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Object-Oriented Software Engineering Using UML Patterns and Java
Shows students how to use both the principles of software engineering and the practices of various object-oriented tools, processes, and products. Using a step-by-step case study to illustrate the concepts and topics in each chapter, Bruegge and Dutoit emphasize learning object-oriented software engineer through practical experience: students can apply the techniques learned in class by implementing a real-world software project. The third edition addresses new trends, in particular agile project management (Chapter 14 Project Management) and agile methodologies (Chapter 16 Methodologies).
Microsoft Visual C# Step by Step
Guide to Microsoft Visual C# fundamentals with Visual Studio. Expand your expertiseand teach yourself the fundamentals of programming with the latest version of Visual C# with Visual Studio. If you are an experienced software developer, you'll get all the guidance, exercises, and code you need to start building responsive, scalable, cloud-connected applications that can run almost anywhere. Discover how to: Quickly start creating Visual C# code and projects with Visual Studio Work with variables, operators, expressions, methods, and program flow Build more robust apps with error, exception, and resource management Spot problems fast with the Visual Studio debugger Make the most of improvements to C# methods, parameters, and switch statements Master the C# object model, and create your own functional data structures Leverage advanced properties, indexers, generics, and collection classes Create Windows 10 apps that share data, collaborate, and use cloud services Integrate Cortana to voice-enable your applications Perform complex queries over object collections with LINQ
Introduction to Algorithms
Combines rigor and comprehensiveness. It covers a broad range of algorithms in depth, yet makes their design and analysis accessible to all levels of readers, with self-contained chapters and algorithms in pseudocode. Since the publication of the first edition, Introduction to Algorithms has become the leading algorithms text in universities worldwide as well as the standard reference for professionals. This fourth edition has been updated throughout.
Introduction à SCILAB
Ce livre est organisé en deux parties. La première partie est consacrée au langage Scilab et à son environnement. Dans la seconde partie, les fonctionnalités des grands domaines d'utilisation du calcul numérique sont décrites et illustrées par des exemples: calcul matriciel, simulation, optimisation, résolution d'équations, statistiques.
Hands-On Software Architecture with Java - Learn key architectural techniques and strategies to design efficient and elegant Java applications
Starts with the fundamentals of architecture and takes you through the basic components of application architecture. You'll cover the different types of software architectural patterns and application integration patterns and learn about their most widespread implementation in Java. You'll then explore cloud-native architectures and best practices for enhancing existing applications to better suit a cloud-enabled world. Later, the book highlights some cross-cutting concerns and the importance of monitoring and tracing for planning the evolution of the software, foreseeing predictable maintenance, and troubleshooting. The book concludes with an analysis of the current status of software architectures in Java programming and offers insights into transforming your architecture to reduce technical debt.
Fluent Python : Clear, Concise, and Effective Programming
You’ll learn how to write effective, modern Python 3 code by leveraging its best ideas. Don’t waste time bending Python to fit patterns you learned in other languages. Discover and apply idiomatic Python 3 features beyond your past experience. Author Luciano Ramalho guides you through Python’s core language features and libraries and teaches you how to make your code shorter, faster, and more readable.
DevOps Tools for Java Developers : Best Practices from Source Code to Production Containers
Explore software lifecycle best practices Use DevSecOps methodologies to facilitate software development and delivery Understand the business value of DevSecOps best practices Manage and secure software dependencies Develop and deploy applications using containers and cloud native technologies Manage and administrate source control repositories and development processes Use automation to set up and administer build pipelines Identify common deployment patterns and antipatterns Maintain and monitor software after deployment
Data structures and algorithm : Analysis in C++
An advanced algorithms book that bridges the gap between traditional CS2 and Algorithms Analysis courses. As the speed and power of computers increases, so does the need for effective programming and algorithm analysis. By approaching these skills in tandem, Mark Allen Weiss teaches readers to develop well-constructed, maximally efficient programs using the C++ programming language
Data structure and algorithms using C++ : A practical implementation
Intended to flow from the basic concepts of C++ to technicalities of the programming language, its approach and debugging. The chapters of the book flow with the formulation of the problem, it's designing, finding the step-by-step solution procedure along with its compilation, debugging and execution with the output. Keeping in mind the learner’s sentiments and requirements, the exemplary programs are narrated with a simple approach so that it can lead to creation of good programs that not only executes properly to give the output, but also enables the learners to incorporate programming skills in them. The style of writing a program using a programming language is also emphasized by introducing the inclusion of comments wherever necessary to encourage writing more readable and well commented programs. As practice makes perfect, each chapter is also enriched with practice exercise questions so as to build the confidence of writing the programs for learners.
Data Algorithms with Spark
Apache Spark's speed, ease of use, sophisticated analytics, and multilanguage support makes practical knowledge of this cluster-computing framework a required skill for data engineers and data scientists. With this hands-on guide, anyone looking for an introduction to Spark will learn practical algorithms and examples using PySpark. you will: Learn how to select Spark transformations for optimized solutions Explore powerful transformations and reductions including reduceByKey(), combineByKey(), and mapPartitions() Understand data partitioning for optimized queries Build and apply a model using PySpark design patterns Apply motif-finding algorithms to graph data Analyze graph data by using the GraphFrames API Apply PySpark algorithms to clinical and genomics data Learn how to use and apply feature engineering in ML algorithms Understand and use practical and pragmatic data design patterns
Command-Line Rust : A Project-Based Primer for Writing Rust CLIs
Rather than focusing on the language as a whole, this guide teaches Rust using a single small, complete, focused program in each chapter. Author Ken Youens-Clark shows you how to start, write, and test each of these programs to create a finished product. You'll learn how to handle errors in Rust, read and write files, and use regular expressions, Rust types, structs, and more.
Machine Learning Algorithms Using Python Programming
Presents the key concepts of Machine Learning which includes Python concepts and Interpreter, Foundation of Machine Learning, Data Pre-processing, Supervised Machine Learning, Unsupervised Machine Learning, Reinforcement Learning, Kernel Machine, Design and analysis of Machine Learning experiment and Data visualization. The theoretical concepts along with coding implementation are covered. This book aims to pursue a middle ground between a theoretical textbook and one that focuses on applications. The book concentrates on the important ideas in machine learning.
Learning network programming with Java
Learn to deliver superior server-to-server communication through the networking channels / Gain expertise of the networking features of your own applications to support various network architectures such as client/server and peer-to-peer Explore the issues that impact scalability, affect security, and allow applications to work in a heterogeneous environment
JavaScript data structures and algorithms : An Introduction to understanding and implementing core data structure and algorithm fundamentals
Combines clear explanations of data structure and algorithm theory with practical code samples, examples and exercises, all specifically relevant to JavaScript Provides background information on object-oriented programming and native JavaScript concepts to help understand how everything fits together Illustrates how these theoretical computer science concepts ties back to practical applications in software engineering
Java Illuminated ; 5th ed.
Provides learners with an interactive, user-friendly approach to learning the Java programming language. Comprehensive but accessible, the text takes a progressive approach to object-oriented programming, allowing students to build on established skills to develop new and increasingly complex classes. Java Illuminated follows an activity-based active learning approach that ensures student engagement and interest.
Java Design Patterns : A Hands-On Experience with Real-World Examples
Covers classical design patterns with the latest editions of Java and Eclipse Includes implementation of the Java design patterns in real-world applications Each chapter has a Q&A section to help you understand the pros and cons of each design pattern
Java : how to program. Late objects : Introducing Jshell
Introduction to Computers, the Internet and Java / Introduction to Java Applications; Input/Output and Operators / Control Statements: Part 1; Assignment, ++ and Operators / Control Statements: Part 2; Logical Operators / Methods / Arrays and ArrayLists / Introduction to Classes and Objects / Classes and Objects: A Deeper Look / Object-Oriented Programming: Inheritance / Object-Oriented Programming: Polymorphism and Interfaces / Exception Handling: A Deeper Look / JavaFX Graphical User Interfaces / JavaFX GUI / Strings, Characters and Regular Expressions / Files, Input/Output Streams, NIO and XML Serialization / Generic Collections / Lambdas and Streams / Recursion / Searching, Sorting and Big O / Generic Classes and Methods: A Deeper Look / Custom Generic Data Structures / JavaFX Graphics and Multimedia / Concurrency / Accessing Databases with JDBC / Introduction to JShell: Java 9's REPL for Interactive Java
Competitive Programming in Python : 128 Algorithms to Develop your Coding Skills
Learn all the algorithmic techniques and programming skills you need from two experienced coaches, problem setters, and jurors for coding competitions. The authors highlight the versatility of each algorithm by considering a variety of problems and show how to implement algorithms in simple and efficient code. What to expect: * Master 128 algorithms in Python. * Discover the right way to tackle a problem and quickly implement a solution of low complexity.
C# 10 in a Nutshell : The Definitive Reference
When you have questions about C# 10.0 or .NET 6, this guide has the answers you need. C# is a language of unusual flexibility and breadth, but with its continual growth, there's so much more to learn. In the tradition of O'Reilly's Nutshell guides, this thoroughly updated edition is simply the best one-volume reference to the C# language available today. Organized around concepts and use cases, this comprehensive and complete reference provides intermediate and advanced programmers with a concise map of C# and .NET that also plumbs significant depths
Beyond the Worst-Case Analysis of Algorithms
There are no silver bullets in algorithm design, and no single algorithmic idea is powerful and flexible enough to solve every computational problem. Nor are there silver bullets in algorithm analysis, as the most enlightening method for analyzing an algorithm often depends on the problem and the application. However, typical algorithms courses rely almost entirely on a single analysis framework, that of worst-case analysis, wherein an algorithm is assessed by its worst performance on any input of a given size. The purpose of this book is to popularize several alternatives to worst-case analysis and their most notable algorithmic applications, from clustering to linear programming to neural network training. Forty leading researchers have contributed introductions to different facets of this field, emphasizing the most important models and results, many of which can be taught in lectures to beginning graduate students in theoretical computer science and machine learning.
