Abstract

The estimation of software effort is an essential and crucial activity for the software development life cycle. It is a problem that often appears on the project of making a software. A poor estimate will result in a worse project management. Several software cost estimation models have been introduced to resolve this problem. Constructive Cost Model II (COCOMO II Model) is a most considerable and broadly used model in cost estimation. To estimate the cost of a software project, COCOMO II model uses cost drivers, scale factors and line of code. However, the model is still lacking in terms of accuracy. In this study, we investigate the influence of components and attributes to achieve new better accuracy improvement on COCOMO II model. We introduced the use of Particle Swarm Optimization (PSO) algorithm in optimizing the COCOMO II model parameters. The proposed method is applied on Turkish Software Industry dataset. The method achieves well result and deals proficient with inexplicit data input and further improve a reliability of the estimation method. The optimized MMRE result is 34.1939%. It can reduce 698.9461% and 104.876% errors from the basic COCOMO II model and Tabu Search coefficient significantly.

Original languageEnglish
Title of host publicationProceeding - 2017 3rd International Conference on Science in Information Technology
Subtitle of host publicationTheory and Application of IT for Education, Industry and Society in Big Data Era, ICSITech 2017
EditorsLala Septem Riza, Andri Pranolo, Aji Prasetyo Wibawa, Enjun Junaeti, Yaya Wihardi, Ummi Raba'ah Hashim, Shi-Jinn Horng, Rafal Drezewski, Heui Seok Lim, Goutam Chakraborty, Leonel Hernandez, Shah Nazir
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages29-34
Number of pages6
ISBN (Electronic)9781509058662
DOIs
Publication statusPublished - 1 Jul 2017
Event3rd International Conference on Science in Information Technology, ICSITech 2017 - Bandung, Indonesia
Duration: 25 Oct 201726 Oct 2017

Publication series

NameProceeding - 2017 3rd International Conference on Science in Information Technology: Theory and Application of IT for Education, Industry and Society in Big Data Era, ICSITech 2017
Volume2018-January

Conference

Conference3rd International Conference on Science in Information Technology, ICSITech 2017
Country/TerritoryIndonesia
CityBandung
Period25/10/1726/10/17

Keywords

  • cocomo II model
  • optimization
  • particle swarm optimization
  • software effort estimation
  • swarm intelligence

Fingerprint

Dive into the research topics of 'Optimizing COCOMO II parameters using particle swarm method'. Together they form a unique fingerprint.

Cite this