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Parameterized Graph Algorithms and Their Role in Static Program Analysis
PhD Thesis Proposal Defence Title: "Parameterized Graph Algorithms and Their Role in Static Program Analysis" by Miss Giovanna KOBUS CONRADO Abstract: Static analyses refer program analysis done prior to program execution, with goals such as speeding up the program, minimizing memory usage, or detecting potential errors and vulnerabilities. Although static analysis are usually expected to be efficient, many related problems are NP-hard or even undecidable. Here, we use parameterization graph algorithms to navigate these challenges. Parameterized complexity analyzes problems and instances along multiple parameters on the input or output, allowing for more efficient solutions when an instance has lower inherent difficulty. This thesis will focus on multiple studies that show parameterization can be used as a versatile tool to speed up static analysis. We will firstly present a couple of studies that exemplify how to design algorithms parameterized by structural graph parameters. These serve as an introduction to the topic of parameterized complexity. We will then present methods that rely on parameterized algorithms to solve static program analysis problems. These include speeding up register allocation by presenting a bound on the pathwidth of control-flow graphs, using graph parameters to process on-demand algebraic program analysis queries, and using a parameterized generalization of context-free grammars to identify context and field-sensitive data-flow. In each case, we develop new algorithms for these static analysis problems and experimentally demonstrate their efficiency compared to previous methods. Date: Wednesday, 27 November 2024 Time: 4:00pm - 6:00pm Venue: Room 5501 Lifts 25/26 Committee Members: Dr. Amir Goharshady (Supervisor) Prof. Pedro Sander (Supervisor) Dr. Sunil Arya (Chairperson) Prof. Charles Zhang