Evidence map›Paper›PMID 25243670›Full record

ArticlePloS one2014

Design pattern mining using distributed learning automata and DNA sequence alignment.

Mansour Esmaeilpour, Vahideh Naderifar, Zarina Shukur

Abstract read
In one paragraph

Article in PloS one, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

3 authors.

Mansour EsmaeilpourDepartment of Computer Engineering, College of Engineering, Hamedan Branch, Islamic Azad University, Hamedan, Iran.
Vahideh NaderifarDepartment of Computer Engineering, College of Engineering, Hamedan Branch, Islamic Azad University, Hamedan, Iran.
Zarina ShukurSoftware Technology and Management Research Center, Faculty of Information Science and Technology, Universiti Kebangsaan Malaysia, Bangi, Malaysia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

contextOver the last decade, design patterns have been used extensively to generate reusable solutions to frequently encountered problems in software engineering and object oriented programming. A design pattern is a repeatable software design solution that provides a template for solving various instances of a general problem.

objectiveThis paper describes a new method for pattern mining, isolating design patterns and relationship between them; and a related tool, DLA-DNA for all implemented pattern and all projects used for evaluation. DLA-DNA achieves acceptable precision and recall instead of other evaluated tools based on distributed learning automata (DLA) and deoxyribonucleic acid (DNA) sequences alignment.

methodThe proposed method mines structural design patterns in the object oriented source code and extracts the strong and weak relationships between them, enabling analyzers and programmers to determine the dependency rate of each object, component, and other section of the code for parameter passing and modular programming. The proposed model can detect design patterns better that available other tools those are Pinot, PTIDEJ and DPJF; and the strengths of their relationships.

resultsThe result demonstrate that whenever the source code is build standard and non-standard, based on the design patterns, then the result of the proposed method is near to DPJF and better that Pinot and PTIDEJ. The proposed model is tested on the several source codes and is compared with other related models and available tools those the results show the precision and recall of the proposed method, averagely 20% and 9.6% are more than Pinot, 27% and 31% are more than PTIDEJ and 3.3% and 2% are more than DPJF respectively.

conclusionThe primary idea of the proposed method is organized in two following steps: the first step, elemental design patterns are identified, while at the second step, is composed to recognize actual design patterns.

Indexed as

DNASequence AlignmentPattern Recognition, AutomatedProgramming LanguagesSequence Analysis, DNASoftwareDNA

Identifiers

PMID25243670
PMCPMC4171372

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.