14,856 research outputs found

    Is the Stack Distance Between Test Case and Method Correlated With Test Effectiveness?

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    Mutation testing is a means to assess the effectiveness of a test suite and its outcome is considered more meaningful than code coverage metrics. However, despite several optimizations, mutation testing requires a significant computational effort and has not been widely adopted in industry. Therefore, we study in this paper whether test effectiveness can be approximated using a more light-weight approach. We hypothesize that a test case is more likely to detect faults in methods that are close to the test case on the call stack than in methods that the test case accesses indirectly through many other methods. Based on this hypothesis, we propose the minimal stack distance between test case and method as a new test measure, which expresses how close any test case comes to a given method, and study its correlation with test effectiveness. We conducted an empirical study with 21 open-source projects, which comprise in total 1.8 million LOC, and show that a correlation exists between stack distance and test effectiveness. The correlation reaches a strength up to 0.58. We further show that a classifier using the minimal stack distance along with additional easily computable measures can predict the mutation testing result of a method with 92.9% precision and 93.4% recall. Hence, such a classifier can be taken into consideration as a light-weight alternative to mutation testing or as a preceding, less costly step to that.Comment: EASE 201

    LittleDarwin: a Feature-Rich and Extensible Mutation Testing Framework for Large and Complex Java Systems

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    Mutation testing is a well-studied method for increasing the quality of a test suite. We designed LittleDarwin as a mutation testing framework able to cope with large and complex Java software systems, while still being easily extensible with new experimental components. LittleDarwin addresses two existing problems in the domain of mutation testing: having a tool able to work within an industrial setting, and yet, be open to extension for cutting edge techniques provided by academia. LittleDarwin already offers higher-order mutation, null type mutants, mutant sampling, manual mutation, and mutant subsumption analysis. There is no tool today available with all these features that is able to work with typical industrial software systems.Comment: Pre-proceedings of the 7th IPM International Conference on Fundamentals of Software Engineerin

    A Model to Estimate First-Order Mutation Coverage from Higher-Order Mutation Coverage

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    The test suite is essential for fault detection during software development. First-order mutation coverage is an accurate metric to quantify the quality of the test suite. However, it is computationally expensive. Hence, the adoption of this metric is limited. In this study, we address this issue by proposing a realistic model able to estimate first-order mutation coverage using only higher-order mutation coverage. Our study shows how the estimation evolves along with the order of mutation. We validate the model with an empirical study based on 17 open-source projects.Comment: 2016 IEEE International Conference on Software Quality, Reliability, and Security. 9 page

    Deciphering the Mechanisms of Developmental Disorders (DMDD): a new programme for phenotyping embryonic lethal mice

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    International efforts to test gene function in the mouse by the systematic knockout of each gene are creating many lines in which embryonic development is compromised. These homozygous lethal mutants represent a potential treasure trove for the biomedical community. Developmental biologists could exploit them in their studies of tissue differentiation and organogenesis; for clinical researchers they offer a powerful resource for investigating the origins of developmental diseases that affect newborns. Here, we outline a new programme of research in the UK aiming to kick-start research with embryonic lethal mouse lines. The 'Deciphering the Mechanisms of Developmental Disorders' (DMDD) programme has the ambitious goal of identifying all embryonic lethal knockout lines made in the UK over the next 5 years, and will use a combination of comprehensive imaging and transcriptomics to identify abnormalities in embryo structure and development. All data will be made freely available, enabling individual researchers to identify lines relevant to their research. The DMDD programme will coordinate its work with similar international efforts through the umbrella of the International Mouse Phenotyping Consortium [see accompanying Special Article (Adams et al., 2013)] and, together, these programmes will provide a novel database for embryonic development, linking gene identity with molecular profiles and morphology phenotypes
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