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Computer systems can be found almost everywhere in our daily life and they are also extensively used in areas such as defense and finance. Unlike hardware reliability which is a well‐developed area, software reliability is relatively new and is generally more difficult to insure. In order to improve the reliability of a software product, the software has to be tested extensively prior to its release. Software reliability models are commonly used to monitor the testing process and to measure and predict future reliability of the software. Such study is also useful to determine the release time of the software product. During the past three decades there have been many software reliability models proposed and studied. This chapter reviews some of the models and discusses the applications of the models for decision making in software development.

Cloud computing is a recent trend in IT, which has attracted lots of attention. In cloud computing, service reliability and service performance are two important issues. To improve cloud service reliability, fault tolerance techniques such as fault recovery may be used, which in turn has impact on cloud service performance. Such impact deserves detailed research. Although there exist some researches on cloud/grid service reliability and performance, very few of them addressed the issues of fault recovery and its impact on service performance. In this paper, we conduct detailed research on performance evaluation of cloud service considering fault recovery. We consider recovery on both processing nodes and communication links. The commonly adopted assumption of Poisson arrivals of users' service requests is relaxed, and the interarrival times of service requests can take arbitrary probability distribution. The precedence constraints of subtasks are also considered. The probability distribution of service response time is derived, and a numerical example is presented. The proposed cloud performance evaluation models and methods could yield results which are realistic, and thus are of practical value for related decisionmakings in cloud computing.

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As a flexible power source, energy storage has many potential applications in renewable energy generation grid integration, power transmission and distribution, distributed generation, micro grid and ancillary services such as frequency regulation, etc. In this paper, the latest energy storage technology profile is analyzed and summarized, in terms of technology maturity, efficiency, scale, lifespan, cost and applications, taking into consideration their impact on the whole power system, including generation, transmission, distribution and utilization. The application scenarios of energy storage technologies are reviewed and investigated, and global and Chinese potential markets for energy storage applications are described. The challenges of large-scale energy storage application in power systems are presented from the aspect of technical and economic considerations. Meanwhile the development prospect of global energy storage market is forecasted, and application prospect of energy storage is analyzed.

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