously, we create one (intentionally unsound) program slice for every program-terminating instruction in the program and run Klee on these slices. Apart from this principal change, we also improved other components of the tool, mainly the program slicer. Further, our fork of Klee now supports symbolic pointer arithmetics and comparison of symbolic addresses.

Applications of Synchronized Pushdown Systems

A precise static data-flow analysis transforms the program into a context-sensitive and field-sensitive approximation of the program. It is challenging to design an analysis of this precision efficiently due to the fact that the analysis is undecidable per se. Synchronized pushdown systems (SPDS) present a highly precise approximation of context-sensitive and field-sensitive data-flow analysis. This chapter presents some data-flow analyses that SPDS can be used for. Further on, this chapter summarizes two other contributions of the thesis “Synchronized Pushdown System for Pointer and Data-Flow Analysis” called Boomerang and IDEal. Boomerang is a demand-driven pointer analysis that builds on top of SPDS and minimizes the highly computational effort of a whole-program pointer analysis by restricting the computation to the minimal program slice necessary for an individual query. IDEal is a generic and efficient framework for data-flow analyses, e.g., typestate analysis. IDEal resolves pointer relations automatically and efficiently by the help of Boomerang. This reduces the burden of implementing pointer relations into an analysis. Further on, IDEal performs strong updates, which makes the analysis sound and precise.

Extracting Business Rule from existing COBOL programs for Redevelopment

The paper describes an industrial business study carried out to regain the business knowledge embedded in a legacy COBOL application. The aim of this work was to extract out the information required to re- implement the Legacy programs in a new client/server environment. The progress solution is in four step. Firstly, the programs were restructured, secondly the programs were sliced into business logic modules, third the business modules were subjected to a multi view analysis and finally the views were integrated into a unified documentation describing the data, decision and procedural flow of each program slice.

USING PROGRAM SLICING TO IMPROVE THE EFFICIENCY AND EFFECTIVENESS OF CLUSTER TEST SELECTION

Cluster test selection is a new successful approach to select a subset of the existing test suite in regression testing. In this paper, program slicing is introduced to improve the efficiency and effectiveness of cluster test selection techniques. A static slice is computed on the modified code. The execution profile of each test case is filtered by the program slice to highlight the parts of software affected by modification, called slice filtering. The slice filtering reduces the data dimensions for cluster analysis, such that the cost of cluster test selection is saved dramatically. The experiment results show that the slice filtering techniques could reduce the cost of cluster test selection significantly and could also improve the effectiveness of cluster test selection modestly. Therefore, cluster test selection by filtering has more potential scalability to deal with large software.