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Research Interests

My research interests include programming languages, persistent memory (NVM), dynamic program analysis, and data race detection.

I am currently working on novel methods for providing efficient persistent transactions with strong guarantees. Our work uses non-volatile memory, such as Intel Optane Memory, combined with commodity hardware transactional memory to allow programs to survive power interruptions and crashes, with minimal performance and scalability impacts.

Publications

## Crafty: Efficient, HTM-Compatible Persistent Transactions
Kaan Genç, Michael D. Bond, and Guoqing Harry Xu
ACM SIGPLAN Conference on Programming Language Design and Implementation (PLDI 2020), Online, June 2020

Talk Paper Extended Paper Implementation

## Dependence Aware, Predictive Unbounded Predictive Race Detection
Kaan Genç, Jake Roemer, Yufan Xu, and Michael D. Bond
ACM SIGPLAN International Conference on Object-Oriented Programming, Systems, Languages, and Applications (OOPSLA 2019), Athens, Greece, October 2019

Talk Paper Extended Paper Implementation

## SmartTrack: Efficient Predictive Race Detection
Jake Roemer, Kaan Genç, and Michael D. Bond
ACM SIGPLAN Conference on Programming Language Design and Implementation (PLDI 2020), Online, June 2020

Paper Extended Paper

## High-Coverage, Unbounded Sound Predictive Race Detection
Jake Roemer, Kaan Genç, and Michael D. Bond
ACM SIGPLAN Conference on Programming Language Design and Implementation (PLDI 2018), Philadelphia, PA, USA, June 2018

Paper Extended Paper

Teaching Experience

During Autumn 2017 and Spring 2018 semesters, I had the opportunity to teach the class CSE 2451, Advanced C Programming, at the Ohio State Univerity. The class had around 35 students enrolled for both semesters. I was given the full responsibilities for the class, including teaching the class, writing assignments and exams, grading, and holding office hours. I revised the course material I was given, making it more comprehensive and adding unique insights on building and optimizing advanced C programs.

The students were satisfied with my teaching, with my Student Evaluation of Instruction mean scores being 4.6 and 4.4 out of 5 for both semesters, a score above the university mean for classes of similar size.

Activities

OOPSLA 2020 Artifact Evaluation Committee member