Evaluating mean squared error as a fitness function in SOMA for software effort estimation: Insights from the NASA dataset

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F70883521%3A28140%2F24%3A63588058" target="_blank" >RIV/70883521:28140/24:63588058 - isvavai.cz</a>

Result on the web

<a href="http://dx.doi.org/10.1007/978-3-031-70300-3_30" target="_blank" >http://dx.doi.org/10.1007/978-3-031-70300-3_30</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1007/978-3-031-70300-3_30" target="_blank" >10.1007/978-3-031-70300-3_30</a>

Result language

angličtina

Original language name

Evaluating mean squared error as a fitness function in SOMA for software effort estimation: Insights from the NASA dataset

Original language description

Software effort estimation plays a pivotal role in software development. The Constructive Cost Model (COCOMO) is one of the most well-known algorithmic models for estimating software effort. However, the precision of these estimates is susceptible to input constants, potentially resulting in inaccuracies. To address this challenge, this research employs the Self-Organizing Migration Algorithm (SOMA), a metaheuristic algorithm, to optimize input constants of the basic COCOMO. This study uses the NASA18 dataset to evaluate the proposed experiment&apos;s performance against the original COCOMO. Evaluation criteria such as MMRE, PRED(0.25), MAE, and MSE, with MSE serving as a fitness function, were employed to validate results. Comparative analysis indicates that optimized COCOMO estimates exhibit improved prediction accuracy. Building on these promising findings, future research will extend testing more deeply with other datasets and involve investigation of the intermediate COCOMO and COCOMO II.

Czech name

—

Czech description

—

Type

D - Article in proceedings

CEP classification

—

OECD FORD branch

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Project

—

Continuities

S - Specificky vyzkum na vysokych skolach

Publication year

2024

Confidentiality

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

Article name in the collection

Lecture Notes in Networks and Systems

ISBN

978-3-031-70299-0

ISSN

2367-3370

e-ISSN

2367-3389

Number of pages

13

Pages from-to

416-428

Publisher name

Springer Science and Business Media Deutschland GmbH

Place of publication

Berlín

Event location

Virtual, Online

Event date

Apr 25, 2024

Type of event by nationality

WRD - Celosvětová akce

UT code for WoS article

001413910400030