A framework for identification of similarities between multiple algorithms


Autoria(s): Amarasinghe Arachchilage, Madhushika Madara Erangani Karunarathra
Data(s)

2015

Resumo

This thesis in software engineering presents a novel automated framework to identify similar operations utilized by multiple algorithms for solving related computing problems. It provides a new effective solution to perform multi-application based algorithm analysis, employing fundamentally light-weight static analysis techniques compared to the state-of-art approaches. Significant performance improvements are achieved across the objective algorithms through enhancing the efficiency of the identified similar operations, targeting discrete application domains.

Formato

application/pdf

Identificador

http://eprints.qut.edu.au/82784/

Publicador

Queensland University of Technology

Relação

http://eprints.qut.edu.au/82784/1/Madhushika%20Madara%20Erangani%20Karunarathra_Amarasinghe%20Arachchilage_Thesis.pdf

Amarasinghe Arachchilage, Madhushika Madara Erangani Karunarathra (2015) A framework for identification of similarities between multiple algorithms. PhD thesis, Queensland University of Technology.

Fonte

School of Electrical Engineering & Computer Science; Science & Engineering Faculty

Palavras-Chave #Algorithm analysis #Algorithm clustering #Parameter weighting system #Algorithm similarities #Special-purpose operations
Tipo

Thesis