The Latest and Popular SDLC Topics

Operational Principles, Architecture, Benefits, and Limitations of Artificial Intelligence Large Language Models

Large Language Models (LLMs) are advanced AI systems that generate human-like text by learning from extensive datasets and employing deep learning neural networks.

May 19, 2025

by Venkata Suresh Babu Chilluri

· 3,687 Views · 1 Like

Navigating the LLM Landscape: A Comparative Analysis of Leading Large Language Models

Here is an in-depth analysis comparing top LLMs, including OpenAI and its exciting contenders like LangChain, Anthropic, Cohere, Google, and more.

Updated May 19, 2025

by Jorge Torres

· 4,167 Views · 2 Likes

AI-Driven Test Automation Techniques for Multimodal Systems

Learn how AI-powered test automation improves reliability and efficiency in multimodal AI systems by addressing complex testing challenges effectively.

May 19, 2025

by Gaurav Sharma

· 3,928 Views · 5 Likes

The Smart Way to Talk to Your Database: Why Hybrid API + NL2SQL Wins

Plain-English questions against a live MySQL database in DBConvert Streams — and the five-table joins text-to-SQL wrote to answer them.

May 19, 2025

by Dmitry Narizhnykh

CORE

· 7,687 Views · 3 Likes

Integrating Model Context Protocol (MCP) With Microsoft Copilot Studio AI Agents

Model Context Protocol (MCP) integrates seamlessly with Copilot Studio, enabling AI agents to access real-time data and interoperate.

May 19, 2025

by Aravind Nuthalapati

CORE

· 24,792 Views · 1 Like

Using Python Libraries in Java

This article discusses how Python libraries can be integrated into Java by presenting real-world examples and Jython samples.

May 16, 2025

by Constantin Kwiatkowski

· 10,011 Views · 7 Likes

The Full-Stack Developer's Blind Spot: Why Data Cleansing Shouldn't Be an Afterthought

Full-stack developers often focus on clean code but neglect clean data, leading to performance issues, security vulnerabilities, and frustrated users.

May 16, 2025

by Farah Kim

· 3,974 Views · 2 Likes

How Can Developers Drive Innovation by Combining IoT and AI?

Discover how developers can drive innovation by combining IoT and AI to create transformative solutions and unlock new opportunities across industries.

May 16, 2025

by Harris Anderson

· 4,332 Views · 2 Likes

AI-Driven Root Cause Analysis in SRE: Enhancing Incident Resolution

This article examines how AI is transforming root cause analysis (RCA) in Site Reliability Engineering by automating incident resolution and improving system reliability.

May 16, 2025

by Nikhil Kapoor

· 5,070 Views · 5 Likes

Designing a Java Connector for Software Integrations

A Java connector unites different systems by allowing them to send information effectively while making crucial data freely available through interoperable interfaces.

May 15, 2025

by Anant Wairagade

· 7,768 Views · 1 Like

Memory Leak Due to Time-Taking finalize() Method

All objects in Java implicitly inherit from java.lang.Object. This class contains multiple methods, which can be overridden in the child class.

May 15, 2025

by Ram Lakshmanan

CORE

· 6,420 Views · 2 Likes

Developers Beware: Slopsquatting and Vibe Coding Can Increase Risk of AI-Powered Attacks

Slopsquatting and vibe coding are fueling a new wave of AI-driven cyberattacks, exposing developers to hidden risks through fake, hallucinated packages.

May 14, 2025

by Aminu Abdullahi

· 4,901 Views · 2 Likes

Unlocking AI Coding Assistants: Generate Unit Tests

This blog post instructs on creating qualitative unit tests for a Spring Boot application using an AI coding assistant and its capabilities and limitations.

May 14, 2025

by Gunter Rotsaert

CORE

· 4,412 Views · 2 Likes

Beyond Code Coverage: A Risk-Driven Revolution in Software Testing With Machine Learning

Machine learning-driven, risk-based testing targets critical risks, automates test selection, and improves software reliability.

May 14, 2025

by Gopinath Kathiresan

· 4,479 Views · 2 Likes

Intro to RAG: Foundations of Retrieval Augmented Generation, Part 1

Retrieval-augmented generation (RAG) retrieves relevant information from external sources to improve the accuracy and reliability of responses, making it a powerful tool.

May 14, 2025

by Jennifer Reif

CORE

· 3,667 Views · 3 Likes

Ethical AI in Agile

Learn all about ethical AI integration for Agile teams with four key guardrails: Data Privacy, Human Value, Output Validation, and Transparent Attribution.

May 14, 2025

by Stefan Wolpers

CORE

· 2,971 Views · 2 Likes