We learn from our alumni in this interaction series, often technically, sometimes semi-technically.

Akshay Utture Uber

Akshay is a researcher and engineer who works primarily on Static Analysis, but his research interests span broadly across Compilers, Program Analysis and Verification. He recently graduated from UCLA with a Ph.D. in Computer Science, and has joined Uber's Programming Systems Group. At UCLA, he was a part of the Compilers Group, and worked with Jens Palsberg on adapting static analysis tools to better meet user expectations on false positives, analysis time and repairability. Before the Ph.D., he completed a five year Dual Degree (Integrated Bachelors and Masters) in Computer Science from the Indian Institute of Technology Madras. There he worked on the runtime design of the X10 task-parallel programming language, and on algorithms for graph matchings.

Resource leaks are a common and elusive source of bugs that can result in crashes and security vulnerabilities. The most effective technique to identify such leaks during development is static analysis. However, empirical studies show that in addition to leak warnings, developers also need help in the form of automated fix suggestions to correctly repair such leaks. In this talk, I shall introduce our new tool, RLFixer, a static-analysis-based repair tool that automatically generates high-quality fixes for resource leaks identified by any resource-leak detector. We will start with a brief introduction to static analysis, then take a deep dive into the design of RLFixer, and finally, conclude with a brief discussion about the potential for applying LLMs to this resource-leak repair problem.

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