@inproceedings{f931275a4816493db6cddb41995f4384,
title = "Heap decomposition for concurrent shape analysis",
abstract = "We demonstrate shape analyses that can achieve a state space reduction exponential in the number of threads compared to the state-of-the-art analyses, while retaining sufficient precision to verify sophisticated properties such as linearizability. The key idea is to abstract the global heap by decomposing it into (not necessarily disjoint) subheaps, abstracting away some correlations between them. These new shape analyses are instances of an analysis framework based on heap decomposition. This framework allows rapid prototyping of complex static analyses by providing efficient abstract transformers given user-specified decomposition schemes. Initial experiments confirm the value of heap decomposition in scaling concurrent shape analyses.",
author = "Roman Manevich and Tal Lev-Ami and Mooly Sagiv and Ganesan Ramalingam and Josh Berdine",
year = "2008",
month = jan,
day = "1",
doi = "10.1007/978-3-540-69166-2_24",
language = "English",
isbn = "3540691634",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
pages = "363--377",
booktitle = "Static Analysis - 15th International Symposium, SAS 2008, Proceedings",
address = "Germany",
note = "15th International Static Analysis Symposium, SAS 2008 ; Conference date: 16-07-2008 Through 18-07-2008",
}
