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Learning Functional Data Structures and Algorithms

You're reading from   Learning Functional Data Structures and Algorithms Learn functional data structures and algorithms for your applications and bring their benefits to your work now

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Product type Paperback
Published in Feb 2017
Publisher Packt
ISBN-13 9781785888731
Length 318 pages
Edition 1st Edition
Languages
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Authors (2):
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Raju Kumar Mishra Raju Kumar Mishra
Author Profile Icon Raju Kumar Mishra
Raju Kumar Mishra
Atul S. Khot Atul S. Khot
Author Profile Icon Atul S. Khot
Atul S. Khot
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Table of Contents (14) Chapters Close

Preface 1. Why Functional Programming? 2. Building Blocks FREE CHAPTER 3. Lists 4. Binary Trees 5. More List Algorithms 6. Graph Algorithms 7. Random Access Lists 8. Queues 9. Streams, Laziness, and Algorithms 10. Being Lazy - Queues and Deques 11. Red-Black Trees 12. Binomial Heaps 13. Sorting

Controlling state changes

Let me share a debugging nightmare with you. We had a multithreaded system written in C++. The state was carefully shared, with concurrent access protected by explicit mutex locks. A team member--ugh--forgot to acquire a lock on a shared data structure and all hell broke loose.

The team member was a senior programmer; he knew what he was doing. He just forgot the locking. It took us some nights full of stack trace to figure out what the issue was.

Writing concurrent programs using shared memory communication can very easily go wrong.

In the book Java Concurrency in Practice, the authors show us how easy it is for internal mutable state to escape (http://jcip.net/ ). Tools, such as Eclipse, make it easy to generate getters, and before you know, a reference escapes and all hell could break loose.

The encapsulation is fine. The mutable state, in this case an array, could be inadvertently exposed. For example, using a getter method, the array reference can be obtained by the outside world. Two or more threads could then try mutating it and everything goes for a toss:

Controlling state changes

We cannot ignore concurrency anymore. Program design is going to be ruled by the machine design; having a multicore machine is the norm.

It is too hard to make sure the state changes are controlled. If instead, we know that a data structure does not change once it is created, reasoning becomes far easier. There is no need to acquire/release locks as a shared state never changes.

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