Efficient points-to analysis based on CFL-reachability summarisation

Download files
Access & Terms of Use
open access
Copyright: Shang, Lei
Altmetric
Abstract
Points-to analysis plays a critical role in modern compilers and a wide range of program understanding and bug detection tools. Nevertheless, developing precise and scalable points-to analysis for large-scale object-oriented software remains a challenge, especially in the presence of different client requirements and frequent software modifications. In this thesis, we present two new techniques for achieving more efficient points-to analysis based on Context-Free Language (CFL)-reachability. In general, our techniques significantly improve the state-of-the-art points-to analysis for Java applications when handling demand-driven queries and small code changes. This thesis firstly presents an on-demand dynamic summary-based points-to analysis for Java, which provides a more scalable solution without affecting precision. Our second technique is an incremental summarisation framework designed for IDEs, which can efficiently handle frequent program edits, addressing a long-standing challenge in points-to analysis. For each technique, we describe the algorithms and evaluate the implementations with a set of Java applications and clients.
Persistent link to this record
Link to Publisher Version
Link to Open Access Version
Additional Link
Author(s)
Shang, Lei
Supervisor(s)
Xue, Jingling
Creator(s)
Editor(s)
Translator(s)
Curator(s)
Designer(s)
Arranger(s)
Composer(s)
Recordist(s)
Conference Proceedings Editor(s)
Other Contributor(s)
Corporate/Industry Contributor(s)
Publication Year
2012
Resource Type
Thesis
Degree Type
PhD Doctorate
UNSW Faculty
Files
download whole.pdf 1.09 MB Adobe Portable Document Format
Related dataset(s)