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تسجيل مستخدم جديدFaster SAT Solving for Software with Repeated Structures (with Case Studies on Software Test Suite Minimization)
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Theorem provers has been used extensively in software engineering for software testing or verification. However, software is now so large and complex that additional architecture is needed to guide theorem provers as they try to generate test suites. The SNAP test suite generator (introduced in this paper) combines the Z3 theorem prover with the following tactic: cluster some candidate tests, then search for valid tests by proposing small mutations to the cluster centroids. This technique effectively removes repeated structures in the tests since many repeated structures can be replaced with one centroid. In practice, SNAP is remarkably effective. For 27 real-world programs with up to half a million variables, SNAP found test suites which were 10 to 750 smaller times than those found by the prior state-of-the-art. Also, SNAP ran orders of magnitude faster and (unlike prior work) generated 100% valid tests.
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Combinatorial testing has been suggested as an effective method of creating test cases at a lower cost. However, industrially applicable tools for modeling and combinatorial test generation are still scarce. As a direct effect, combinatorial testing
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Statistics comes in two main flavors: frequentist and Bayesian. For historical and technical reasons, frequentist statistics has dominated data analysis in the past; but Bayesian statistics is making a comeback at the forefront of science. In this pa
per, we give a practical overview of Bayesian statistics and illustrate its main advantages over frequentist statistics for the kinds of analyses that are common in empirical software engineering, where frequentist statistics still is standard. We also apply Bayesian statistics to empirical data from previous research investigating agile vs. structured development processes, the performance of programming languages, and random testing of object-oriented programs. In addition to being case studies demonstrating how Bayesian analysis can be applied in practice, they provide insights beyond the results in the original publications (which used frequentist statistics), thus showing the practical value brought by Bayesian statistics.
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Harsh Beohar
, Mohammad Reza Mousavi (Center for Research on Embeddedn Systems Halmstad University
2014
A major challenge in testing software product lines is efficiency. In particular, testing a product line should take less effort than testing each and every product individually. We address this issue in the context of input-output conformance testin
g, which is a formal theory of model-based testing. We extend the notion of conformance testing on input-output featured transition systems with the novel concept of spinal test suites. We show how this concept dispenses with retesting the common behavior among different, but similar, products of a software product line.
Context: software projects are common resources in Software Engineering experiments, although these are often selected without following a specific strategy, which reduces the representativeness and replication of the results. An option is the use of
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