Software Performability From Concepts To Applications

Computers are currently used in a variety of critical applications, including systems for nuclear reactor control, flight control (both aircraft and spacecraft), and air traffic control. Moreover, experience has shown that the dependability of such systems is particularly sensitive to that of its software components, both the system software of the embedded computers and the application software they support. Software Performability: From Concepts to Applications addresses the construction and solution of analytic performability models for critical-application software. The book includes a review of general performability concepts along with notions which are peculiar to software performability. Since fault tolerance is widely recognized as a viable means for improving the dependability of computer system (beyond what can be achieved by fault prevention), the examples considered are fault-tolerant software systems that incorporate particular methods of design diversity and fault recovery. Software Performability: From Concepts to Applications will be of direct benefit to both practitioners and researchers in the area of performance and dependability evaluation, fault-tolerant computing, and dependable systems for critical applications. For practitioners, it supplies a basis for defining combined performance-dependability criteria (in the form of objective functions) that can be used to enhance the performability (performance/dependability) of existing software designs. For those with research interests in model-based evaluation, the book provides an analytic framework and a variety of performability modeling examples in an application context of recognized importance. The material contained in this book will both stimulate future research on related topics and, for teaching purposes, serve as a reference text in courses on computer system evaluation, fault-tolerant computing, and dependable high-performance computer systems.

Includes articles in topic areas such as autonomic computing, operating system architectures, and open source software technologies and applications.

Poor performance is one of the main quality-related shortcomings that cause software projects to fail. Thus, the need to address performance concerns early during the software development process is fully acknowledged, and there is a growing interest in the research and software industry communities towards techniques, methods and tools that permit to manage system performance concerns as an integral part of software engineering. Model-based software performance analysis introduces performance concerns in the scope of software modeling, thus allowing the developer to carry on performance analysis throughout the software lifecycle. With this book, Cortellessa, Di Marco and Inverardi provide the cross-knowledge that allows developers to tackle software performance issues from the very early phases of software development. They explain the basic concepts of performance analysis and describe the most representative methodologies used to annotate and transform software models into performance models. To this end, they go all the way from performance primers through software and performance modeling notations to the latest transformation-based methodologies. As a result, their book is a self-contained reference text on software performance engineering, from which different target groups will benefit: professional software engineers and graduate students in software engineering will learn both basic concepts of performance modeling and new methodologies; while performance specialists will find out how to investigate software performance model building.

As modern society relies on the fault-free operation of complex computing systems, system fault-tolerance has become an indispensable requirement. Therefore, we need mechanisms that guarantee correct service in cases where system components fail, be they software or hardware elements. Redundancy patterns are commonly used, for either redundancy in space or redundancy in time. Wolter’s book details methods of redundancy in time that need to be issued at the right moment. In particular, she addresses the so-called "timeout selection problem", i.e., the question of choosing the right time for different fault-tolerance mechanisms like restart, rejuvenation and checkpointing. Restart indicates the pure system restart, rejuvenation denotes the restart of the operating environment of a task, and checkpointing includes saving the system state periodically and reinitializing the system at the most recent checkpoint upon failure of the system. Her presentation includes a brief introduction to the methods, their detailed stochastic description, and also aspects of their efficient implementation in real-world systems. The book is targeted at researchers and graduate students in system dependability, stochastic modeling and software reliability. Readers will find here an up-to-date overview of the key theoretical results, making this the only comprehensive text on stochastic models for restart-related problems.

The digital age has presented an exponential growth in the amount of data available to individuals looking to draw conclusions based on given or collected information across industries. Challenges associated with the analysis, security, sharing, storage, and visualization of large and complex data sets continue to plague data scientists and analysts alike as traditional data processing applications struggle to adequately manage big data. Big Data: Concepts, Methodologies, Tools, and Applications is a multi-volume compendium of research-based perspectives and solutions within the realm of large-scale and complex data sets. Taking a multidisciplinary approach, this publication presents exhaustive coverage of crucial topics in the field of big data including diverse applications, storage solutions, analysis techniques, and methods for searching and transferring large data sets, in addition to security issues. Emphasizing essential research in the field of data science, this publication is an ideal reference source for data analysts, IT professionals, researchers, and academics.

Because performance is paramount today, this thoroughly updated guide shows you how to test mission-critical applications for scalability and performance before you deploy them—whether it’s to the cloud or a mobile device. You’ll learn the complete testing process lifecycle step-by-step, along with best practices to plan, coordinate, and conduct performance tests on your applications. Set realistic performance testing goals Implement an effective application performance testing strategy Interpret performance test results Cope with different application technologies and architectures Understand the importance of End User Monitoring (EUM) Use automated performance testing tools Test traditional local applications, web applications, and web services Recognize and resolves issues often overlooked in performance tests Written by a consultant with over 15 years’ experience with performance testing, The Art of Application Performance Testing thoroughly explains the pitfalls of an inadequate testing strategy and offers a robust, structured approach for ensuring that your applications perform well and scale effectively when the need arises.

This practical book provides a step-by-step approach to testing mission-critical applications for scalability and performance before they're deployed -- a vital topic to which other books devote one chapter, if that. Businesses today live and die by network applications and web services. Because of the increasing complexity of these programs, and the pressure to deploy them quickly, many professionals don't take the time to ensure that they'll perform well and scale effectively. The Art of Application Performance Testing explains the complete life cycle of the testing process, and demonstrates best practices to help you plan, gain approval for, coordinate, and conduct performance tests on your applications. With this book, you'll learn to: Set realistic performance testing goals Implement an effective application performance testing strategy Interpret performance test results Cope with different application technologies and architectures Use automated performance testing tools Test traditional local applications, web-based applications, and web services (SOAs) Recognize and resolves issues that are often overlooked in performance tests Written by a consultant with 30 years of experience in the IT industry and over 12 years experience with performance testing, this easy-to-read book is illustrated with real-world examples and packed with practical advice. The Art of Application Performance Testing thoroughly explains the pitfalls of an inadequate testing strategy and offers you a robust, structured approach for ensuring that your applications perform well and scale effectively when the need arises. "Ian has maintained a vendor-agnostic methodology beautifully in this material. The metrics and graphs, along with background information provided in his case studies, eloquently convey to the reader, 'Methodology above all, tools at your discretion...' Ian's expertise shines through throughout the entire reading experience."-- Matt St. Onge, Enterprise Solution Architect, HCL Technologies America / Teradyne