Overview: Poor data validation, leakage, and weak preprocessing pipelines cause most XGBoost and LightGBM model failures in production.Default hyperparameters, ...

As AI agents transition from simple chatbots to autonomous systems capable of managing cloud incidents, navigating complex web interfaces, and executing multi-step API workflows, a new challenge has ...

Abstract: Large language models (LLMs) have shown promising code generation capabilities; however, they still face challenges in generating successful code for non-trivial programming tasks. To ...

Python development requires efficient IDE providing code intelligence, debugging capabilities, and framework integration where generic text editors lack Python-specific features demanding specialized ...

If you are interested in learning more about the new Claude Code Superpowers plugin and its ability to enhance AI-driven software development by embedding disciplined practices into the coding process ...

Abstract: This paper presents a comprehensive comparative analysis of three distinct prompt engineering strategies—Zero-Shot, Few-Shot, and Chain-of-Thought—for Python code debugging applications ...

ABSTRACT: Generative Artificial Intelligence (GAI) is rapidly reshaping programming education, yet little is known about how college students cognitively, emotionally, and behaviorally engage with AI ...

ABSTRACT: Generative Artificial Intelligence (GAI) is rapidly reshaping programming education, yet little is known about how college students cognitively, emotionally, and behaviorally engage with AI ...

The recently discovered sophisticated Linux malware framework known as VoidLink is assessed to have been developed by a single person with assistance from an artificial intelligence (AI) model. That's ...

I’ve always regarded debugging and troubleshooting as the most challenging of all hands-on engineering skills. It’s not formally taught; it is usually learned through hands-on experience (often the ...