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We present a combinatorial testing-based fault localization tool called BEN. BEN takes as input three types of information, including the subject program, the source code, an input parameter model, and a combinatorial test set created based on the input parameter model. It is assumed that the combinatorial test set has already been executed, and thus the execution status of each test is known. The...
Combinatorial testing has been shown to be a very effective testing strategy. After a failure is detected, the next task is to identify the fault that causes the failure. In this paper, we present an approach to fault localization that leverages the result of combinatorial testing. Our approach is based on a notion called failure-inducing combinations. A combination is failure-inducing if it causes...
Combinatorial testing (CT) aims at detecting interaction failures between parameters in a system. Identifying the failure-inducing combinations of a failing test configuration can help developers find the cause of this failure. However, most studies in CT focus on detecting the failures rather than identifying failure-inducing combinations. In this paper, we propose the notion of a tuple relationship...
Combinatorial Testing (CT) is a systematic way of sampling input parameters of the software under test (SUT). A t-way combinatorial test set can exercise all behaviors of the SUT caused by interactions between t input parameters or less. Although combinatorial testing can provide fault detection capability, it is often desirable to isolate the input combinations that cause failures. Isolating these...
A t-way combinatorial test set is designed to detect failures that are triggered by combinations involving no more than t parameters. Assume that we have executed a t-way test set and some tests have failed. A natural question to ask is: What combinations have caused these failures? Identifying such combinations can facilitate the debugging effort, e.g., by reducing the scope of the code that needs...
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