Software reliability: measurement, prediction, application
Software reliability: measurement, prediction, application
Artificial intelligence (2nd ed.)
Artificial intelligence (2nd ed.)
Real-time knowledge-based systems
AI Magazine
Design & analysis of fault tolerant digital systems
Design & analysis of fault tolerant digital systems
Artificial Intelligence
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SAC '93 Proceedings of the 1993 ACM/SIGAPP symposium on Applied computing: states of the art and practice
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Parallelism in Production Systems
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IEEE Transactions on Knowledge and Data Engineering
Parallel Rule Firing in Production Systems
IEEE Transactions on Knowledge and Data Engineering
Performance Evaluation of Rule Grouping on a Real-Time Expert System Architecture
IEEE Transactions on Knowledge and Data Engineering
A logarithmic poisson execution time model for software reliability measurement
ICSE '84 Proceedings of the 7th international conference on Software engineering
Human performance and embedded intelligent technology in safety-critical systems
International Journal of Human-Computer Studies - Special issue: Trust and technology
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Proceedings of the Second Asia-Pacific Symposium on Internetware
A survey of intrusion detection techniques for cyber-physical systems
ACM Computing Surveys (CSUR)
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We define the reliability of a real-time system incorporating AI planning programs as the probability that, for each problem-solving request issued from the environment, the embedded system can successfully plan and execute a response within a specified real-time deadline. A methodology is developed for evaluating the reliability of such systems taking into consideration the fact that, other than program bugs, the intrinsic characteristics of AI planning programs may also cause the embedded system to fail even after all software bugs are removed from the program. The utility of the methodology is demonstrated by applying it to the reliability evaluation of two AI planning algorithms embedded in a real-time multicriteria route-finding system.