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Related Experiment Video

Updated: Apr 23, 2026

A Virtual Machine Platform for Non-Computer Professionals for Using Deep Learning to Classify Biological Sequences of Metagenomic Data

A Virtual Machine Platform for Non-Computer Professionals for Using Deep Learning to Classify Biological Sequences of Metagenomic Data

Published on: September 25, 2021

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

Mansour Esmaeilpour¹, Vahideh Naderifar¹, Zarina Shukur²

¹Department of Computer Engineering, College of Engineering, Hamedan Branch, Islamic Azad University, Hamedan, Iran.

|September 23, 2014

Summary

This summary is machine-generated.

This study introduces DLA-DNA, a novel method for mining software design patterns and their relationships. DLA-DNA demonstrates superior precision and recall compared to existing tools, enhancing code analysis.

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Area of Science:

Software Engineering
Object-Oriented Programming
Pattern Mining

Background:

Design patterns offer reusable solutions for common software engineering problems.
Identifying and understanding relationships between design patterns is crucial for effective software development.

Purpose of the Study:

To introduce a new method and tool, DLA-DNA, for mining design patterns and their relationships.
To evaluate the effectiveness of DLA-DNA in terms of precision and recall compared to existing tools.

Main Methods:

Mining structural design patterns from object-oriented source code.
Extracting strong and weak relationships between identified design patterns.
Utilizing distributed learning automata (DLA) and deoxyribonucleic acid (DNA) sequence alignment principles.

Main Results:

The DLA-DNA method achieves high precision and recall in design pattern detection.
DLA-DNA outperforms Pinot, PTIDEJ, and DPJF in identifying design patterns and their relationships.
The proposed method shows average improvements of 20% and 9.6% in precision and recall over Pinot, respectively.

Conclusions:

The proposed method effectively identifies elemental and actual design patterns in software.
DLA-DNA provides a robust approach for analyzing design patterns and their interdependencies.
This method enhances code analysis by enabling determination of object and component dependency rates.