TCTracer: Establishing test-to-code traceability links using dynamic and static techniques

Test-to-code traceability links model the relationships between test artefacts and code artefacts. When utilised during the development process, these links help developers to keep test code in sync with tested code, reducing the rate of test failures and missed faults. Test-to-code traceability links can also help developers to maintain an accurate mental model of the system, reducing the risk of architectural degradation when making changes. However, establishing and maintaining these links manually places an extra burden on developers and is error-prone. This paper presents TCTracer, an approach and implementation for the automatic establishment of test-to-code traceability links. Unlike existing work, TCTracer operates at both the method level and the class level, allowing us to establish links between tests and functions, as well as between test classes and tested classes. We improve over existing techniques by combining an ensemble of new and existing techniques that utilise both dynamic and static information and exploiting a synergistic flow of information between the method and class levels. An evaluation of TCTracer using five large, well-studied open source systems demonstrates that, on average, we can establish test-to-function links with a mean average precision (MAP) of 85% and test-class-to-class links with an MAP of 92%

05451 Abstracts Collection -- Beyond Program Slicing

From 06.11.05 to 11.11.05, the Dagstuhl Seminar 05451 ``Beyond Program Slicing\u27\u27 was held in the International Conference and Research Center (IBFI), Schloss Dagstuhl. During the seminar, several participants presented their current research, and ongoing work and open problems were discussed. Abstracts of the presentations given during the seminar as well as abstracts of seminar results and ideas are put together in this paper. The first section describes the seminar topics and goals in general. Links to extended abstracts or full papers are provided, if available

Field-Sensitive Program Slicing

The granularity level of the program dependence graph (PDG) for composite data structures (tuples, lists, records, objects, etc.) is inaccurate when slicing their inner elements. We present the constrained-edges PDG (CE-PDG) that addresses this accuracy problem. The CE-PDG enhances the representation of composite data structures by decomposing statements into a subgraph that represents the inner elements of the structure, and the inclusion and propagation of data constraints along the CE-PDG edges allows for accurate slicing of complex data structures. Both extensions are conservative with respect to the PDG, in the sense that all slicing criteria (and more) that can be specified in the PDG can be also specified in the CE-PDG, and the slices produced with the CE-PDG are always smaller or equal to the slices produced by the PDG. An evaluation of our approach shows a reduction of the slices of 11.67%/5.49% for programs without/with loops

Dependence Cluster Visualization

Large clusters of mutual dependence have long been regarded as a problem impeding comprehension, testing, maintenance, and reverse engineering. An effective visualization can aid an engineer in addressing the presence of large clusters. Such a visualization is presented. It allows a program’s dependence clusters to be considered from an abstract high level down thru a concrete source-level. At the highest level of abstraction, the visualization uses a heat-map (a color scheme) to efficiently overview the clusters found in an entire system. Other levels include three source code views that allow a user to “zoom” in on the clusters starting from the high-level system view, down through a file view, and then onto the actual source code where each cluster can be studied in detail. Also presented are two case studies, the first is the open-source calculator bc and the second is the industrial program copia, which performs signal processing. The studies consider qualitative evaluations of the visualization. From the results, it is seen that the visualization reveals high-level structure of programs and interactions between its components. The results also show that the visualization highlights potential candidates (functions/files) for re-factoring in bc and finds dependence pollution in copia

Sentinel: A Hyper-Heuristic for the Generation of Mutant Reduction Strategies

Mutation testing is an effective approach to evaluate and strengthen software test suites, but its adoption is currently limited by the mutants' execution computational cost. Several strategies have been proposed to reduce this cost (a.k.a. mutation cost reduction strategies), however none of them has proven to be effective for all scenarios since they often need an ad-hoc manual selection and configuration depending on the software under test (SUT). In this paper, we propose a novel multi-objective evolutionary hyper-heuristic approach, dubbed Sentinel, to automate the generation of optimal cost reduction strategies for every new SUT. We evaluate Sentinel by carrying out a thorough empirical study involving 40 releases of 10 open-source real-world software systems and both baseline and state-of-the-art strategies as a benchmark. We execute a total of 4,800 experiments, and evaluate their results with both quality indicators and statistical significance tests, following the most recent best practice in the literature. The results show that strategies generated by Sentinel outperform the baseline strategies in 95% of the cases always with large effect sizes. They also obtain statistically significantly better results than state-of-the-art strategies in 88% of the cases, with large effect sizes for 95% of them. Also, our study reveals that the mutation strategies generated by Sentinel for a given software version can be used without any loss in quality for subsequently developed versions in 95% of the cases. These results show that Sentinel is able to automatically generate mutation strategies that reduce mutation testing cost without affecting its testing effectiveness (i.e. mutation score), thus taking off from the tester's shoulders the burden of manually selecting and configuring strategies for each SUT.Comment: in IEEE Transactions on Software Engineerin

Comparison and Evaluation of Clone Detection Tools

Many techniques for detecting duplicated source code (software clones) have been proposed in the past. However, it is not yet clear how these techniques compare in terms of recall and precision as well as space and time requirements. This paper presents an experiment that evaluates six clone detectors based on eight large C and Java programs (altogether almost 850 KLOC). Their clone candidates were evaluated by one of the authors as an independent third party. The selected techniques cover the whole spectrum of the state-of-the-art in clone detection. The techniques work on text, lexical and syntactic information, software metrics, and program dependency graphs

Coherent clusters in source code

This paper presents the results of a large scale empirical study of coherent dependence clusters. All statements in a coherent dependence cluster depend upon the same set of statements and a↵ect the same set of statements; a coherent cluster’s statements have ‘coherent’ shared backward and forward dependence. We introduce an approximation to efficiently locate coherent clusters and show that it has a minimum precision of 97.76%. Our empirical study also finds that, despite their tight coherence constraints, coherent dependence clusters are in abundance: 23 of the 30 programs studied have coherent clusters that contain at least 10% of the whole program. Studying patterns of clustering in these programs reveals that most programs contain multiple significant coherent clusters. A series of case studies reveals that these major clusters map to logical functionality and program structure. For example, we show that for the program acct, the top five coherent clusters all map to specific, yet otherwise non-obvious, functionality. Cluster visualization can also reveal subtle deficiencies in program structure and identify potential candidates for refactoring e↵orts. Finally a study of inter-cluster dependence is used to highlight how coherent clusters built are connected to each other, revealing higher-level structures, which can be used in reverse engineering