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Formal Specification and Verification of JDK’s Identity Hash Map Implementation

Formal specification and verification of JDK's identity hash map implementation
Authors: Martin De Boer; Stijn De Gouw; Jonas Klamroth; Christian Jung; Mattias Ulbrich; Alexander Weigl;

Formal Specification and Verification of JDK’s Identity Hash Map Implementation

Abstract

Hash maps are a common and important data structure in efficient algorithm implementations. Despite their wide-spread use, real-world implementations are not regularly verified. In this article, we present the first case study of the IdentityHashMap class in the Java JDK. We specified its behavior using the Java Modeling Language (JML) and proved correctness for the main insertion and lookup methods with KeY, a semi-interactive theorem prover for JML-annotated Java programs. Furthermore, we report how unit testing and bounded model checking can be leveraged to find a suitable specification more quickly. We also investigated where the bottlenecks in the verification of hash maps lie for KeY by comparing required automatic proof effort for different hash map implementations and draw conclusions for the choice of hash map implementations regarding their verifiability.

Keywords

ddc:004, Data structures, Specification and verification (program logics, model checking, etc.), Verified Hash Map, cooperative verification, verified hash map, real-world case study, verified data structure, Real-world case study, Cooperative verification, Deductive program verification, Verified hash map, deductive program verification, Java modeling language, Verified data structure, Verified Data Structure, DATA processing & computer science, Theory of programming languages, Real-world case study \and, Deductive Program Verification, Cooperative Verification, 004, Java Modeling Language, info:eu-repo/classification/ddc/004

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
13
Top 10%
Average
Top 10%
Green