After completing this self-contained course on server-based Internet applications software that grew out of an MIT course, students who start with only the knowledge of how to write and debug a computer program will have learned how to build sophisticated Web-based applications.
"This book presents current, effective software engineering methods for the design and development of modern Web-based applications"--Provided by publisher.
Software engineering is playing an increasingly significant role in computing and informatics, necessitated by the complexities inherent in large-scale software development. To deal with these difficulties, the conventional life-cycle approaches to software engineering are now giving way to the "process system" approach, encompassing development methods, infrastructure, organization, and management. Until now, however, no book fully addressed process-based software engineering or set forth a fundamental theory and framework of software engineering processes. Software Engineering Processes: Principles and Applications does just that. Within a unified framework, this book presents a comparative analysis of current process models and formally describes their algorithms. It systematically enables comparison between current models, avoidance of ambiguity in application, and simplification of manipulation for practitioners. The authors address a broad range of topics within process-based software engineering and the fundamental theories and philosophies behind them. They develop a software engineering process reference model (SEPRM) to show how to solve the problems of different process domains, orientations, structures, taxonomies, and methods. They derive a set of process benchmarks-based on a series of international surveys-that support validation of the SEPRM model. Based on their SEPRM model and the unified process theory, they demonstrate that current process models can be integrated and their assessment results can be transformed between each other. Software development is no longer just a black art or laboratory activity. It is an industrialized process that requires the skills not just of programmers, but of organization and project managers and quality assurance specialists. Software Engineering Processes: Principles and Applications is the key to understanding, using, and improving upon effective engineering procedures for software development.
Bioinformatics Software Engineering: Delivering Effective Applications will be useful to anyone who wants to understand how successful software can be developed in a rapidly changing environment. A handbook, not a textbook, it is not tied to any particular operating system, platform, language, or methodology. Instead it focuses on principles and practices that have been proven in the real world. It is pragmatic, emphasizing the importance of what the author calls Adaptive Programming - doing what works in your situation, and it is concise, covering the whole software development lifecycle in one slim volume. At each stage, it describes common pitfalls, explains how these can be avoided, and suggests simple techniques which make it easier to deliver better solutions. "Well thought-out ... addresses many of the key issues facing developers of bioinformatics software." (Simon Dear, Director, UK Technology and Development, Bioinformatics Engineering and Integration, Genetics Research, GlaxoSmithKline) Here are some examples from the book itself. On software development: “Writing software properly involves talking to people – often lots of people – and plenty of non-coding work on your part. It requires the ability to dream up new solutions to problems so complicated that they are hard to describe.” From description to specification: “Look for verbs – action words, such as ‘does’, ‘is’ and ‘views’. Identify nouns – naming words, like ‘user’, ‘home’ and ‘sequence’. List the adjectives – describing words, for example ‘quick’, ‘simple’ or ‘precise’. The verbs are the functions that must be provided by your application. The nouns define the parameters to those functions, and the adjectives specify the constraint conditions under which your program must operate.” On how to start writing software: “Handle errors. Take in data. Show output. Get going!” On testing: “It may not be physically possible to test every potential combination of situations that could occur as users interact with a program. But one thing that can be done is to test an application at the agreed extremes of its capability: the maximum number of simultaneous users it has to support, the minimum system configuration it must run on, the lowest communication speed it must cope with, and the most complex operations it must perform. If your program can cope with conditions at the edge of its performance envelope, it is less likely to encounter difficulties in dealing with less challenging situations.” On showing early versions of software to users: “It can be hard explaining the software development process to people who are unfamiliar with it. Code that to you is nearly finished is simply not working to them, and seeing their dream in bits on the workbench can be disappointing to customers, especially when they were expecting to be able to take it for a test drive.” On bugs: “If your users find a genuinely reproducible bug in production code, apologize, fix it fast, and then fix the system that allowed it through. And tell your customers what you are doing, and why, so they will be confident that it will not happen again. Everybody makes mistakes. Don’t make the same ones twice.” And one last thought on successful software development: "You have to be a detective, following up clues and examining evidence to discover what has gone wrong and why. And you have to be a politician, understanding what people want, both in public and in private, and how this is likely to affect what you are trying to do. This book cannot teach you how to do all of that, but it can help."
By way of this book, Norman Schneidewind has officially bridged the gap between the two disparate fields. Filled with many real-world examples drawn from industry and government, Systems and Software Engineering with Applications provides a new perspective for systems and software engineers to consider when developing optimal solutions. This unique approach to looking at the big picture when addressing system and software reliability can benefit students, practitioners, and researchers. Excel spreadsheets noted in the book are available on CD-Rom for an interactive learning experience. Read Systems and Software Engineering with Applications and learn how to: Quantitatively analyze the performance, reliability, maintainability, and availability of software in relation to the total system - Understand the availability of software in relation to the total system - Use standards as part of the solution - Evaluate and mitigate the risk of deploying software-based systems - Apply models dealing with the optimization of systems through quantitative examples provided to help you understand and interpret model results Some of the areas the book focuses on include: - Systems and software models, methods, tools, and standards - Quantitative methods to ensure reliability - Software reliability and metrics tools - Integrating testing with reliability - Cyber security prediction models - Ergonomics and safety in the workplace - Scheduling and cost control in systems and software.
"This book provides analysis, characterization and refinement of software engineering data in terms of machine learning methods. It 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 while offering readers suggestions by proposing future work in this emerging research field"--Provided by publisher.
Machine learning deals with the issue of how to build computer programs that improve their performance at some tasks through experience. Machine learning algorithms have proven to be of great practical value in a variety of application domains. Not surprisingly, the field of software engineering turns out to be a fertile ground where many software development and maintenance tasks could be formulated as learning problems and approached in terms of learning algorithms. This book deals with the subject of machine learning applications in software engineering. It provides an overview of machine learning, summarizes the state-of-the-practice in this niche area, gives a classification of the existing work, and offers some application guidelines. Also included in the book is a collection of previously published papers in this research area.
Professionals in the interdisciplinary field of computer science focus on the design, operation, and maintenance of computational systems and software. Methodologies and tools of engineering are utilized alongside computer applications to develop efficient and precise information databases. Computer Systems and Software Engineering: Concepts, Methodologies, Tools, and Applications is a comprehensive reference source for the latest scholarly material on trends, techniques, and uses of various technology applications and examines the benefits and challenges of these computational developments. Highlighting a range of pertinent topics such as utility computing, computer security, and information systems applications, this multi-volume book is ideally designed for academicians, researchers, students, web designers, software developers, and practitioners interested in computer systems and software engineering.
This book constitutes the first part of refereed proceedings of the 5th Computational Methods in Systems and Software 2021 (CoMeSySo 2021). The CoMeSySo 2021 Conference is breaking the barriers, being held online. CoMeSySo 2021 intends to provide an international forum for the discussion of the latest high-quality research results. The software engineering, computer science, and artificial intelligence are crucial topics for the research within an intelligent systems problem domain.
This book identifies challenges and opportunities in the development and implementation of software that contain significant statistical content. While emphasizing the relevance of using rigorous statistical and probabilistic techniques in software engineering contexts, it presents opportunities for further research in the statistical sciences and their applications to software engineering. It is intended to motivate and attract new researchers from statistics and the mathematical sciences to attack relevant and pressing problems in the software engineering setting. It describes the "big picture," as this approach provides the context in which statistical methods must be developed. The book's survey nature is directed at the mathematical sciences audience, but software engineers should also find the statistical emphasis refreshing and stimulating. It is hoped that the book will have the effect of seeding the field of statistical software engineering by its indication of opportunities where statistical thinking can help to increase understanding, productivity, and quality of software and software production.