Solving the Subset Sum Problem using Dynamic Programming in Java. How to solve Subset Sum Problem using Dynamic Programming in Java. We can use dynamic programming to save time and get best performance.

Subset sum problem is a common interview question asked during technical interviews for the position of a software developer.

It is also a very good question to understand the concept of dynamic programming.### ubset Sum Problem Statement

The problem statement is as follows :

`Given a set of positive integers, and a value sum S, find out if there exists a subset in the array whose sum is equal to given sum S`

An array B is the subset of array A if all the elements of B are present in A. Size of the subset has to be less than or equal to the parent array.

Let’s take an example :

`A = { 3, 2, 7, 1}, Sum = 6`

`Output: True`

In this case the subarray {3, 2, 1} gives the sum 6. Hence we output true.

Simpliv is aware that the animated, visual and spatial way is the best means to learn data structures and algorithms. This is why Simpliv’s course on data structures and algorithms is visual, adding fun and interactivity into your learning.

What is OpenJDK? OpenJDk or Open Java Development Kit is a free, open-source framework of the Java Platform, Standard Edition (or Java SE).

This particular concept is identified as one of the most important concepts in software engineering, and that became a primary checkpoint for most of the top-level companies.

Understanding concepts such as algorithmic complexity and proper use of data structures will enable you to write more optimal code. I will list a few tools you will have under your tool-belt after taking a typical algorithms course.

In this tutorial, we will cover everything you need to know to implement max heaps in java from scratch. A max heap is a complete binary tree in which the value of a node is greater than or equal to the values of its children. Max Heap data structure is useful for sorting data using heap sort.