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... them run faster than Daikon, primarily because Daikon checks many more invariants (for example, millions of times more, on flex [29]). The Agitator product developed by Agitar was inspired by Daikon =-=[31]-=-. Agitar performs dynamic invariant detection in order to inform users about tests, and to improve those tests. The results are called “observations”, they include equality (x = y), range (−10 ≤ x ≤ 1...

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...e random test cases, aimed at automatically generating new test inputs that can direct the execution along alternative program paths. Another example is provided by the notion of “software agitation” =-=[17]-=-, an automatic unit test technique supported by the Agitator commercial tool, which combines different analyses, such as symbolic execution, constraint solving, and directed random input generation fo...

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...Hangal and Lam [2002] present the DIDUCE invariant inference tool, which is optimized for efficiency and can possibly allow bigger testees and longer-running test suites than Daikon. Agitar Agitator [=-=Boshernitsan et al. 2006-=-], a commercial tool, also uses Daikon-like inference techniques to infer likely invariants (termed “observations”) from test executions and suggests these observations to developers so that the devel...

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...d on observed return values and object states and adds assertions to check future runs against these observations. A similar approach has also been adopted in commercial tools such as Agitar Agitator =-=[6]-=-. While such approaches can be used to derive efficient oracles, they do not serve to identify which of these assertions are actually useful, and such techniques are therefore only found in regression...

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...nference is exemplified by (and often even identified with) the Daikon tool [7, 8, 25, 26]—the first and most mature representative of the approach, with the widest use in further applications (e.g., =-=[2, 5, 6, 10, 20, 33]-=-). Daikon tracks a program’s variables during execution and generalizes the observed behavior to invariants— preconditions, postconditions, and class invariants. Daikon instruments the program, execut...

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...work [14, 15] investigates dynamic inference techniques for algebraic specifications. Some of the ideas developed in academic research on contract inference were also adopted by industry. AgitatorOne =-=[5]-=-, previously called Agitator, implements a Daikon-like approach for inferring assertions. Users have the option of promoting these inferred assertions to contracts included in the program or discardin...

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...Lines 8, 10, and 12) . C. Test Generator The Test Generator component usesJUnitFactory [8] for test generation. JUnit Factory is a commercial automated characterization test generator based on Agitar =-=[1]-=-. The input to the Test Generator component is the instrumented code and the test driver generated by the Instrumenter component. JUnit Factory is used to generate tests for the test driver. JUnit Fac...

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...synthesizes and inserts new assertions into the existing test-input set to check future runs against the collected method-return values and receiverobject states. Parasoft Jtest [22], Agitar Agitator =-=[3]-=-, and JUnit Factory [12] adopt a similar approach to generate test inputs with assertions called characterization tests. Our approach does not generate assertions, but captures instead behaviors from ...

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...tests. The problem becomes particularly acute when developers make a “deep” change that breaks many tests or when developers have a large test suite produced by an automatic test-generation tool [9], =-=[10]-=-, [11], [12], [13], [14]. Automatically generated tests tend to be more fragile than manually written tests, e.g., dozens of automatically generated tests can fail on a seemingly simple code change. D...

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...he program computes, and then reports properties that were true over the observed executions. A primary example of a dynamic invariants detector is Daikon [13]. Other examples are described in, e.g., =-=[7, 36]-=-. As opposed to scenario-based specification mining, which, like, e.g., [6, 25, 41], is concerned with detecting temporal invariants in the form of ordering constraints over program events, these tool...