Data-oriented programming reduce software complexity
Eliminate the unavoidable complexity of object-oriented designs. The innovative data-oriented programming paradigm makes your systems less complex by making it simpler to access and manipulate data. In Data-Oriented Programming you will learn how to: Separate code from data Represent data with gener...
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| Format: | Online |
| Sprache: | eng |
| Veröffentlicht: |
Shelter Island, New York
Manning Publications
2022
Sebastopol, CA O'Reilly Media Inc. |
| Ausgabe: | [First edition] |
| Schlagworte: | |
| Online Zugang: | https://learning.oreilly.com/library/view/~/9781617298578AU/?ar |
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Tag hinzufügen | Zusammenfassung: | Eliminate the unavoidable complexity of object-oriented designs. The innovative data-oriented programming paradigm makes your systems less complex by making it simpler to access and manipulate data. In Data-Oriented Programming you will learn how to: Separate code from data Represent data with generic data structures Manipulate data with general-purpose functions Manage state without mutating data Control concurrency in highly scalable systems Write data-oriented unit tests Specify the shape of your data Benefit from polymorphism without objects Debug programs without a debugger Data-Oriented Programming is a one-of-a-kind guide that introduces the data-oriented paradigm. This groundbreaking approach represents data with generic immutable data structures. It simplifies state management, eases concurrency, and does away with the common problems you'll find in object-oriented code. The book presents powerful new ideas through conversations, code snippets, and diagrams that help you quickly grok what's great about DOP. Best of all, the paradigm is language-agnostic--you'll learn to write DOP code that can be implemented in JavaScript, Ruby, Python, Clojure, and also in traditional OO languages like Java or C#. About the Technology Code that combines behavior and data, as is common in object-oriented designs, can introduce almost unmanageable complexity for state management. The Data-oriented programming (DOP) paradigm simplifies state management by holding application data in immutable generic data structures and then performing calculations using non-mutating general-purpose functions. Your applications are free of state-related bugs and your code is easier to understand and maintain. About the Book Data-Oriented Programming teaches you to design software using the groundbreaking data-oriented paradigm. You'll put DOP into action to design data models for business entities and implement a library management system that manages state without data mutation. The numerous diagrams, intuitive mind maps, and a unique conversational approach all help you get your head around these exciting new ideas. Every chapter has a lightbulb moment that will change the way you think about programming. What's Inside Separate code from data Represent data with generic data structures Manage state without mutating data Control concurrency in highly scalable systems Write data-oriented unit tests Specify the shape of your data About the Reader For programmers who have experience with a high-level programming language like JavaScript, Java, Python, C#, Clojure, or Ruby. About the Author Yehonathan Sharvit has over twenty years of experience as a software engineer. He blogs, speaks at conferences, and leads Data-oriented programming workshops around the world. Quotes Reach the next level of enlightenment ... Reduce accidental complexity and raise the level of abstraction. - From the Foreword by Michael T. Nygard, author of Release It!: Design and Deploy Production-Ready Software After I saw the examples, I couldn't unsee it. I didn't need a new language; I needed to approach programming differently! - From the Foreword by Ryan Singer, author of Shape Up: Stop Running in Circles and Ship Work that Matters If you have to deal with data in your code, you should know about DOP! - Michael Aydinbas, Exxeta The principles are straightforward and universally applicable. - Seth MacPherson, QuoteFactory. |
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| Beschreibung: | 1 Online-Ressource (1 audio file (09 hr., 31 min.) |
| ISBN: | 9781617298578AU (Sekundärausgabe) |