A framework for identification of similarities between multiple algorithms
Data(s) |
2015
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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 | |
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 |