Research Article
Automated Dynamic Slicing based UML Modeling for Phylogenetic Classification
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
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| Volume 93 - Issue 7 |
| Published: May 2014 |
| Authors: Divanshi Priyadarshni Wangoo |
10.5120/16226-5703
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Divanshi Priyadarshni Wangoo . Automated Dynamic Slicing based UML Modeling for Phylogenetic Classification. International Journal of Computer Applications. 93, 7 (May 2014), 13-20. DOI=10.5120/16226-5703
@article{ 10.5120/16226-5703,
author = { Divanshi Priyadarshni Wangoo },
title = { Automated Dynamic Slicing based UML Modeling for Phylogenetic Classification },
journal = { International Journal of Computer Applications },
year = { 2014 },
volume = { 93 },
number = { 7 },
pages = { 13-20 },
doi = { 10.5120/16226-5703 },
publisher = { Foundation of Computer Science (FCS), NY, USA }
}
%0 Journal Article
%D 2014
%A Divanshi Priyadarshni Wangoo
%T Automated Dynamic Slicing based UML Modeling for Phylogenetic Classification%T
%J International Journal of Computer Applications
%V 93
%N 7
%P 13-20
%R 10.5120/16226-5703
%I Foundation of Computer Science (FCS), NY, USA
Abstract
This paper presents an efficient classification algorithm for categorizing evolutionary organisms using slicing techniques. Dynamic slicing excels in tracing out dependencies between executable statements. The nature of these dependencies aids in the determination of control statements in a program. Dynamic slicing technique imbibes the run time execution trace based on a slicing criterion. Dynamic slicing algorithms can trace both the backward and forward dependencies. The UML model is automatically generated from the source code to validate the forward and backward dynamic slicing algorithm. This paper shows the algorithmic implementation in NetBeans IDE 7. 4. It provides a new platform for automated software engineering. The algorithm efficiently discovers the evolutionary relationship between organisms . Forward dynamic slicing algorithm helps in identifying the successors of the organisms and the backward dynamic slicing algorithm finds out the predecessors of the evolutionary organisms. Both the algorithms are based on dynamic slicing criterion at the run time execution trace. The integration of these phylogenetic algorithms deciphers the building complexity of the evolutionary organisms. It proves to have an advantageous classification encasement for jeopardized species.
References
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