Abstract: Software testing of networked devices using whitebox fuzzing is provided. Target network device (TC) can execute a software target that can selectively receive fuzzed data to perturb the execution of the software target. The perturbation can be correlated with the fuzzed data to detect intentional and unintentional features of the software target in. Information related to the interaction of the TC and a target network peer device (TPC) can be employed to determine a state input. Optionally, the TC can interact with the TPC normally until a determined state input, at which point, a fuzzed input can be substituted into the communication to the TC as if it were from the TPC. Resulting deviations from normal operation can then be determined and analyzed. Further optionally, a session dependent conditional and corresponding value can be determined.

Abstract: The disclosed subject matter provides for software testing using metaphor based language fuzzing. Metaphor based language fuzzing can decompose a code segment into a metaphor representing the code segment. The metaphor can be mutated based on determined logical perturbations to any element of the metaphor. The mutation of the metaphor can act as a surrogate for mutation of the code segment. The mutated metaphor can be analyzed to reveal performance differences in comparison to the code segment. These performance difference can be correlated to mutation of the metaphor such that a corresponding mutation of the code segment can be correlated by extrapolation. Moreover, mutators can be stored and reused on other metaphors. Furthermore, employing a metaphor as a root language surrogate can facilitate generating a reduced number of mutators as compared to directly mutating code segments in a plurality of computer languages.

Abstract: Flow based fault testing is provided. A logical constraint model or a state model (LS model) can be generated based on logic/state characteristics of a system under test (SUT). The LS model can be generated from logical constraint grammar statements. The logical constraint grammar can be parsed as part of a pre-test analysis to seek faults related to the logic or states of the model. The inputs and outputs related to the SUT can be employed to determine faults, including post-test analysis for faults. The disclosed subject matter can capture in an automated or semi-automated manner faults that can be missed in more conventional fuzz testing. Further, flow based fault testing can be employed alone, along with, or in combination with conventional fuzz testing.