Distributed real-time systems (DRTSs) are used in a wide range of applications, including command and control systems, flight control systems, robotics, patient monitoring systems, and many others. This volume provides an overview of various systematic approaches to the testing and debugging of DRTSs—tasks that typically consume 50% to 70% of a new system's development costs. 
Distributed Real-Time Systems covers both the theoretical and practical issues involved in monitoring, visualization, and analysis methodology for verifying and debugging DRTSs. It describes in detail how to overcome timing verification difficulties and improve system performance and reliability. Complete with many carefully worked-out examples, as well as dozens of illustrations, this timely and accessible work Explains real-world debugging approaches—proposed or tested—using static analysis or dynamic analysis with or without monitoring <ul>
<li>Features step-by-step instructions for design implementation in hardware and software, detecting timing errors and their causes, graphical debugging methods, and more</li> <li>Covers numerous analytical techniques, including timed Petri nets, temporal logic, timed state transition systems, timed process algebra, and synchronous programming languages</li> <li>Makes distributed systems analysis accessible through examples such as a distributed telephone switching system and a fault-tolerant distributed system</li> <li>Reviews many relevant professional papers and current research work</li> </ul>
The joint product of four leaders in the field, Distributed Real-Time Systems is an important text and reference for electrical and software engineers, graduate students, and anyone involved in computer and data processing technology.

Distributed Real-Time Systems: Monitoring, Visualization, Debugging, and Analysis

Computers & Technology

Bi, Yaodong

Yang, Steve J. H.

Smith, Ross A. W.

Tsai, Jeffrey J.P.

Programming

Wiley-Interscience

With the rapid growth of networking and high-computing power, the demand for large-scale and complex software systems has increased dramatically. Many of the software systems support or supplant human control of safety-critical systems such as flight control systems, space shuttle control systems, aircraft avionics control systems, robotics, patient monitoring systems, nuclear power plant control systems, and so on. Failure of safety-critical systems could result in great disasters and loss of human life. Therefore, software used for safety critical systems should preserve high assurance properties. In order to comply with high assurance properties, a safety-critical system often shares resources between multiple concurrently active computing agents and must meet rigid real-time constraints. However, concurrency and timing constraints make the development of a safety-critical system much more error prone and arduous. The correctness of software systems nowadays depends mainly on the work of testing and debugging. Testing and debugging involve the process of de tecting, locating, analyzing, isolating, and correcting suspected faults using the runtime information of a system. However, testing and debugging are not sufficient to prove the correctness of a safety-critical system. In contrast, static analysis is supported by formalisms to specify the system precisely. Formal verification methods are then applied to prove the logical correctness of the system with respect to the specification. Formal verifica tion gives us greater confidence that safety-critical systems meet the desired assurance properties in order to avoid disastrous consequences.

Compositional Verification of Concurrent and Real-Time Systems (The Springer International Series in Engineering and Computer Science, 676)

Juan, Eric Y.T.

Computer Science

Springer

With the rapid growth of networking and high-computing power, the demand for large-scale and complex software systems has increased dramatically. Many of the software systems support or supplant human control of safety-critical systems such as flight control systems, space shuttle control systems, aircraft avionics control systems, robotics, patient monitoring systems, nuclear power plant control systems, and so on. Failure of safety-critical systems could result in great disasters and loss of human life. Therefore, software used for safety­ critical systems should preserve high assurance properties. In order to comply with high assurance properties, a safety-critical system often shares resources between multiple concurrently active computing agents and must meet rigid real-time constraints. However, concurrency and timing constraints make the development of a safety-critical system much more error prone and arduous. The correctness of software systems nowadays depends mainly on the work of testing and debugging. Testing and debugging involve the process of de­ tecting, locating, analyzing, isolating, and correcting suspected faults using the runtime information of a system. However, testing and debugging are not sufficient to prove the correctness of a safety-critical system. In contrast, static analysis is supported by formalisms to specify the system precisely. Formal verification methods are then applied to prove the logical correctness of the system with respect to the specification. Formal verifica­ tion gives us greater confidence that safety-critical systems meet the desired assurance properties in order to avoid disastrous consequences.

Compositional Verification of Concurrent and Real-Time Systems (The Springer International Series in Engineering and Computer Science)

Juan, Eric Y.T. Y. T.

"Machine learning is the study of building computer programs that improve their performance through experience. To meet the challenge of developing and maintaining larger and complex software systems in a dynamic and changing environment, machine learning methods have been playing an increasingly important role in many software development and maintenance tasks. Advances in Machine Learning Applications in Software Engineering provides analysis, characterization, and refinement of software engineering data in terms of machine learning methods. This book depicts applications of several machine learning approaches in software systems development and deployment, and the use of machine learning methods to establish predictive models for software quality. Advances in Machine Learning Applications in Software Engineering also offers readers direction for future work in this emerging research field."

Advances in Machine Learning Applications in Software Engineering

Zhang, Du

Idea Group Publishing

The interplay of artificial intelligence and software engineering has been an interesting and an active area in research institution and industry. This book covers the state of the art in the use of knowledge-based approaches for software specification, design, implementation, testing and debugging. Starting with an introduction to various software engineering paradigms and knowledge-based software systems, the book continues with the discussion of using hybrid knowledge representation as a basis to specify software requirements, to facilitate specification analysis and transformation of real-time distributed software systems. A formal requirements specification language using non-monotonic logic, temporal logic, frames and production systems for new software engineering paradigms (such as rapid prototyping, operational specification and transformational implementation) is also discussed in detail. Examples from switching and other applications are used to illustrate the requirements language. Finally, the development, specification and verification of knowledge-based systems are investigated.

KNOWLEDGE-BASED SOFTWARE DEVELOPMENT FOR REAL-TIME DISTRIBUTED SYSTEMS (Software Engineering and Knowledge Engineering)

Weigert, Thomas J

World Scientific Publishing Company

Parallel processing is a very important technique for improving the performance of various software development and maintenance activities. The purpose of this book is to introduce important techniques for parallel executation of high-level specifications of software systems. These techniques are very useful for the construction, analysis, and transformation of reliable large-scale and complex software systems.

Hybrid Parallel Execution Model for Logic-Based Specification Languages

李, 冰

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