Software bugs are ubiquitous and costly, posing significant challenges to software developers. An essential technique to reduce the cost of these bugs is static analysis, which allows software developers to reason about the run-time behaviour of their code without necessarily executing it. However, many software developers shy away from static analysis tools because they often fail to scale with modern software systems, generate numerous false positives, and interrupt development workflows. In this talk, I will share my journey over the past few years to overcome these challenges, focusing on enhancing the scalability, precision, and usability of static analysis tools to make them more practical for real-world application.

SCAM2024 Keynote by Karim Ali

Karim Ali is an Associate Professor of Computer Science at NYUAD. He received his PhD from the University of Waterloo in 2014 and worked as a postdoctoral researcher in TU Darmstadt for approximately two years. Before joining NYUAD, Dr. Ali was an Associate Professor in the Department of Computing Science at the University of Alberta. Dr. Ali’s lab conducts research on programming languages, particularly in scalability, precision, and usability of program analysis tools. His work ranges from developing new theories for scalable and precise program analyses to applications of program analysis in security and just-in-time compilers. In recognition of his research contributions in the field, Dr. Ali has been awarded the Dahl-Naygaard Junior Prize in 2021. He has also received two distinguished paper awards from ACM SIGSOFT and ACM SIGPLAN