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Locality metrics and program physical structures

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Bibliographic Details
Title: Locality metrics and program physical structures
Authors: Kang Zhang, Narasimhaiah Gorla
Contributors: The Pennsylvania State University CiteSeerX Archives
Source: http://www.utdallas.edu/~kzhang/Publications/JSS00.pdf.gz.
Publication Year: 2000
Collection: CiteSeerX
Subject Terms: Locality metric, Physical structure, Logical structure, Program component
Description: This paper introduces a new class of physical metrics, known as locality metric, that measures the relative positions of components in a program listing and reveals useful attributes that may affect programmer productivity. The placement of the components can be determined by a simple algorithm that is of polynomial time complexity. The paper compares the performance of the algorithm with that of an exhaustive search approach and also reports various characteristics of the locality metric based on the collected statistical dam. The performance shows the feasibility of the algorithm and closeness of its output to the optimal result found by the exhaustive approach.
Document Type: text
File Description: application/pdf
Language: English
Relation: http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.18.6689; http://www.utdallas.edu/~kzhang/Publications/JSS00.pdf.gz
Availability: http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.18.6689
http://www.utdallas.edu/~kzhang/Publications/JSS00.pdf.gz
Rights: Metadata may be used without restrictions as long as the oai identifier remains attached to it.
Accession Number: edsbas.F4484BEB
Database: BASE
Description
Abstract:This paper introduces a new class of physical metrics, known as locality metric, that measures the relative positions of components in a program listing and reveals useful attributes that may affect programmer productivity. The placement of the components can be determined by a simple algorithm that is of polynomial time complexity. The paper compares the performance of the algorithm with that of an exhaustive search approach and also reports various characteristics of the locality metric based on the collected statistical dam. The performance shows the feasibility of the algorithm and closeness of its output to the optimal result found by the exhaustive approach.