2016.11.09(Wed) ‘머신러닝 기반 선별적 프로그램 분석’ – Hakjoo Oh 오학주교수 (Korea University 고려대학교)
-Titile: Machine-Learning-Guided Selective Program Analysis
Hakjoo Oh is an Assistant Professor of the Computer Science Department at Korea University. He received his Bachelors degree in Computer Science from KAIST in 2005 and his PhD from Seoul National University in 2012. He was a research associate at the center of software analysis for error-free computing in SNU before joining Korea University in 2015. His research interest lies in program analysis and synthesis, and in areas related to programming languages in general.
I am going to present my experience to use machine learning
techniques for automatically adapting a program analysis to a given
verification task. Building a cost-effective static analyzer for
real-world programs is regarded an art, mainly because of the
difficulty in balancing the cost and the precision of an analyzer. An
ideal analyzer should be able to adapt to a given analysis task
automatically, and avoid using techniques that unnecessarily improve
precision and increase analysis cost. However, designing a good
adaptation strategy is highly nontrivial, and it requires a large
amount of engineering efforts. In this talk, I will describe my
on-going research that aims to automate this procedure by
learning a good strategy from existing codebases.