An Expert Guide to Software Performance Optimization From mobile and cloud apps to video games to driverless vehicle control, more and more software is time-constrained: It must deliver reliable results seamlessly, consistently, and virtually instantaneously. If it doesn't, customers are unhappy--and sometimes lives are put at risk. When complex software underperforms or fails, software engineers need to identify and address the root causes. This is difficult and, historically, few tools have been available to help. In Understanding Software Dynamics, performance expert Richard L. Sites tackles the problem head on, offering expert methods and advanced tools for understanding complex, time-constrained software dynamics, improving reliability and troubleshooting challenging performance problems. Sites draws on several decades of experience pioneering software performance optimization, as well as extensive experience teaching graduate-level developers. He introduces principles and techniques for use in any environment, from embedded devices to datacenters, illuminating them with examples based on x86 or ARM processors running Linux and linked by Ethernet. He also guides readers through building and applying a powerful, new, extremely low-overhead open-source software tool, KUtrace, to precisely trace executions on every CPU core. Using insights gleaned from this tool, readers can apply nuanced solutions--not merely brute-force techniques such as turning off caches or cores. Measure and address issues associated with CPUs, memory, disk/SSD, networks, and their interactions Fix programs that are always too slow, and those that sometimes lag for no apparent reason Design useful observability, logging, and time-stamping capabilities into your code Reason more effectively about performance data to see why reality differs from expectations Identify problems such as excess execution, slow instruction execution, waiting for resources, and software locks Understanding Software Dynamics will be valuable to experienced software professionals, including application and OS developers, hardware and system architects, real-time system designers, and game developers, as well as advanced students. Register your book for convenient access to downloads, updates, and/or corrections as they become available. See inside book for details.

Presenting a fresh look at process control, this new text demonstrates state-space approach shown in parallel with the traditional approach to explain the strategies used in industry today. Modern time-domain and traditional transform-domain methods are integrated throughout and explain the advantages and limitations of each approach; the fundamental theoretical concepts and methods of process control are applied to practical problems. To ensure understanding of the mathematical calculations involved, MATLAB® is included for numeric calculations and MAPLE for symbolic calculations, with the math behind every method carefully explained so that students develop a clear understanding of how and why the software tools work. Written for a one-semester course with optional advanced-level material, features include solved examples, cases that include a number of chemical reactor examples, chapter summaries, key terms, and concepts, as well as over 240 end-of-chapter problems, focused computational exercises and solutions for instructors.

Provides a candid look at the ups and downs of software development, providing tips on how to ship great software on. The book is divided into five sections that chart the progress from initial design to successful product. The Adobe Reader format of this title is not suitable for use on the Pocket PC or Palm OS versions of Adobe Reader.

This book is designed for professionals and students in software engineering or information technology who are interested in understanding the dynamics of software development in order to assess and optimize their own process strategies. It explains how simulation of interrelated technical and social factors can provide a means for organizations to vastly improve their processes. It is structured for readers to approach the subject from different perspectives, and includes descriptive summaries of the best research and applications.

While modern project management systems support teams during planning and development activities, primarily through performance-related process information, the equally relevant human factors are often insufficiently considered for explaining team dynamics (e.g., the affect of moods in teams). However, understanding team behavioral patterns are crucial for the accurate planning and steady execution of development tasks throughout an ongoing project. A computer-aided feedback concept is described, unifying interdisciplinary foundations and methods from the software engineering, data science, organizational, and social psychology fields for disclosing team dynamics in agile software projects. The concept covers the systematic capture of sociotechnical data combined with descriptive, predictive, and exploratory model-based methods that support understanding behavioural changes during the development process. Design science from information systems research is used in academic and industrial case studies to conceptualize and operationalize the feedback methods into a practical Jira plugin. A concluding evaluation through an action research method in two industrial software projects results in quantitative and qualitative findings regarding the feedback utilization and utility during agile development processes (e.g., team communication changes related to accomplished performances). The case studies underscore the practical relevance for systematic feedback and the need to better understand human factors in software projects.

Symbolic dynamics is a mature yet rapidly developing area of dynamical systems. It has established strong connections with many areas, including linear algebra, graph theory, probability, group theory, and the theory of computation, as well as data storage, statistical mechanics, and $C^*$-algebras. This Second Edition maintains the introductory character of the original 1995 edition as a general textbook on symbolic dynamics and its applications to coding. It is written at an elementary level and aimed at students, well-established researchers, and experts in mathematics, electrical engineering, and computer science. Topics are carefully developed and motivated with many illustrative examples. There are more than 500 exercises to test the reader's understanding. In addition to a chapter in the First Edition on advanced topics and a comprehensive bibliography, the Second Edition includes a detailed Addendum, with companion bibliography, describing major developments and new research directions since publication of the First Edition.

Understanding Complex Ecosystem Dynamics: A Systems and Engineering Perspective takes a fresh, interdisciplinary perspective on complex system dynamics, beginning with a discussion of relevant systems and engineering skills and practices, including an explanation of the systems approach and its major elements. From this perspective, the author formulates an ecosystem dynamics functionality-based framework to guide ecological investigations. Next, because complex system theory (across many subject matter areas) is crucial to the work of this book, relevant network theory, nonlinear dynamics theory, cellular automata theory, and roughness (fractal) theory is covered in some detail. This material serves as an important resource as the book proceeds. In the context of all of the foregoing discussion and investigation, a view of the characteristics of ecological network dynamics is constructed. This view, in turn, is the basis for the central hypothesis of the book, i.e., ecological networks are ever-changing networks with propagation dynamics that are punctuated, local-to-global, and perhaps most importantly fractal. To analyze and fully test this hypothesis, an innovative ecological network dynamics model is defined, designed, and developed. The modeling approach, which seeks to emulate features of real-world ecological networks, does not make a priori assumptions about ecological network dynamics, but rather lets the dynamics develop as the model simulation runs. Model analysis results corroborate the central hypothesis. Additional important insights and principles are suggested by the model analysis results and by the other supporting investigations of this book – and can serve as a basis for going-forward complex system dynamics research, not only for ecological systems but for complex systems in general. - Provides a fresh interdisciplinary perspective, offers a broad integrated development, and contains many new ideas - Clearly explains the elements of the systems approach and applies them throughout the book - Takes on the challenging and open issues of complex system network dynamics - Develops and utilizes a new, innovative ecosystem dynamics modeling approach - Contains over 135 graphic illustrations to help the reader visualize and understand important concepts