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Defects4J has enabled numerous software testing and debugging research work since its introduction. A large part of its contribution, and the resulting popularity, lies in the clear separation and distillation of the root cause of each individual test failure based on careful manual analysis, which in turn allowed researchers to easily study individual faults in isolation. However, in a realistic debugging scenario, multiple faults can coexist and affect test results collectively. Study of automated debugging techniques for these situations, such as failure clustering or fault localisation for multiple faults, would significantly benefit from a reliable benchmark of multiple, coexisting faults. We search f
Computational models of human language often involve combinatorial problems. For instance, a probabilistic parser may marginalize over exponentially many trees to make predictions. Algorithms for such problems often employ dynamic programming and are
Bug patterns are erroneous code idioms or bad coding practices that have been proved to fail time and time again, which are usually caused by the misunderstanding of a programming languages features, the use of erroneous design patterns, or simple mi
The success of several constraint-based modeling languages such as OPL, ZINC, or COMET, appeals for better software engineering practices, particularly in the testing phase. This paper introduces a testing framework enabling automated test case gener
This paper presents an approach towards specifying and verifying adaptive distributed systems. We here take fault-handling as an example of adaptive behavior and propose a modeling language Sandal for describing fault-prone message-passing systems. O
We investigate the problem of classifying a line of program as containing a vulnerability or not using machine learning. Such a line-level classification task calls for a program representation which goes beyond reasoning from the tokens present in t