Look to this innovative resource for the most comprehensive coverage of software fault tolerance techniques available in a single volume. It offers you a thorough understanding of the operation of critical software fault tolerance techniques and guides you through their design, operation and performance. You get an in-depth discussion on the advantages and disadvantages of specific techniques, so you can decide which ones are best suited for your work. The book examines key programming techniques such as assertions, checkpointing, and atomic actions, and provides design tips and models to assist in the development of critical fault tolerant software that helps ensure dependable performance. From software reliability, recovery, and redundancy... to design and data diverse software fault tolerance techniques, this practical reference provides detailed insight into techniques that can improve the overall dependability of your software.
This book provides guidance on the verification and validation of neural networks/adaptive systems. Considering every process, activity, and task in the lifecycle, it supplies methods and techniques that will help the developer or V&V practitioner be confident that they are supplying an adaptive/neural network system that will perform as intended. Additionally, it is structured to be used as a cross-reference to the IEEE 1012 standard.
Look to this innovative resource for the most-comprehensive coverage of software fault tolerance techniques available in a single volume. It offers you a thorough understanding of the operation of critical software fault tolerance techniques and guides you through their design, operation and performance. You get an in-depth discussion on the advantages and disadvantages of specific techniques, so you can decide which ones are best suited for your work.
This book provides guidance on the verification and validation of neural networks/adaptive systems. Considering every process, activity, and task in the lifecycle, it supplies methods and techniques that will help the developer or V&V practitioner be confident that they are supplying an adaptive/neural network system that will perform as intended. Additionally, it is structured to be used as a cross-reference to the IEEE 1012 standard.
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