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Domain Modeling-based Software Engineering
Many approaches have been proposed to enhance software productivity and reliability. These approaches typically fall into three categories: the engineering approach, the formal approach, and the knowledge-based approach. The optimal gain in software productivity cannot be obtained if one relies on only one of these approaches. Thus, the integration of different approaches has also become a major area of research.
No approach can be said to be perfect if it fails to satisfy the following two criteria. Firstly, a good approach should support the full life cycle of software development. Secondly, a good approach should support the development of large-scale software for real use in many application domains. Such an approach can be referred to as a five-in-one approach.
The authors of this book have, for the past eight years, conducted research in knowledge-based software engineering, of which the final goal is to develop a paradigm for software engineering which not only integrates the three approaches mentioned above, but also fulfils the two criteria on which the five-in-one approach is based. Domain Modeling- Based Software Engineering: A Formal Approach explores the results of this research.
Domain Modeling-Based Software Engineering: A Formal Approach will be useful to researchers of knowledge-based software engineering, students and instructors of computer science, and software engineers who are working on large-scale projects of software development and want to use knowledge-based development methods in their work.
Python For Software Design
Python for Software Design is a concise introduction to software design using the Python programming language.
Intended for people with no programming experience, this book starts with the most basic concepts and gradually adds new material. Some of the ideas students find most challenging, like recursion and object-oriented programming, are divided into a sequence of smaller steps and introduced over the course of several chapters. The focus is on the programming process, with special emphasis on debugging.
The book includes a wide range of exercises, from short examples to substantial projects, so that students have ample opportunity to practice each new concept.
About the Author
Allen B. Downey, Ph.D., is an Associate Professor of Computer Science at the Olin College of Engineering in Needham, Massachusetts. He has taught at Wellesley College, Colby College, and UC Berkeley. He has a doctorate in computer science from UC Berkeley and a Master's degree from MIT. Dr Downey is the author of a previous version of this book, titled How to Think Like a Computer Scientist : Learning with Python , which he self-published in 2001.
Software Testing Industrialization
This book gives a realistic overview of model-based testing, its values and prerequisites for success when deploying the approach in a software testing industrialization perspective. The text shows how to save time and lower costs while raising quality in the phases of system testing, acceptance testing and, more generally, all functional testing phases.</p> <p> Key features:</p> <ul> <li>Details the key role of model-based testing to ensure continuity in the software testing industrialization process, describing how each step could be implemented. </li> <li>Uses detailed examples – the actiTIME application – to teach techniques of model-based testing, including modeling guidelines, test generation strategies and automated test execution. </li> <li>Offers a companion website which makes available machine-readable versions of case studies and examples used in the book, as well as presentation slides. </li> </ul>
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