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Topic Area: Software Testing Metrics
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Displaying records 81 to 90 of 107 records.
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81. Software Assurance Common Body of Knowledge Workshop|||June 1-2, 2005|Arlington, Virginia
Topic: Software Testing Metrics
Published: 6/1/2005
Authors: Michael J Kass, Elizabeth Nee nee Fong
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 ...
http://www.nist.gov/manuscript-publication-search.cfm?pub_id=150320

82. Software Assurance Metrics and Tool Evaluation (SAMATE)
Topic: Software Testing Metrics
Published: 4/1/2005
Author: Michael J Kass
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 ...
http://www.nist.gov/manuscript-publication-search.cfm?pub_id=150318

83. Software Assurance Using Structured Assurance Case Models
Series: NIST Interagency/Internal Report (NISTIR)
Report Number: 7608
Topic: Software Testing Metrics
Published: 5/1/2009
Authors: Thomas R. Rhodes, Frederick E Boland Jr, Elizabeth Nee nee Fong, Michael J Kass
Abstract: Software assurance is an important part of the software development process to reduce risks and ensure that the software is dependable and trustworthy. Software defects and weaknesses can often lead to software errors and failures and to exploitatio ...
http://www.nist.gov/manuscript-publication-search.cfm?pub_id=902688

84. Software Assurances Metrics and Tool Evaluation
Topic: Software Testing Metrics
Published: 7/1/2005
Author: Michael Sindelar
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 ...
http://www.nist.gov/manuscript-publication-search.cfm?pub_id=50317

85. Software Error Analysis
Series: Special Publication (NIST SP)
Report Number: 500-209
Topic: Software Testing Metrics
Published: 3/1/1993
Authors: W W Peng, D Wallace
http://www.nist.gov/manuscript-publication-search.cfm?pub_id=900458

86. Software Fault Complexity and Implications for Software Testing
Topic: Software Testing Metrics
Published: 6/16/2004
Authors: David R Kuhn, D Wallace, A M Gallo
Abstract: Exhaustive testing of computer software is intractable, but empirical studies of software failures suggest that testing can in some cases be effectively exhaustive. Data reported in this study and others show that software failures in a variety of ...
http://www.nist.gov/manuscript-publication-search.cfm?pub_id=151290

87. Software Quality Assurance: Documentation and Reviews
Series: NIST Interagency/Internal Report (NISTIR)
Report Number: 4909
Topic: Software Testing Metrics
Published: 9/1/1992
Authors: D Wallace, W W Peng, L M Ippolito
http://www.nist.gov/manuscript-publication-search.cfm?pub_id=900651

88. Software Testing by Statistical Methods - Preliminary Success Estimates for Approaches Based on Binomial Models, Coverage Designs, Mutation Testing, and Usage Models
Series: NIST Interagency/Internal Report (NISTIR)
Report Number: 6129
Topic: Software Testing Metrics
Published: 3/1/1998
Authors: D L. Banks, W H. Dashiell, Leonard J Gallagher, Robert Charles Hagwood, Raghu N Kacker, Lynne S. Rosenthal
http://www.nist.gov/manuscript-publication-search.cfm?pub_id=900838

89. Software Verification and Validation: Its Role in Computer Assurance and Its Relationship with Software Project Management Standards
Series: Special Publication (NIST SP)
Report Number: 500-165
Topic: Software Testing Metrics
Published: 9/5/1989
Authors: D Wallace, Roger U. Fujii
http://www.nist.gov/manuscript-publication-search.cfm?pub_id=905731

90. Static Analyzers in Software Engineering
Topic: Software Testing Metrics
Published: 3/2/2009
Author: Paul E Black
Abstract: Static analyzers can report possible problems in code and help reinforce good practices of developers. We contrast the strengths of static analyzers with testing and indicate the current state of the art.
http://www.nist.gov/manuscript-publication-search.cfm?pub_id=901506



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