Software Cost Estimation – A Comparative Study of COCOMO-II and Bailey-Basili Models

Ullah, M.I.; Ali, Rahman; Abdullah, .; Ahmad, Mukhtiar Ahmad Mukhtiar; Khan, Tufail; Mulk, Farhan Ul

doi:10.1109/aect47998.2020.9194166

Cited by 7 publications

(5 citation statements)

References 8 publications

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“…The model relies on function points to give the software cost. The equation applied to come up with an approximate cost is private as it is proprietary software (Kahuti, 2020). The model involves function points, which are 25 input functionalities rather than lines of code.…”

Section: Estimacs Modelmentioning

confidence: 99%

A Model for Total Cost Determination in Open-Source Software Ownership: Case of Kenyan Universities’ Learning Management System

Kodhek,

Kamau,

Musyoka

2024

CIS

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The adoption of open-source products is slowly increasing; the increase, however, is slower than expected, considering that most open-source products are freely available. Researchers and scholars have attributed the adoption levels to, among other things, a lack of know-how of the total cost of ownership of the open-source software. Thus, it is crucial for the cost of owning the software to be developed. While an ongoing endeavor to develop a model to determine the total cost of ownership of open-source software, the models have proved to be less accurate and do not capture essential elements. Moreover, there has been a rising call for organizations to adopt open-source software to lower the software costs incurred on proprietary software. If the cost of owning open-source software were known, it would be beneficial as several organizations and institutions could adopt it readily. The data was collected from Universities in Kiambu and Embu Counties. Linear regression analysis was done to help develop the model, and a mathematical model was developed. The proposed model was: total cost of open-source software ownership = direct + +indirect + hidden costs. To validate the model, it was subjected to expert validation. The model will be an outstanding contribution to information technology as it will make it possible to come up with the total cost of owning open-source software.

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Section: Estimacs Modelmentioning

confidence: 99%

A Model for Total Cost Determination in Open-Source Software Ownership: Case of Kenyan Universities’ Learning Management System

Kodhek,

Kamau,

Musyoka

2024

CIS

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“…COCOMO, Function Point Analysis (FPA), and software estimation by analogy are examples of common algorithmic methodologies. COCOMO forecasts the effort, time, and expense needed for software development [14]. With increasing levels of accuracy and sophistication, COCOMO has developed into several variants, including Basic COCOMO, Intermediate COCOMO, and Detailed COCOMO [15].…”

Section: B Algorithmic-based Approachesmentioning

confidence: 99%

Software Cost and Effort Estimation: Current Approaches and Future Trends

Rashid,

Shafi,

Ahmad

et al. 2023

IEEE Access

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Software cost and effort estimation is one of the most significant tasks in the area of software engineering. Research conducted in this field has been evolving with new techniques that necessitate periodic comparative analyses. Software project success largely depends on accurate software cost estimation as it gives an idea of the challenges and risks involved in the development. The great diversity of ML and Non-ML techniques has generated a comparison and progressed into the integration of these techniques. Based on varying advantages it has become imperative to work out preferred estimation techniques to improve the project development process. This study aims to present a systematic literature review (SLR) to investigate the trends of the articles published in the recent one and a half decades and to propose a way forward. This systematic literature review has proposed a three-stage approach to plan (Tollgate approach), conduct (Likert type scale), and report the results from five renowned digital libraries. For the selected 52 articles, artificial neural network model (ANN) and constructive cost model (COCOMO) based approaches have been the favored techniques. The mean magnitude of relative error (MMRE) has been the preferred accuracy metric, software engineering, and project management are the most relevant fields, and the promise repository has been identified as the widely accessed database. This review is likely to be of value for the development, cost, and effort estimations.

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“…Metode Bailey-Basili adalah salah satu dari beberapa model estimasi yang menggunakan perhitungan persamaan matematika. Perhitungan COCOMO II dan Bailey Basili dihitung dengan nilai Line of Code (LOC) dan faktor lainnya seperti Effort Multiplier dan Scale Factor (M. Ullah et al, 2020). Kemudian, metode Homeostasis Mutation Based Differential Evolution (HMBDE) adalah sebuah algoritma yang digunakan untuk mengembangkan parameter dari metode COCOMO II.…”

Section: Metode Pada Estimasi Biaya Perangkat Lunakunclassified

“…Line of Code (LOC) adalah input dasar dari perhitungan estimasi biaya yang berisi baris kode dari proyek perangkat lunak dan berfungsi mengukur besarnya perangkat lunak. LOC ini digunakan dalam perhitungan pada metode COCOMO, yang tidak termasuk baris komentar dan baris kosong (M. Ullah et al, 2020) Singh, 2016) tidak menggunakan semua jenis dari Effort Multiplier, tetapi hanya menggunakan jenis Personnel Attributes saja. Selanjutnya, Scale Faktor (SF) adalah proses perhitungan untuk menentukan karakteristik serta usaha dari suatu proyek yang sedang berjalan (Maqdum et al, 2019).…”

Section: Faktor Yang Mempengaruhi Estimasi Biaya Perangkat Lunakunclassified

“…Dan faktor terakhir adalah data proyek software sebelumnya atau historical data yang digunakan sebagai acuan estimasi biaya. Ziaaddini, 2016), (Pratama et al, 2017), (Kholed Langsari et al, 2018) Function Point (FP) (Padmaja & Haritha, 2017), (Sarno et al, 2015a), (Garg & Gupta, 2015) Effort Multiplier (EM) (Gharehchopogh, Maleki, et al, 2015), (Sarno et al, 2015b) Sarno, 2017), (Pratama et al, 2017), (Kholed Langsari et al, 2018) Historical Data (M. Ullah et al, 2020), (Singh & Kumar, 2017)…”

Section: Faktor Yang Mempengaruhi Estimasi Biaya Perangkat Lunakunclassified

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Analisis Metode Estimasi Biaya pada Perangkat Lunak Beserta Faktor-Faktor yang Mempengaruhi : A Systematic Literature Review

Ariyanto

2022

JTIIK

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Estimasi biaya sampai sekarang masih menjadi salah satu permasalahan utama dalam perencanaan proyek perangkat lunak. Estimasi biaya ini memiliki peran yang penting karena berpengaruh pada berjalannya proyek dan menjadi penentu keberhasilan suatu proyek perangkat lunak. Kegagalan estimasi biaya dalam perencanaan proyek perangkat lunak dapat menyebabkan proyek tidak berjalan dengan baik dan menimbulkan kerugian bagi perusahaan. Oleh karena itu, banyak peneliti sampai saat ini masih mencari dan melakukan penelitian untuk mendapatkan estimasi terbaik. Berbagai metode diusulkan untuk mendapatkan ketepatan akurasi dengan memperhatikan faktor-faktor estimasi biaya. Tujuan penelitian ini adalah membuat Systematic Literature Review (SLR) yang berisi rangkuman dan analisis perkembangan penelitian terbaru tentang estimasi biaya pada perangkat lunak, khususnya pada metode yang digunakan serta faktor-faktor yang mempengaruhi. Penelitian ini berhasil mengkaji 21 penelitian lain dalam lima tahun terakhir (2015-2020) dan didapatkan 24 metode usulan yang terbagi menjadi tiga jenis metode yang sering digunakan dalam melakukan estimasi biaya perangkat lunak yaitu nonparametrik, parametrik dan semiparametrik. Selain itu, penelitian ini juga berhasil menemukan metode dan kombinasi metode terbaik berdasarkan ketepatan akurasi beserta lima faktor utama yang mempengaruhi estimasi biaya sehingga dapat digunakan para peneliti atau praktisi lain untuk mengembangkan estimasi biaya pada proyek perangkat lunak. AbstractCost estimation has an important role because it affects the project’s progress and determines the success of a software project. Failure to estimate costs in software project planning can cause the project to not run well and cause losses to the company. Therefore, many researchers are still looking for and researching to get the best estimation by considering the cost estimation factors. The purpose of this study is to create a Systematic Literature Review (SLR) which contains a summary and analysis of the latest research developments on cost estimation in software, especially in the methods used and the factors that affect cost estimation. This study successfully reviewed 21 other studies in the last five years (2015-2020) and obtained 24 planning methods which are divided into three types of methods that are often used in conducting software cost research, namely nonparametric, parametric and semiparametric. Besides, this study also succeeded in finding the best method and combination of methods based on best accuracy, namely COCOMO II and the combination of Genetic Algorithm and Artificial Bee Colony, along with the five main factors that influence cost estimation so that it can be used by researchers or other practitioners to develop cost estimates for software projects.

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Software Cost Estimation – A Comparative Study of COCOMO-II and Bailey-Basili Models

Cited by 7 publications

References 8 publications

A Model for Total Cost Determination in Open-Source Software Ownership: Case of Kenyan Universities’ Learning Management System

A Model for Total Cost Determination in Open-Source Software Ownership: Case of Kenyan Universities’ Learning Management System

Software Cost and Effort Estimation: Current Approaches and Future Trends

Analisis Metode Estimasi Biaya pada Perangkat Lunak Beserta Faktor-Faktor yang Mempengaruhi : A Systematic Literature Review

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