Software cost estimation: a comparative study of COCOMO-II, Halstead and IVR models

Iqtidar Ali; Shah Nawaz; Mohib Ullah; Rafiullah Khan; Muhammad  Tariq; Imran Ud Din; Arshad Khan; Gohar Rehman Khalil; Majid Khan

Software cost estimation: a comparative study of COCOMO-II, Halstead and IVR models

Iqtidar Ali, Shah Nawaz, Mohib Ullah, Rafiullah Khan, Muhammad Tariq^*, Imran Ud Din, Arshad Khan, Gohar Rehman Khalil, Majid Khan

^*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceeding › Conference proceeding contribution › peer-review

Abstract

The comparison of the three best cost estimation models to be simulated for two prestigious organization datasets. The aim is to find out the best one in term of time and money. Multiple efforts in wastes grabs the attention of the researchers that a software project neither completed in time nor budget. Extra ordinary best models have been developed in the recent days. From online services to construction industry the field has spread and modified itself with the changes. Now the cost estimation industry has grown well. There are specific models for specific purposes. As the field has changed to Machine Learning (ML) and still it is not easy to find out the correct cost estimation of a project. This study has shown the comparison of COCOMO-II, Halstead and IVR cost models. NASA 93 and Turkish Industry datasets has been chosen. The evaluation performance has been checked through Magnitude Relative Error (MRE) and Mean Magnitude Relative Error (MMRE). From the simulation of these projects with these models, COCOMO-II performs outstandingly. So this study suggest that COCOMO-II is best enough for software cost estimation.

Original language	English
Title of host publication	Proceedings of 1st International Conference on Computing Technologies, Tools and Applications (ICTAPP-23)
Editors	Javed Iqbal Bangash
Place of Publication	Pakistan
Publisher	The University of Agriculture Peshawar
Pages	338-348
Number of pages	11
Publication status	Published - 2023
Externally published	Yes
Event	International Conference on Computing Technologies, Tools and Applications (1st : 2023) - Peshawar, Pakistan Duration: 9 May 2023 → 11 May 2023 Conference number: 1st

Conference

Conference	International Conference on Computing Technologies, Tools and Applications (1st : 2023)
Abbreviated title	ICTAPP-23
Country/Territory	Pakistan
City	Peshawar
Period	9/05/23 → 11/05/23

Keywords

ML (Machine Learning)
COCOMO (Constructive Cost Model)
IVR (Interactive Voice Response)
MRE (Mean Relative Error)
MMRE (Mean Magnitude Relative Error)

Access to Document

https://ictapp.org.pk/ICTAPP-23-97-Abstract.htmlLicence: Unspecified

Cite this

Ali, I., Nawaz, S., Ullah, M., Khan, R., Tariq, M., Ud Din, I., Khan, A., Khalil, G. R., & Khan, M. (2023). Software cost estimation: a comparative study of COCOMO-II, Halstead and IVR models. In J. I. Bangash (Ed.), Proceedings of 1st International Conference on Computing Technologies, Tools and Applications (ICTAPP-23) (pp. 338-348). The University of Agriculture Peshawar. https://ictapp.org.pk/ICTAPP-23-97-Abstract.html

@inproceedings{868ab104e414463b8fbe04b8fb0bedf9,

title = "Software cost estimation: a comparative study of COCOMO-II, Halstead and IVR models",

abstract = "The comparison of the three best cost estimation models to be simulated for two prestigious organization datasets. The aim is to find out the best one in term of time and money. Multiple efforts in wastes grabs the attention of the researchers that a software project neither completed in time nor budget. Extra ordinary best models have been developed in the recent days. From online services to construction industry the field has spread and modified itself with the changes. Now the cost estimation industry has grown well. There are specific models for specific purposes. As the field has changed to Machine Learning (ML) and still it is not easy to find out the correct cost estimation of a project. This study has shown the comparison of COCOMO-II, Halstead and IVR cost models. NASA 93 and Turkish Industry datasets has been chosen. The evaluation performance has been checked through Magnitude Relative Error (MRE) and Mean Magnitude Relative Error (MMRE). From the simulation of these projects with these models, COCOMO-II performs outstandingly. So this study suggest that COCOMO-II is best enough for software cost estimation.",

keywords = "ML (Machine Learning), COCOMO (Constructive Cost Model), IVR (Interactive Voice Response), MRE (Mean Relative Error), MMRE (Mean Magnitude Relative Error)",

author = "Iqtidar Ali and Shah Nawaz and Mohib Ullah and Rafiullah Khan and Muhammad Tariq and {Ud Din}, Imran and Arshad Khan and Khalil, {Gohar Rehman} and Majid Khan",

year = "2023",

language = "English",

pages = "338--348",

editor = "Bangash, {Javed Iqbal}",

booktitle = "Proceedings of 1st International Conference on Computing Technologies, Tools and Applications (ICTAPP-23)",

publisher = "The University of Agriculture Peshawar",

address = "Pakistan",

note = "International Conference on Computing Technologies, Tools and Applications (1st : 2023), ICTAPP-23 ; Conference date: 09-05-2023 Through 11-05-2023",

}

Ali, I, Nawaz, S, Ullah, M, Khan, R, Tariq, M, Ud Din, I, Khan, A, Khalil, GR & Khan, M 2023, Software cost estimation: a comparative study of COCOMO-II, Halstead and IVR models. in JI Bangash (ed.), Proceedings of 1st International Conference on Computing Technologies, Tools and Applications (ICTAPP-23). The University of Agriculture Peshawar, Pakistan, pp. 338-348, International Conference on Computing Technologies, Tools and Applications (1st : 2023), Peshawar, Pakistan, 9/05/23. <https://ictapp.org.pk/ICTAPP-23-97-Abstract.html>

Software cost estimation: a comparative study of COCOMO-II, Halstead and IVR models. / Ali, Iqtidar; Nawaz, Shah; Ullah, Mohib et al.
Proceedings of 1st International Conference on Computing Technologies, Tools and Applications (ICTAPP-23). ed. / Javed Iqbal Bangash. Pakistan: The University of Agriculture Peshawar, 2023. p. 338-348.

Research output: Chapter in Book/Report/Conference proceeding › Conference proceeding contribution › peer-review

TY - GEN

T1 - Software cost estimation

T2 - International Conference on Computing Technologies, Tools and Applications (1st : 2023)

AU - Ali, Iqtidar

AU - Nawaz, Shah

AU - Ullah, Mohib

AU - Khan, Rafiullah

AU - Tariq, Muhammad

AU - Ud Din, Imran

AU - Khan, Arshad

AU - Khalil, Gohar Rehman

AU - Khan, Majid

N1 - Conference code: 1st

PY - 2023

Y1 - 2023

N2 - The comparison of the three best cost estimation models to be simulated for two prestigious organization datasets. The aim is to find out the best one in term of time and money. Multiple efforts in wastes grabs the attention of the researchers that a software project neither completed in time nor budget. Extra ordinary best models have been developed in the recent days. From online services to construction industry the field has spread and modified itself with the changes. Now the cost estimation industry has grown well. There are specific models for specific purposes. As the field has changed to Machine Learning (ML) and still it is not easy to find out the correct cost estimation of a project. This study has shown the comparison of COCOMO-II, Halstead and IVR cost models. NASA 93 and Turkish Industry datasets has been chosen. The evaluation performance has been checked through Magnitude Relative Error (MRE) and Mean Magnitude Relative Error (MMRE). From the simulation of these projects with these models, COCOMO-II performs outstandingly. So this study suggest that COCOMO-II is best enough for software cost estimation.

AB - The comparison of the three best cost estimation models to be simulated for two prestigious organization datasets. The aim is to find out the best one in term of time and money. Multiple efforts in wastes grabs the attention of the researchers that a software project neither completed in time nor budget. Extra ordinary best models have been developed in the recent days. From online services to construction industry the field has spread and modified itself with the changes. Now the cost estimation industry has grown well. There are specific models for specific purposes. As the field has changed to Machine Learning (ML) and still it is not easy to find out the correct cost estimation of a project. This study has shown the comparison of COCOMO-II, Halstead and IVR cost models. NASA 93 and Turkish Industry datasets has been chosen. The evaluation performance has been checked through Magnitude Relative Error (MRE) and Mean Magnitude Relative Error (MMRE). From the simulation of these projects with these models, COCOMO-II performs outstandingly. So this study suggest that COCOMO-II is best enough for software cost estimation.

KW - ML (Machine Learning)

KW - COCOMO (Constructive Cost Model)

KW - IVR (Interactive Voice Response)

KW - MRE (Mean Relative Error)

KW - MMRE (Mean Magnitude Relative Error)

M3 - Conference proceeding contribution

SP - 338

EP - 348

BT - Proceedings of 1st International Conference on Computing Technologies, Tools and Applications (ICTAPP-23)

A2 - Bangash, Javed Iqbal

PB - The University of Agriculture Peshawar

CY - Pakistan

Y2 - 9 May 2023 through 11 May 2023

ER -

Software cost estimation: a comparative study of COCOMO-II, Halstead and IVR models

Abstract

Conference

Keywords

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