Toward applying agglomerative hierarchical clustering in improving the software development effort estimation

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F70883521%3A28140%2F22%3A63556599" target="_blank" >RIV/70883521:28140/22:63556599 - isvavai.cz</a>

Result on the web

<a href="http://dx.doi.org/10.1007/978-3-031-09070-7_30" target="_blank" >http://dx.doi.org/10.1007/978-3-031-09070-7_30</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1007/978-3-031-09070-7_30" target="_blank" >10.1007/978-3-031-09070-7_30</a>

Result language

angličtina

Original language name

Toward applying agglomerative hierarchical clustering in improving the software development effort estimation

Original language description

Background: There are many studies on the effect of data clustering on the effort estimation process. Most of them are on partitioning and density-based clustering, and some use hierarchical clustering but fewer details on the linkage methods. Aim: we concentrate on the aspect of the agglomerative hierarchical clustering algorithm’s effectiveness on the accuracy of the effort estimation. Method: We used the agglomerative hierarchical clustering algorithm to group the data into clusters then performed the IFPUG FPA method for effort estimation. The ISBSG dataset was used in this study. The number of clusters is determined using the dendrogram’s cut points. Different cut points and linkage methods were employed to cluster the dataset for the comparison. The estimated results of these clusters were compared with the result from the whole dataset without clustering. Result: with the selected number of clusters, results are consistently better than without clustering with all selected evaluation criteria. Conclusion: the accuracy of the effort estimation can be significantly improved when using agglomerative hierarchical clustering. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.

Czech name

—

Czech description

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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

2022

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

978-3-031-09069-1

ISSN

2367-3370

e-ISSN

2367-3389

Number of pages

19

Pages from-to

353-371

Publisher name

Springer International Publishing AG

Place of publication

Basel

Event location

on-line

Event date

Apr 26, 2022

Type of event by nationality

WRD - Celosvětová akce

UT code for WoS article

000893645700030