Verification and validation for trustworthy software systems
Michael, James Bret
Otani, Thomas W.
MetadataShow full item record
The close interaction between high-integrity systems and their operating environments places a high priority on understanding and satisfying both functional requirements (what the software must do) and safety requirements (what the system must not do). However, traditional validation methods that test the delivered system’s behavior against customer expectations are ineffective (and too late) to assure requirement correctness. Validating requirements early in the system life cycle is increasingly important to organizations that implement capability-based acquisition. For instance, government organizations such as the US Department of Defense (DoD) now play the role of smart buyers whose job is to acquire a set of capabilities. This makes the task of assuring that the system developers correctly translate capabilities into system specifications even more vital. Without such assurance, the DoD can’t reasonably expect successful development of trustworthy software-intensive systems. The US Food and Drug Administration (FDA), on the other hand, plays the role of regulator with the responsibility of approving public use of, say, safety critical medical devices and investigating the cause of mishaps involving these devices. The FDA must ensure that the device behaves as the manufacturer specifies and that the manufacturer acts with due diligence in assessing its products’ trustworthiness - without source code or other detailed information about the systems’ implementation. These examples highlight the need for the continuous and proactive verification and validation (V&V) of complex and safety-critical software systems. This article presents a continuous, computer-aided process that uses statechart assertions, runtime execution monitoring, and scenario-based testing to specify and validate complex system requirements.
The article of record as published may be found at http://dx.doi.org/10.1109/MS.2011.151
Showing items related by title, author, creator and subject.
Big Data and Deep Learning for Defense Acquisition Visibility Environment (DAVE)—Developing NPS Student Thesis Research Zhao, Ying (2017-12-21); NPS-AM-18-012The U.S. Department of Defense (DoD) acquisition process is extremely complex. There are three key processes that must work in concert to deliver capabilities: determining warfighters’ requirements and needs, planning the ...
Goerger, Simon R.; McGinnis, Michael L.; Darken, Rudolph P. (West Point, New York, United States Military Academy,, 2005-05);The Department of Defense relies heavily on mathematical models and computer simulations to analyze and acquire new weapon systems. Models and simulations help decision-makers understand the differences between systems ...
Goerger, Simon R.; McGinnis, Michael L.; Darken, Rudolph P. (Monterey, California: Naval Postgraduate School., 2005-01);The Department of Defense (DoD) relies heavily on mathematical models and computer simulations to analyze and acquire new weapon systems. Models and simulations help decision makers understand the differences between systems ...