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Enabling Modularity and Re-use in Dynamic Program Analysis Tools for the Java Virtual Machine

Ansaloni, Danilo and Kell, Stephen and Zheng, Yudi and Bulej, Walter and Truma (2013) Enabling Modularity and Re-use in Dynamic Program Analysis Tools for the Java Virtual Machine. In: ECOOP 2013 – Object-Oriented Programming 27th European Conference. Lecture Notes in Computer Science . Springer, Berlin, Germany, pp. 352-377. ISBN 978-3-642-39037-1. E-ISBN 978-3-642-39038-8. (doi:10.1007/978-3-642-39038-8_15) (The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided) (KAR id:69705)

The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided.
Official URL:
https://doi.org/10.1007/978-3-642-39038-8_15

Abstract

Dynamic program analysis tools based on code instrumentation serve many important software engineering tasks such as profiling, debugging, testing, program comprehension, and reverse engineering. Unfortunately, constructing new analysis tools is unduly difficult, because existing frameworks offer little or no support to the programmer beyond the incidental task of instrumentation. We observe that existing dynamic analysis tools re-address recurring requirements in their essential task: maintaining state which captures some property of the analysed program. This paper presents a general architecture for dynamic program analysis tools which treats the maintenance of analysis state in a modular fashion, consisting of mappers decomposing input events spatially, and updaters aggregating them over time. We show that this architecture captures the requirements of a wide variety of existing analysis tools.

Item Type: Book section
DOI/Identification number: 10.1007/978-3-642-39038-8_15
Divisions: Divisions > Division of Computing, Engineering and Mathematical Sciences > School of Computing
Depositing User: Stephen Kell
Date Deposited: 25 Jan 2019 14:09 UTC
Last Modified: 16 Nov 2021 10:25 UTC
Resource URI: https://kar.kent.ac.uk/id/eprint/69705 (The current URI for this page, for reference purposes)

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