Functional Programming library for Java

Elegant puzzles solutions 🖊

All code samples, scripts and more in-depth examples for The Apache Ignite Book. Include Apache Ignite 2.6 or above

Clojure Memoization project

Java memoization library

Sequence Alignment (Needleman–Wunsch Algorithm using Dynamic Programming) for aligning sequences (words, sentences, DNA etc.)

Java Solutions of Dynamic Programming series by Sir Aditya Verma ( i.e God of Dp ) on Youtube

A computational exploration of combinatorial mathematics, aimed at solving the problem of counting all possible paths in an m x n grid using recursive and dynamic programming techniques with memoization for enhanced efficiency.

This Java program calculates Fibonacci numbers using two methods: a simple recursive approach and an optimized dynamic programming approach with memoization. It explores algorithm efficiency, recursive function calls, and the use of memoization to improve computational performance.

This Java program utilizes dynamic programming with memoization to solve the problem of counting the number of distinct ways to climb a staircase, where each step involves choosing between climbing one or two steps.

A short Java-based project that explores the problem of determining if a target sum can be achieved using elements from a given array, employing both a basic recursive approach and an optimized version using memoization

My version of leetcode problem solutions

This Java project focuses on implementing a dynamic programming solution to find the shortest combination of numbers that sum up to a given target sum, using recursion and memoization for efficiency.

A Java implementation of an algorithm that determines if a target string can be constructed by concatenating elements from a given word bank, using recursion and memoization for optimization.

This Java program defines two functions, howSum and improvedHowSum, to find a combination of numbers that add up to a given target sum, using a simple recursive approach and a more efficient recursive approach with memoization, respectively.

This repositiory contains easy to hard level Java codes that one must practice to excel in Technical Interviews.

Faster Mutation Analysis with MeMu

simple learning of Dynamic Programming top-down approach memoization

This is a simple demonstration on how recursive algorithms may not scale when input increase and how we can use dynamic programming (memoization) to improve performance.