Searching Algorithms in Java

Searching Algorithms are designed to check for an element or retrieve an element from any data structure where it is stored. Based on the type of search operation, these algorithms are generally classified into two categories:

1. Sequential Search: In this, the list or array is traversed sequentially and every element is checked. For Example: Linear Search.
2. Interval Search: These algorithms are specifically designed for searching in sorted data-structures. These type of searching algorithms are much more efficient than Linear Search as they repeatedly target the center of the search structure and divide the search space in half. For Example: Binary Search.

Linear Search: The idea is to traverse the given array arr[] and find the index at which the element is present. Below are the steps:

• Let the element to be search be x.
• Start from the leftmost element of arr[] and one by one compare x with each element of arr[].
• If x matches with an element then return that index.
• If x doesn’t match with any of elements then return -1.

#java #searching #algorithms-searching #binary search

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How to Install OpenJDK 11 on CentOS 8

What is OpenJDK?

OpenJDk or Open Java Development Kit is a free, open-source framework of the Java Platform, Standard Edition (or Java SE). It contains the virtual machine, the Java Class Library, and the Java compiler. The difference between the Oracle OpenJDK and Oracle JDK is that OpenJDK is a source code reference point for the open-source model. Simultaneously, the Oracle JDK is a continuation or advanced model of the OpenJDK, which is not open source and requires a license to use.

In this article, we will be installing OpenJDK on Centos 8.

#tutorials #alternatives #centos #centos 8 #configuration #dnf #frameworks #java #java development kit #java ee #java environment variables #java framework #java jdk #java jre #java platform #java sdk #java se #jdk #jre #open java development kit #open source #openjdk #openjdk 11 #openjdk 8 #openjdk runtime environment

Going Beyond Java 8: Local Variable Type Inference (var) - DZone Java

According to some surveys, such as JetBrains’s great survey, Java 8 is currently the most used version of Java, despite being a 2014 release.

What you are reading is one in a series of articles titled ‘Going beyond Java 8,’ inspired by the contents of my book, Java for Aliens. These articles will guide you step-by-step through the most important features introduced to the language, starting from version 9. The aim is to make you aware of how important it is to move forward from Java 8, explaining the enormous advantages that the latest versions of the language offer.

In this article, we will talk about the most important new feature introduced with Java 10. Officially called local variable type inference, this feature is better known as the **introduction of the word **var. Despite the complicated name, it is actually quite a simple feature to use. However, some observations need to be made before we can see the impact that the introduction of the word var has on other pre-existing characteristics.

#java #java 11 #java 10 #java 12 #var #java 14 #java 13 #java 15 #verbosity

Searching Algorithms in Java

Searching Algorithms are designed to check for an element or retrieve an element from any data structure where it is stored. Based on the type of search operation, these algorithms are generally classified into two categories:

1. Sequential Search: In this, the list or array is traversed sequentially and every element is checked. For Example: Linear Search.
2. Interval Search: These algorithms are specifically designed for searching in sorted data-structures. These type of searching algorithms are much more efficient than Linear Search as they repeatedly target the center of the search structure and divide the search space in half. For Example: Binary Search.

Linear Search: The idea is to traverse the given array arr[] and find the index at which the element is present. Below are the steps:

• Let the element to be search be x.
• Start from the leftmost element of arr[] and one by one compare x with each element of arr[].
• If x matches with an element then return that index.
• If x doesn’t match with any of elements then return -1.

#java #searching #algorithms-searching #binary search

SKP's Algorithms and Data Structures

Continuing on the Quick Revision of Important Questions for My Interviews. These Are Good Puzzles or Questions Related to Data Structures.

My Article Series on Algorithms and Data Structures in a Sort of ‘Programming Language Agnostic Way’. Few of the Algorithms and Data Structures in C, Few in C++, and Others in Core Java. Assorted Collection for Learning, Revising, Revisiting, Quick Refresh, and a Quick Glance for Interviews. You May Even Include them Directly for Professional or Open Source Efforts. Have Included Explanation Only for Few of These! Hope these turn out to be Really Helpful as per the Author’s Intention.

Data Structure — Interview Questions

#java #core java #data structures #dijkstra #core java basics #data structure using java #algorithms and data structures #java code examples #linked list in java #circular linked list

Graphs in Java - A* Algorithm

Introduction

A* is a heuristic path searching graph algorithm. This means that given a weighed graph, it outputs the shortest path between two given nodes.

The algorithm is guaranteed to terminate for finite graphs with non-negative edge weights. Additionally, if you manage to ensure certain properties when designing your heuristic it will also always return an almost-optimal solution in a pretty efficient manner.

A heuristic is a method which is constructed to guide us to the optimal solution most of the time, which means we trade in some accuracy for a lot of speed (if the heuristic is well constructed).

In this article, we’ll go over:

• Some characteristics that we aim to have in our heuristic search algorithms in general.
• Show a logical progression from a greedy search to A*.
• Go through the aforementioned conditions which enable A* to solve our problem optimally and efficiently.

Table of Contents:

• Graph Search Characteristics
• Shortfalls of Other Algorithms
• The A* Algorithm in Java
• Cost Function - f(n)
• Move Function - g(n)
• Heuristic Function - h(n)
• Calculating A* Moves
• Pseudocode
• Implementation
• Creating a Good Heuristic Function
• Practical Terrain Example

#java #ai #artificial intelligence #graphs in java - a* algorithm #algorithm #graphs in java