Dynamic Programming for Coding Interviews: A Bottom-Up approach to problem solving-finelybook

Dynamic Programming for Coding Interviews: A Bottom-Up approach to problem solving

Author: Meenakshi , Kamal Rawat

Publisher finelybook 出版社:‏ ‎ Notion Press

Edition 版本:‏ N/A

Publication Date 出版日期:‏ 2017-01-16

Language 语言: English

Print Length 页数: 142 pages

ISBN-10: 1946556696

ISBN-13: 9781946556691

Book Description

I wanted to compute 80th term of the Fibonacci series. I wrote the rampant recursive function,

int fib(int n){

return (1==n || 2==n) ? 1 : fib(n-1) + fib(n-2);

}

and waited for the result. I wait… and wait… and wait…

With an 8GB RAM and an Intel i5 CPU, why is it taking so long? I terminated the process and tried computing the 40th term. It took about a second. I put a check and was shocked to find that the above recursive function was called 204,668,309 times while computing the 40th term.

More than 200 million times? Is it reporting function calls or scam of some government?

The Dynamic Programming solution computes 100th Fibonacci term in less than fraction of a second, with a single function call, taking linear time and constant extra memory.

A recursive solution, usually, neither pass all test cases in a coding competition, nor does it impress the interviewer in an interview of company like Google, Microsoft, etc.

The most difficult questions asked in competitions and interviews, are from dynamic programming. This book takes Dynamic Programming head-on. It first explain the concepts with simple examples and then deep dives into complex DP problems.

Review

“This is one of the best books on Dynamic Programming.” – Gaurav Sehgal, Engineering Manager, Amazon.

From the Author

DP is one of the most complex problem solving approaches in computer science. At the same time, benefits that DP provide are huge, it usually reduces the time taken from exponential to polynomial. So getting it right is very important.

In most algorithm books, there is one chapter dedicated to DP, that discuss related concepts like optimal substructure, overlapping sub-problems, memoization, etc. And then there are few complex examples to showcase working of DP.

The approach we have followed in this book is that we have one chapter for each concept. And while discussing the concepts, we have taken very simple examples, so that focus remains on the concept. Once the concept is understood, we deep dive into complex problem solving.

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Dynamic Programming for Coding Interviews: A Bottom-Up approach to problem solving