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Ghila Castelnuovo

dblp:92/10809 · DBLP profile ↗
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2ranked-venue papers
1as first author
0since 2021 · last 2015
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Software engineering, systems software and programming languages · 2 · 1 first-author

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Software engineering, system software, and programming languages
1 paper
Program analysis · 100%

Topics — the 2 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Program analysis › static analysis
pointer analysis
0.112012
Abstractions from tests · POPL 2012
Program analysis
static analysis
0.112012
Abstractions from tests · POPL 2012

Methods — techniques the papers use, named apart from their topics

trace analysis · 0.1dynamic analysis · 0.1
YearPublicationVenuePosition
2015 Modularity in Lattices: A Case Study on the Correspondence Between Top-Down and Bottom-Up Analysis
Ghila Castelnuovo, Mayur Naik, Noam Rinetzky, Shmuel Sagiv, Hongseok Yang
SAS1
2012 Abstractions from tests
abstract
We present a framework for leveraging dynamic analysis to find good abstractions for static analysis. A static analysis in our framework is parametrised. Our main insight is to directly and efficiently compute from a concrete trace, a necessary condition on the parameter configurations to prove a given query, and thereby prune the space of parameter configurations that the static analysis must consider. We provide constructive algorithms for two instance analyses in our framework: a flow- and context-sensitive thread-escape analysis and a flow- and context-insensitive points-to analysis. We show the efficacy of these analyses, and our approach, on six Java programs comprising two million bytecodes: the thread-escape analysis resolves 80% of queries on average, disproving 28% and proving 52%; the points-to analysis resolves 99% of queries on average, disproving 29% and proving 70%.
Mayur Naik, Hongseok Yang, Ghila Castelnuovo, Shmuel Sagiv
POPL3