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Parameterized Graph Algorithms and Their Role in Static Program Analysis
The Hong Kong University of Science and Technology
Department of Computer Science and Engineering
PhD Thesis Defence
Title: "Parameterized Graph Algorithms and Their Role in Static Program
Analysis"
By
Miss Giovanna KOBUS CONRADO
Abstract:
Parameterized complexity is a branch of complexity theory that allows us to
analyze the relationship between an algorithm’s runtime and specific
characteristics of its input, beyond its size. This enables the creation of
algorithms that perform efficiently when the input displays certain
properties, rather than having the complexity always be bounded by the
worst-case scenario.
In particular, classically hard graph problems may become tractable when the
graph given as an input exhibits certain structural properties. Many graphs
encountered in real-world applications possess some of these properties,
which means we can develop exact algorithms that solve traditionally
difficult problems efficiently in practice. One setting where this approach
proves itself particularly useful is static analysis. Static analysis refers
to program analysis done prior to program execution, with goals such as
improving performance, minimizing memory usage, or detecting potential
errors and vulnerabilities. Many graphs derived from program analysis, such
as graphs representing the control of information, control of data, or
function calls, exhibit exploitable properties such as low treewidth or low
tree-depth.
In this thesis, I show how to use parameterization to speed up static
analyses. I introduce novel algorithms and present extensive experimental
data that show this approach can significantly improve existing methods for
analyzing programs.
Date: Wednesday, 16 July 2025
Time: 5:00pm - 7:00pm
Venue: Room 5501
Lifts 25/26
Chairman: Prof. Jidong ZHAO (CIVL)
Committee Members: Prof. Pedro SANDER (Supervisor)
Dr. Amir GOHARSHADY (Co-supervisor, Oxford)
Dr. Sunil ARYA
Dr. Lionel PARREAUX
Dr. Maximilian Alexander NITZSCHNER (MATH)
Prof. Jean-François Raskin (ULB)