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A Framework For Efficient Modular Heap Analysis (Paperback) Loot Price: R1,911
Discovery Miles 19 110
A Framework For Efficient Modular Heap Analysis (Paperback): Ravichandhran Madhavan, G. Ramalingam, Kapil Vaswani

A Framework For Efficient Modular Heap Analysis (Paperback)

Ravichandhran Madhavan, G. Ramalingam, Kapil Vaswani

Series: Foundations and Trends (R) in Programming Languages

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Loot Price R1,911 Discovery Miles 19 110 | Repayment Terms: R179 pm x 12*

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Modular heap analysis techniques analyze a program by computing summaries for every procedure in the program that describes its effects on an input heap, using pre-computed summaries for the called procedures. In A Framework For Efficient Modular Heap Analysis, the focus is on a family of modular heap analyses that summarize a procedure's heap effects using a context-independent, shape-graph-like summary that is agnostic to the aliasing in the input heap. These analyses are very efficient but their complexity and the absence of a theoretical formalization and correctness proofs makes it hard to produce correct extensions and modifications of these algorithms - whether to improve precision or scalability or to compute more information. This book presents a modular heap analysis framework that generalizes these four analyses. It formalizes this framework as an abstract interpretation and establishes the correctness and termination guarantees. It formalizes the four analyses as instances of the framework. The formalization explains the basic principle behind such modular analyses and simplifies the task of producing extensions and variations of such analyses. It is written with exceptional clarity and is a delightful read for program analysis experts and novices alike.

General

Imprint: Now Publishers Inc
Country of origin: United States
Series: Foundations and Trends (R) in Programming Languages
Release date: 2015
First published: 2015
Authors: Ravichandhran Madhavan • G. Ramalingam • Kapil Vaswani
Dimensions: 234 x 156 x 7mm (L x W x T)
Format: Paperback
Pages: 130
ISBN-13: 978-1-68083-002-6
Categories: Books > Computing & IT > Applications of computing > Databases > Data mining
LSN: 1-68083-002-3
Barcode: 9781680830026

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