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Arun Pandey

DZone Core CORE

|Accredited Investor| Enterprise Coach| Sr. TechLead| Topcoder Ambassador|

New York, US

Joined Mar 2016

About

Arun Pandey is a distinguished technologist, Enterprise Coach, and Accredited Investor with a prolific career spanning multiple cutting-edge technologies. With hands-on expertise in Java, Python, Blockchain, Artificial Intelligence (AI), and Machine Learning, Arun has consistently demonstrated his ability to leverage these technologies to drive innovation and business transformation. Arun holds a Master’s degree in Software Technology and boasts an impressive array of credentials from some of the world's most prestigious institutions, including Harvard University, University of Maryland, Rochester Institute of Technology (RIT), Rice Business School, University of Washington, ICAgile, and Scrum Alliance. His diverse educational background underscores his commitment to continuous learning and professional development.

Stats

Reputation: 3014
Pageviews: 2.5M
Articles: 55
Comments: 16

Expertise

Team Management Expertise Icon

Team Management

  • Articles
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Articles

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Building an IoT-based Waste Management System: A Software Architect's Guide
Explore how IoT waste management optimizes collection, reduces costs, and enhances sustainability using smart bins, mobile apps, and analytics.
August 5, 2024
· 5,249 Views · 2 Likes
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Self-Compassion in Tech Teams: Building Strength and Teamwork
Embrace self-compassion in technical teams to enhance emotional resilience, foster collaboration, and promote a supportive, innovative, and successful work culture.
July 31, 2024
· 6,110 Views · 3 Likes
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Microsoft Teams for Developers: Enhancing Communication With Call Initiating and Recording
Learn how Microsoft Teams empowers developers to create seamless communication with smart calling solutions, APIs, and third-party integrations.
April 22, 2024
· 3,696 Views · 3 Likes
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Conflict Management in Technology Teams: Insights From Google's Project Aristotle
Explore conflict management strategies inspired by Google's Project Aristotle with additional data points, and a use case to illustrate real-life scenarios.
April 8, 2024
· 4,809 Views · 4 Likes
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Game Theory in Blockchain: A Developer's Guide With Java Example
Enhance blockchain stability, security, and efficiency with game theory. Shape consensus mechanisms, incentives, and governance in a Java-based PoS simulation.
April 4, 2024
· 3,259 Views · 2 Likes
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Comprehensive Proxy Server Guide: Types, Applications, and Developer Examples
Proxy servers offer improved performance, security, and privacy. Here, learn about proxy server types including forward, reverse, transparent, SOCKS, and more.
April 3, 2024
· 8,118 Views · 3 Likes
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Snowflake Micro-Partitioning: Technical Insights, Examples, and Advanced Developer Guide
Snowflake micro-partitioning boosts query performance, scalability, and storage efficiency with advanced developer tactics.
April 2, 2024
· 8,828 Views · 2 Likes
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A Developer's Guide to Database Sharding With MongoDB
Database sharding improves performance by distributing data across multiple shards. Use MongoDB to easily implement various sharding strategies.
March 9, 2024
· 7,717 Views · 4 Likes
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Real-Time Communication Protocols: A Developer's Guide With JavaScript
Explore WebSocket for low latency communication, WebRTC for peer-to-peer streaming, and MQTT for IoT while implementing provided JavaScript examples.
February 29, 2024
· 11,002 Views · 5 Likes
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Architectural Insights: Designing Efficient Multi-Layered Caching With Instagram Example
Explore the concept of multi-layered caching from both architectural and development perspectives, focusing on real-world applications like Instagram.
February 27, 2024
· 15,652 Views · 5 Likes
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Microsoft Research Lab Structure: A Data-Driven Approach to Tech Leadership and Innovation
Microsoft Research's unique lab structure is designed to foster tech leadership and innovation. Let's explore its approach to autonomy, collaboration, and diversity.
February 12, 2024
· 5,176 Views · 2 Likes
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Advanced Brain-Computer Interfaces With Java
This article guides Java developers on building a brain-computer interface application using NeuroSky's MindWave Mobile headset.
February 11, 2024
· 9,665 Views · 6 Likes
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Building Your Own Automatic Garbage Collector: A Guide for Developers
Implementing a custom Java garbage collector requires deep JVM knowledge, exploration of OpenJDK, and understanding memory management principles.
January 14, 2024
· 15,321 Views · 3 Likes
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Advanced Content Prioritization Techniques for Web Developers
Optimize web performance using content prioritization, code splitting, image optimization, resource hints, and service workers for better user experience.
November 22, 2023
· 3,779 Views · 2 Likes
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Research Beats Best Practices: A Google Leadership Thought Process
Google's research-focused leadership outpaces traditional best practices, driving innovation through data-driven decisions and fostering a learning culture.
November 11, 2023
· 4,188 Views · 2 Likes
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Project Oxygen: Breathing New Life into Teams and Organizations
Project Oxygen identifies key managerial behaviors that boost team performance, fostering collaboration, communication, and professional growth in organizations.
November 9, 2023
· 3,781 Views · 2 Likes
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Exploring Lightweight Concurrency With Virtual Threads: A Developer-Agnostic Perspective
Virtual threads simplify concurrent programming, enhance scalability, and optimize resource usage in complex applications.
November 6, 2023
· 5,350 Views · 2 Likes
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TAO: A Comprehensive Look at Facebook's Distributed Data Store
TAO is Facebook's scalable, distributed data store, managing social graph objects and associations with a two-tiered caching mechanism for optimized performance.
November 5, 2023
· 4,372 Views · 4 Likes
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Developing Brain-Computer Interface (BCI) Applications With Java: A Guide for Developers
BCIs enable brain-device communication; Java aids development with libraries; challenges include signal quality and ethics.
November 1, 2023
· 7,712 Views · 4 Likes
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Mastering Backpressure in Java: Concepts, Real-World Examples, and Implementation
Backpressure balances data production and consumption, preventing system overload. Java's Flow API enables effective backpressure implementation in applications.
October 17, 2023
· 14,581 Views · 12 Likes
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Bloom Filters: Efficient Data Filtering With Practical Applications
Bloom filters enable efficient set membership testing with minimal memory, allow a small probability of false positives, and are used in spell checkers and CDNs.
October 10, 2023
· 6,833 Views · 5 Likes
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Fencing in Distributed Systems: Twitter's Approach
Fencing techniques effectively safeguard distributed systems, isolating faults and securing resources, as exemplified by Twitter.
October 6, 2023
· 4,732 Views · 2 Likes
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Split-Brain in Distributed Systems
Split-brain challenges distributed systems' data consistency; employing quorum-based techniques and consensus algorithms can mitigate potential issues.
October 5, 2023
· 5,868 Views · 3 Likes
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Gossip Protocol in Social Media Networks: Instagram and Beyond
Gossip protocol facilitates efficient information propagation in social media networks, offering fault-tolerance, scalability, and quick updates using Python examples.
October 5, 2023
· 9,698 Views · 5 Likes
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Leveraging Weka Library for Facebook Data Analysis
Leverage Weka library to analyze Facebook data, preprocess, perform feature selection, and clustering for insights into user behavior.
October 2, 2023
· 4,750 Views · 2 Likes
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Scalable Rate Limiting in Java With Code Examples: Managing Multiple Instances
Implement scalable rate limiting in Java using Token Bucket, Redis, and Gradle for high-performance and DoS attack protection.
October 2, 2023
· 9,386 Views · 3 Likes
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Building AI Applications With Java and Gradle
Explore AI development with Java and Gradle using popular libraries like Deeplearning4j, Weka, and Encog through practical code examples.
September 27, 2023
· 12,126 Views · 6 Likes
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Exploring Edge Computing: Delving Into Amazon and Facebook Use Cases
Edge computing enhances latency, bandwidth utilization, security, and scalability in data processing for companies like Amazon and Facebook.
September 20, 2023
· 7,599 Views · 5 Likes
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Agile Estimation: Techniques and Tips for Success
Agile estimation combines techniques and best practices for better project forecasting, aiding planning and decision-making.
September 19, 2023
· 18,904 Views · 7 Likes
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Securing Your Applications With Spring Security
Spring Security secures Java apps with authentication, authorization, and protection features, shown in an online banking example.
September 15, 2023
· 12,668 Views · 4 Likes

Comments

Building AI Applications With Java and Gradle

Oct 03, 2023 · Arun Pandey

Sure, Milan. I'll take a look.

Technical vs. Adaptive Leadership

Aug 12, 2023 · Arun Pandey

I totally agree, and getting this kind of leader in our career and life is a blessing!

Technical vs. Adaptive Leadership

Aug 12, 2023 · Arun Pandey

very well said :)

Locking Files in Java

May 21, 2017 · Arun Pandey

Thanks Sun. This is compatible with Java9.

Use this code-

public void writeToFileWithLock(String data) {

fc = randomAccessFile.getChannel();

ByteBuffer buffer = null;

try (FileLock fileLock = fc.tryLock()) {

if (null != fileLock) {

buffer = ByteBuffer.wrap(data.getBytes());

buffer.put(data.toString().getBytes());

buffer.flip();

while (buffer.hasRemaining())

fc.write(buffer);

}

} catch (OverlappingFileLockException | IOException ex) {

LOG.error("Exception occured while trying to get a lock on File... " + ex.getMessage());

}finally{

fc.close();

randomAccessFile.close();

}

}

ConcurrentHashMap in Java 8

Mar 15, 2017 · Arun Pandey

Thanks Gaurav

ConcurrentHashMap in Java 8

Mar 10, 2017 · Arun Pandey

Thank you Anand


A Look at ForkJoinPool and Parallel Streams

Dec 30, 2016 · Arun Pandey

Thank you Jirka. Actually ForkJoin Pool has come up with a common Pool concept in Java 8. you can refer - http://openjdk.java.net/projects/jdk8/features

" core/libs
103 Parallel Array Sorting Add additional utility methods to java.util.Arrays that use the JSR 166 Fork/Join parallelism common pool to provide sorting of arrays in parallel.
"


An Introduction to JBehave and BDD

Dec 16, 2016 · Arun Pandey

Hi Arturo, both are matured tool, and you are right that most of the organizations are using Cucumber. JBehave is purely Java based framework while Cucumber is Ruby based.

How to Create Runtime JUnit Test Cases

Oct 16, 2016 · Arun Pandey

Hi Charles,

It could be used as below ----

@RunWith(JUnitFactoryRunner.class)
public class TextFileInputDataTest {

/** Here's where to set up test case inputs, and their expected result will be
* read from a text-file, and will be populated as an map
* (Map<TestInputData, ExpectedResultData>) and need to compare values with
* their corresponding expected result fetched from map.
* This basically reads the text input file and prepare the List<RuntimeTestCase>.
* and provides this List as an input to RuntimeTestCase
* @return
*/

@JUnitTestFactory
public static Collection<?> tests() {

Map<TestInputData, ExpectedResultData> testInputAndResultMap = getTestInputAndResultMap();
Iterator<TestInputData> testInputAndResultMapItr = testInputAndResultMap.keySet().iterator();
ArrayList<RuntimeTestCase> tests = new ArrayList<RuntimeTestCase>(testInputAndResultMap.size());

while(testInputAndResultMapItr.hasNext()){
TestInputData testInput = testInputAndResultMapItr.next();
ExpectedResultData expectedResultData = testInputAndResultMap.get(testInput);
tests.add(new RuntimeTestCase(testInput, expectedResultData));
}
return tests;
}

private static Map<TestInputData, ExpectedResultData> getTestInputAndResultMap(){
Map<TestInputData, ExpectedResultData> testInputAndResultMap = new HashMap<TestInputData,
ExpectedResultData>();

TestInputData testInputData1 = new TestInputData();
ExpectedResultData expectedResultData1 = new ExpectedResultData();
testInputData1.setName("test-1");
expectedResultData1.setName("test-1");
testInputAndResultMap.put(testInputData1, expectedResultData1);

TestInputData testInputData2 = new TestInputData();
ExpectedResultData expectedResultData2 = new ExpectedResultData();
testInputData2.setName("test-2");
expectedResultData2.setName("test-2");
testInputAndResultMap.put(testInputData2, expectedResultData2);
return testInputAndResultMap;
}
}


The same way file can be used. In above example it will create 2 test cases. Hope it will clear your doubt. Thanks :)


JMS: A Quick and Complete Guide

Sep 30, 2016 · Arun Pandey

Thank you Run


How ConcurrentHashMap Works Internally in Java

Sep 10, 2016 · Arun Pandey

Thanks Akhil

How ConcurrentHashMap Works Internally in Java

Sep 10, 2016 · Arun Pandey

Thanks Franks :)


How ConcurrentHashMap Works Internally in Java

Sep 09, 2016 · Arun Pandey

Thanks Bhavin


How ConcurrentHashMap Works Internally in Java

Sep 09, 2016 · Arun Pandey

Thanks Shaomin. To answer you - It will not fail with ConcurrentModificationException. While one thread will operate to read the data on same entry another thread would be eligible to write, so get can overlap with put.

How ConcurrentHashMap Works Internally in Java

Sep 07, 2016 · Arun Pandey

Thnaks Minborg for suggestion,

VTD XML Parser

Aug 30, 2016 · Arun Pandey

Agreed Jimmy :)


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