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Model checking engines employed to generate test cases covering the structure of the model or code are limited by factors like code size, loops and floating point computation. We propose an approach that overcomes these limitations by approximating code fragments by dynamically inferring their post-conditions. We use Daikon to infer likely invariants from execution traces, which are used as post conditions...
Static analysis of code is very effective in finding common programmer errors but it comes at a price - a large number of false positives. Model checking, on the other hand, is very precise but does not scale up. We have developed a tool that combines both techniques and also implements a novel loop abstraction. The tool was run on 2 million lines of embedded code to analyze for two properties - division...
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