Bøger i Undergraduate Topics in Computer Science serien

The third edition of this textbook has been fully revised and adds material about the SSA form, polymorphism, garbage collection, and pattern matching. It presents techniques for making realistic compilers for simple to intermediate-complexity programming languages. The techniques presented in the book are close to those used in professional compilers, albeit in places slightly simplified for presentation purposes. "Further reading" sections point to material about the full versions of the techniques.All phases required for translating a high-level language to symbolic machine language are covered, and some techniques for optimising code are presented. Type checking and interpretation are also included.Aiming to be neutral with respect to implementation languages, algorithms are mostly presented in pseudo code rather than in any specific language, but suggestions are in many places given for how these can be realised in different language paradigms.Depending on how much of the material from the book is used, it is suitable for both undergraduate and graduate courses for introducing compiler design and implementation.

This accessible textbook supports a foundation or module course on A.I., covering a broad selection of the subdisciplines within this field. It provides study exercises at the end of each chapter, plus examples, definitions, theorems, and illustrations.

In doing so it provides readers with a comprehensive understanding of where software quality fits into the development lifecycle (spoiler: everywhere), and what the key quality assurance activities are. The book focuses on quality assurance in a way that typical, more generic software engineering reference books do not.

After a brief explanation of why modeling is an indispensable part of software development, the authors introduce the individual diagram types of UML (the class and object diagram, the sequence diagram, the state machine diagram, the activity diagram, and the use case diagram), as well as their interrelationships, in a step-by-step manner.

This engaging text presents the fundamental mathematics and modelling techniques for computing systems in a novel and light-hearted way, which can be easily followed by students at the very beginning of their university education.

The coverage spans key concepts adopted from statistics and machine learning, useful techniques for graph analysis and parallel programming, and the practical application of data science for such tasks as building recommender systems or performing sentiment analysis.

Features: provides an introduction to the basic notation and mathematical concepts for describing an image and the key concepts for mapping an image into an image; explains the topologic and geometric basics for analysing image regions and distributions of image values and discusses identifying patterns in an image;

The updated and expanded 4th edition of this book explores mathematical techniques and problem-solving strategies for computer games, animation, virtual reality, CAD and other areas of computer graphics. Includes 120 worked examples and some 270 illustrations.

The other describes how to compile a C subset to real (x86) hardware, as a smooth extension of the previously presented compilers.The examples present several interpreters and compilers for toy languages, including compilers for a small but usable subset of C, abstract machines, a garbage collector, and ML-style polymorphic type inference.

reviews the basic image processing methods for segmenting or enhancing certain features in an image, with a focus on morphology methods for binary images; describes how to change the geometry within an image, how to align two images so that they are as similar as possible, and how to detect lines and paths in images;

Programming language analysis and translation techniques are used in many software application areas.A Practical Approach to Compiler Construction covers the fundamental principles of the subject in an accessible way.

This book provides an undergraduate introduction to analysing data for data science, computer science, and quantitative social science students.

Tracing the story of computing from Babylonian counting boards to smartphones, this inspiring textbook provides a concise overview of the key events in the history of computing, together with discussion exercises to stimulate deeper investigation into this fascinating area.

This classroom-tested textbook provides an accessible introduction to the design, formal modeling, and analysis of distributed computer systems.

Programming Languages is a self-contained approach to the topic, and differentiates between the design, implementation and pragmatic aspects of programming languages overall. The main programming paradigms are presented, in a straightforward way.

This easy-to-follow textbook provides a modern, algorithmic introduction to digital image processing. It concentrates on practical applications and working implementations whilst also presenting important formal details and the necessary mathematics.

This easy-to-follow textbook/reference presents a concise introduction to mathematical analysis from an algorithmic point of view, with a particular focus on applications of analysis and aspects of mathematical modelling.

This textbook describes the approaches used by software engineers to build quality into their software. examines all aspects of the software development process, including project planning and tracking, software lifecycles, software inspections and testing, configuration management, and software quality assurance;