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You searched on: Author: paul black

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51. Using Model Checking to Generate Tests From Specifications
Published: 11/1/1998
Authors: P E Ammann, Paul E Black, William J Majurski
Abstract: We apply a model checker to the problem of test generation using a new application of mutation analysis. We define syntactic operators, each of which produces a slight variation on a given model. The operators define a form of mutation analysis at ...

52. Using Model Checking to Generate Tests from Specifications
Series: NIST Interagency/Internal Report (NISTIR)
Report Number: 6166
Published: 11/1/1998
Authors: P E Ammann, Paul E Black, William J Majurski

53. Dictionary of Algorithms and Data Structures
Published: 10/1/1998
Author: Paul E Black
Abstract: The National Software Reference Library (NSRL) of the U.S. National Institute of Standards and Technology (NIST) collects software from various sources and publishes file profiles computed from this software (such as MD5 and SHA-1 hashes) as a Refer ...

54. Reliability of Conformance Tests
Published: 8/21/1998
Authors: Robert Charles Hagwood, Raghu N Kacker, James H Yen, D L. Banks, Lynne S. Rosenthal, Leonard J Gallagher, Paul E Black
Abstract: A conformance test is a software assurance test that is applied in order to determine if specification requirements of the software are being met. It is a time-dependent model, where the software object is subjected to an a priori known test suite. ...

55. Software Testing: Protocol Comparison
Published: 5/29/1998
Authors: James H Yen, D L. Banks, Leonard J Gallagher, Paul E Black, Robert Charles Hagwood, Raghu N Kacker, Lynne S. Rosenthal
Abstract: Software testing is hard, expensive, and uncertain. Many protocols have been suggested, especially in the area of conformance verification. In order to compare the efficacy of these protocols, we have implemented a designed simulation experiment th ...

56. Formal Verification of Secure Programs in the Presence of Side Effects
Published: 1/1/1998
Authors: Paul E Black, P J Windley
Abstract: Much software is written in industry standard programming languages, but these these languages often have complex semantics making them hard to formalize. For example, the use of expressions with side effects is common in C programs. We present new i ...

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