Software reliability: measurement, prediction, application
Software reliability: measurement, prediction, application
Handbook of software reliability engineering
Handbook of software reliability engineering
Predicting Software Reliability
Computer
Reflections on Industry Trends and Experimental Research in Dependability
IEEE Transactions on Dependable and Secure Computing
Predictors of customer perceived software quality
Proceedings of the 27th international conference on Software engineering
Autonomous recovery in componentized Internet applications
Cluster Computing
Microreboot — A technique for cheap recovery
OSDI'04 Proceedings of the 6th conference on Symposium on Opearting Systems Design & Implementation - Volume 6
Architecture Design for Soft Errors
Architecture Design for Soft Errors
Proceedings of the 2010 Conference of the Center for Advanced Studies on Collaborative Research
Post-release reliability growth in software products
ACM Transactions on Software Engineering and Methodology (TOSEM)
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The relationship between software defects and failures is not one-to-one. Some defects remain undis-covered and never cause a failure, but a single defect can cause many failures.Many researchers have offered solutions to this problem, but their approaches typically reflect only the developer view of software reliability: how to predict and prevent the underlying defects. At Hewlett-Packard's Non-Stop Enterprise Division, researchers augment their defect-prevention activities with analyses of what their customers experience: software failures. NED provides customers with a regularly updated suite of hardware and software products for business-critical applications, then tracks the failure rate for each version so that it can measure the customer experience with that update.