1999
DOI: 10.14236/ewic/iwfm1999.11
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Tests Derivation from Model Based Formal Specifications

Abstract: Software testing consumes a large percentage of total software development costs. Yet, it is still usually performed manually in a non rigorous fashion. In this work we suggest how state of the art practices in the area of testing can be applied to the systematic generation of tests from model-based formal specifications. Tests Derivation from Model Based Formal Specifications However we should always keep in mind the shortcomings of defect testing as highlighted in [15]: primarily it may not always be the mos… Show more

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Cited by 2 publications
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“… 419 This technique, where one calculates the partial derivative in the i th feature dimension for the j th sample is also known as saliency mapping. Thanks to libraries like tf-explain 420 and keras-vis, 421 appealing visualizations of model explanations are often only one function call away, but one should be aware that there are many caveats wherefore some sanity checks (such as randomization tests or addition of noise) should be used before relying on such a model interpretation. 417 , 422…”
Section: How To Interpret the Results: Avoiding The Clever Hansmentioning
confidence: 99%
“… 419 This technique, where one calculates the partial derivative in the i th feature dimension for the j th sample is also known as saliency mapping. Thanks to libraries like tf-explain 420 and keras-vis, 421 appealing visualizations of model explanations are often only one function call away, but one should be aware that there are many caveats wherefore some sanity checks (such as randomization tests or addition of noise) should be used before relying on such a model interpretation. 417 , 422…”
Section: How To Interpret the Results: Avoiding The Clever Hansmentioning
confidence: 99%