Sundas Javed@sundasjaved38449087
2
Events attended
1
Submissions made
Pakistan
1 year of experience
About me
I am a Software Engineering student with a strong interest in technology and software development with good communication skills . Throughout my academic journey, I have developed skills in web development, Python, and Generative AI. I have worked on academic and personal projects that strengthened my problem-solving and development skills. Recently, I participated in an AI-focused hackathon, where I gained practical experience in building real-world applications. I am continuously learning new technologies and looking for opportunities to apply my skills professionally. My goal is to become a skilled software engineer and build innovative, user-focused solutions.
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🤓 Latest Submissions
Code Lens
Reviewing pull requests in large software repositories can be difficult because a change may affect code, tests, dependencies, documentation, and other parts of the repository. Traditional automated reviewers often analyze only the changed lines and can miss important context or produce generic suggestions. Our solution is an agentic AI powered pull request quality checker that analyzes a pull request together with the relevant repository context. It first understands the type and scope of the change, then identifies related files, dependencies, tests, and documentation that may be affected. Specialized analysis steps can then focus on code quality, potential bugs, security concerns, test coverage, and regression risks. Instead of relying only on an AI generated opinion, the system can use relevant tests and other available evidence to support its findings. This allows the final review to distinguish between issues identified through reasoning and issues supported by actual verification. The system is designed for real world repositories, including large and private codebases where sending the entire repository to an AI model would be inefficient or inappropriate. It retrieves relevant context based on the actual pull request and applies analysis according to the type of change. The target users are software developers, open source maintainers, and development teams who want faster and more context aware pull request reviews. The system aims to reduce manual review effort while giving developers clear findings, explanations, and evidence that they can act on.
27 Sep 2026
