An Investigation into the Suitability of k-Nearest Neighbour (k-NN) for Software Effort Estimation

Abstract

Software effort estimation is an increasingly significant field, due to the overwhelming role of software in today’s global market. Effort estimation involves forecasting the effort in person-months or hours required for developing a software. It is vital to ideal planning and paramount for controlling the software development process. However, there is presently no optimal method to accurately estimate the effort required to develop a software system. Inaccurate estimation leads to poor use of resources and perhaps failure of the software project. Effort estimation also plays a key role in deducing cost of a software project. Software cost estimation includes the generation of the effort estimates and project duration to predict cost required to develop software project. Thus, effort is very essential and there is always need to enhance the accuracy as much as possible. This study evaluates and compares the potential of Constructive COst MOdel II (COCOMO II) and k-Nearest Neighbor (k-NN) on software project dataset. By the analysis of results received from each method, it may be concluded that the proposed method k-NN yields better performance over the other technique utilized in this study.

Authors and Affiliations

Razak Olu-Ajayi

Keywords

Related Articles

A Tri-Level Industry-Focused Learning Approach for Software Engineering Management

Most engineering classes in higher education rely heavily on the traditional lecture format, despite the fact that a number of investigations have shown that lectures, even when given by good lecturers, have limited succ...

Relationship Analysis on the Experience of Hospitalised Paediatric Cancer Patient in Malaysia using Text Analytics Approach

The purpose of this study is to analyse the keyword relationships of paediatric cancer patient’s experiences whilst being hospitalised during the treatment session. This study collects data through 40 days of observation...

Optimizing the Hyperparameter of Feature Extraction and Machine Learning Classification Algorithms

The process of assigning a quantitative value to a piece of text expressing a mood or effect is called Sentiment analysis. Comparison of several machine learning, feature extraction approaches, and parameter optimization...

Cross-Layer-Based Adaptive Traffic Control Protocol for Bluetooth Wireless Networks

Bluetooth technology is particularly designed for a wireless personal area network that is low cost and less energy consuming. Efficient transmission between different Bluetooth nodes depends on network formation. An ine...

Cloud-Based Processing on Data Science for Visualization

The big data processing and visualization have the challenge on method and process. The volume, variety, velocity, and veracity in the big data need to handle for visualizing the data. The research work investigates, des...

Download PDF file
  • EP ID EP259599
  • DOI 10.14569/IJACSA.2017.080628
  • Views 105
  • Downloads 0

How To Cite

Razak Olu-Ajayi (2017). An Investigation into the Suitability of k-Nearest Neighbour (k-NN) for Software Effort Estimation. International Journal of Advanced Computer Science & Applications, 8(6), 227-233. https://europub.co.uk/articles/-A-259599