CONTENTS

KNOWLEDGE ENGINEERING: PRINCIPLES AND TECHNIQUES
Proceedings of the International Conference on Knowledge Engineering,
Principles and Techniques, KEPT2009
Cluj-Napoca (Romania), July 2–4, 2009, pp. 206–210
SOFTWARE COST ESTIMATION MODEL BASED ON NEURAL
NETWORKS
C ĂLIN ENĂCHESCU(1) AND DUMITRU R ĂDOIU(2)
Abstract. Software engineering is providing estimation models in order to evaluate
the costs for important phases of software development such as requirements
analysis, high and low level design, development, testing, deployment and maintenance.
The paper proposes a software cost estimation model based on neural
networks and compares it with traditional cost estimation models. The paper
argues that there are at least two considerable advantages for the neural network
model: neural networks can learn from previous experience and secondly, neural
networks can discover a complete set of relations between dependent variables
(software cost, software size, required effort, etc.) and independent variables
(complexity of the project, number of inputs and outputs, files, various cost
drives etc.).
1. Software cost estimation
A very critical aspect for suppliers and clients in a software project is the accuracy
of the software project cost estimation [3]. This accuracy represents the basic
argument in contract negotiation, project plan and project controls. Accuracy has a
great influence on the following items [13]:
• Prioritization and classification of the software development projects;
• Accurate estimation of the required human resources;
• Evaluation of the financial impact determined by the chance requests;
• Efficient control of the project based on realistic and efficient resource allocation;
• Keeping the project cost in the reasonable limits as agreed with the client.
The estimation of a project cost (measured in currency) is based (in broad lines)
on the following estimations [5]:
• Project size (e.g. measured in functional points);
• Project effort (e.g. measured in person/months);
• Project duration (e.g. measured in working days);
• Project schedule (measured in calendar days);
• Other cost drivers (e.g. labor cost, organizational overhead, procurement
costs);
2000 Mathematics Subject Classification. 68N30, 68T05, 62M45.
Key words and phrases. software development cost estimation, software metrics, neural networks.
206
c○2009 Babe¸s-Bolyai University, Cluj-Napoca