CHANDHRA SHEKHAR BOTCHA@Chandhra103
1
Events attended
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India
1 year of experience
About me
I am a 3rd-year B.Tech Computer Science and Engineering student with a strong interest in Artificial Intelligence, Machine Learning, Software Development, and emerging technologies. I enjoy learning by building practical projects and solving real-world problems through technology. I have worked on projects involving AI/ML, computer vision, sustainability, healthcare support, and smart agriculture. Some of my project interests include AI-based crop and weed detection, CampusEnergy Twin for sustainability, ResQAI for emergency first-aid support, and AI-based attendance and spam detection systems. Along with project development, I am continuously improving my programming and problem-solving skills through DSA and coding practice in Java, C, and Python. I am also exploring areas such as cybersecurity, data analytics, web development, and modern AI tools and frameworks. I am passionate about learning new technologies, participating in technical opportunities, and turning ideas into useful solutions. My goal is to develop strong technical skills, gain industry experience, and build a successful career in the technology field.
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🤓 Latest Submissions
DevFix AI — Investigate. Fix. Verify
DevFix AI — Investigate. Fix. Verify. Software debugging often requires developers to spend significant time understanding an unfamiliar repository, tracing an issue across multiple files, identifying the root cause, planning a safe fix, applying changes, and repeatedly testing the result. This can lead to unnecessary investigation, rework, and verification effort. DevFix AI is an AI-assisted developer workflow designed to turn this process into a structured, verifiable pipeline. A developer provides a software repository and a problem. DevFix AI then investigates the repository, analyzes the issue, identifies the root cause, creates a fix plan, waits for developer approval, applies the approved fix, and verifies the result. The workflow is organized around six specialized stages: Repository Explorer, Root Cause Investigator, Fix Planner, Developer Approval, Fixer Agent, and Verification Agent. An Orchestrator coordinates these stages and passes the results from one step to the next. A key part of the solution is the human approval boundary. DevFix AI does not directly apply proposed changes without developer approval. This keeps the developer involved in the decision before the fixing stage begins. For our demonstration, DevFix AI investigates an intermittent 401 Unauthorized error after token refresh in a sample API gateway repository. The system traces the request and token lifecycle, identifies a race condition, produces a structured fix plan, applies the approved solution, and verifies the result through build, unit-test, regression-test, and lint checks. The final report presents the outcome as FIX VERIFIED. The project uses a modern web architecture with React, TypeScript, Vite, Tailwind CSS, Node.js/API abstraction, specialized agents, and local state management. Demo/Mock execution provides a consistent end-to-end demonstration of the workflow. IBM Bob 2.0 was used during development as an AI development partner for project setup, agent architecture, workflow implementation, API abstraction, debugging, build/type-checking activities, and documentation. DevFix AI demonstrates how a complex debugging workflow can be divided into specialized AI-assisted stages while keeping the developer in control. Investigate. Fix. Verify.
27 Sep 2026
