Chhavi Shukla @Chhavi_s

TraceRoot is an AI-powered Root Cause Analysis (RCA) platform designed to simplify debugging and software failure investigation for both experienced developers and aspiring engineers. Modern software systems generate massive amounts of logs, stack traces, and error outputs, making debugging a time-consuming and mentally exhausting process. Developers often spend hours manually tracing errors across files, dependencies, and recent code changes just to identify what actually caused a failure. TraceRoot acts like a diagnostic lab for code. The platform analyzes logs, stack traces, and source code context to identify likely causes of failures, explain why the issue occurred, and suggest possible fixes in a beginner-friendly and understandable manner. Instead of only showing the error, TraceRoot focuses on explaining the logical root cause behind the failure, helping users learn while debugging. The system combines AI-powered reasoning with repository-aware analysis to provide more contextual and intelligent debugging assistance. It can inspect affected files, analyze code snippets around the error location, and correlate failures with possible dependency or logic issues. This helps reduce debugging time, lowers cognitive overload, and improves developer productivity. TraceRoot is especially useful for students, beginner engineers, hackathon participants, and developers working on unfamiliar codebases. The goal is to make debugging less intimidating and more educational by transforming raw technical errors into clear, actionable insights. Future improvements include repository explanation, dependency visualization, commit-aware analysis, and automated debugging workflows to create a complete AI-powered developer investigation platform.

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