ProRE: An ACO- based programmer recommendation model to precisely manage software bugs

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27240%2F23%3A10251685" target="_blank" >RIV/61989100:27240/23:10251685 - isvavai.cz</a>

Result on the web

<a href="https://www.scopus.com/record/display.uri?eid=2-s2.0-85146751385&origin=resultslist&sort=plf-f&src=s&st1=rezac+f&sid=a85db75dc11a8dcd04fa1cd71ca515c2&sot=b&sdt=b&sl=20&s=AUTHOR-NAME%28rezac+f%29&relpos=0&citeCnt=0&searchTerm=" target="_blank" >https://www.scopus.com/record/display.uri?eid=2-s2.0-85146751385&origin=resultslist&sort=plf-f&src=s&st1=rezac+f&sid=a85db75dc11a8dcd04fa1cd71ca515c2&sot=b&sdt=b&sl=20&s=AUTHOR-NAME%28rezac+f%29&relpos=0&citeCnt=0&searchTerm=</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1016/j.jksuci.2022.12.017" target="_blank" >10.1016/j.jksuci.2022.12.017</a>

Result language

angličtina

Original language name

ProRE: An ACO- based programmer recommendation model to precisely manage software bugs

Original language description

The process of assigning bugs to particular programmers is called bug assignment in software engineering. The programmer can fix the bugs by applying their knowledge. This research article presents an Ant colony optimization-based programmer recommendation model (ProRE) to manage software bugs precisely. The proposed ProRE model performs four operations: data pre-processing, i.e., data Pre-processing, extraction, feature selection, and programmer recommendation process. The feature selection stage utilized the Ant colony optimization (ACO) method to determine the appropriate subsets of features from all features. In the programmer recommendation stages, three programmer metrics, i.e., functionality ranking, bug occurrence, and mean Bug fixing time, are utilized for the recommendation assignment. The effectiveness of the proposed programmer recommendation system is assessed using datasets from Mozilla, Eclipse, Firefox, JBoss, and OpenFOAM. It is noted that the proposed model offers a better recommendation strategy over the other available systems. The simulation findings of the proposed ProRE model are also analyzed with well-known available ML methods, i.e., SVM, NB, and C4.5. It is observed that the recommendation results have improved by an average of 4%, 10%, and 12% compared to SVM, C4.5, and NB-based models. Programmer recommendation software is implemented for allocating the bugs to accurate programmers. It has been found that the proposed ProRE model generates more optimistic outcomes than existing ones.

Czech name

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Czech description

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Type

J_SC - Article in a specialist periodical, which is included in the SCOPUS database

CEP classification

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OECD FORD branch

20203 - Telecommunications

Project

—

Continuities

S - Specificky vyzkum na vysokych skolach

Publication year

2023

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Name of the periodical

Journal of King Saud University - Computer and Information Sciences

ISSN

1319-1578

e-ISSN

2213-1248

Volume of the periodical

35

Issue of the periodical within the volume

1

Country of publishing house

SA - THE KINGDOM OF SAUDI ARABIA

Number of pages

16

Pages from-to

483-498

UT code for WoS article

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EID of the result in the Scopus database

2-s2.0-85146751385