Elsevier

Applied Soft Computing

Volume 11, Issue 2, March 2011, Pages 2260-2270
Applied Soft Computing

Fuzzy Emotional COCOMO II Software Cost Estimation (FECSCE) using Multi-Agent Systems

https://doi.org/10.1016/j.asoc.2010.08.006Get rights and content

Abstract

Software development cost estimation is important for effective project management. Many models have been introduced to predict software development cost. In this paper, a novel emotional COnstructive COst MOdel II (COCOMO II) has been proposed for software cost estimation. In COCOMO II only the project characteristics are considered, whereas the characteristics of team members are also important factors. This paper presents a model, namely FECSCE, which in addition to project characteristics considers the communication skills, personality, mood and capabilities of team members. In FECSCE, we have used a Multi-Agent System (MAS) in order to simulate team communications.

Introduction

One of the most critical tasks in managing software projects is software cost estimation [1]. The software industry is very competitive to establish the market with accurate cost estimation [2]. It can help industries to better analyze the feasibility of a project and to effectively manage the software development process [3]. There is no approach proven to have effectively and consistently predicted software output metrics [3]. There are a number of methods used to estimate the cost of various projects. COCOMO is known as a popular method in this respect.

Having an agile team is a significant element for the success of a complex software project. A project is the same as a social system where personal and cooperative characteristics play a key role in achieving goals. The members of any projects have emotions such as anger, fear, joy, sadness and surprise [4]. These emotions are positive or negative at the start of the project [4]. The positive emotion is related to the joy of having an interesting assignment, meeting new people and working in a new team. The negative emotion is related to the fear of a new challenge in a new work and new responsibility in a team. Emotions, the degree of cooperation and the suitability of the assigned tasks with the capability of team members are parameters affecting project properties (e.g. cost) [5]. By using simulation tools, we can simulate the operations of a team in a given project to estimate its cost [6].

In the previous cost estimations, only the project characteristics have been considered. In this paper a novel emotional COCOMO II model has been proposed. We present the FECSCE, Fuzzy Emotional COCOMO II Software Cost Estimation. The major difference between this model and previous ones is that the FECSCE incorporates characteristics of team members (i.e. communication skills, personality, mood and capabilities) into the COCOMO II model. In this study, fuzzy agents and Multi-Agent Systems have been used to simulate personal characteristics and interactions in a team.

This study has been inspired from a web-based digital library project in which all team members were students and the authors were involved in. The authors could view the effect of personality and emotional factors in the productivity of team members. Since the data of this project was available, we used it as the pilot test for the configuration of fuzzy sets and membership functions, and the definition of the internal variables of a team member.

Section 2 of the paper, describes the background of the study including the COCOMO model, fuzzy systems, software agents, personality, mood, and emotion, and related work; Section 3 describes the FECSCE model. In Section 4, the design of the FECSCE is discussed. Section 5 presents the implementation and evaluation of the FECSCE and finally Section 6 presents the conclusion and the perspective of future works.

Section snippets

The COCOMO

The COnstructive COst MOdel, COCOMO, was introduced by Boehm [7]. It has become one of the most widely used software cost estimation models in the industry. To support new life cycles and capability, it has evolved into a more comprehensive estimation model, called COCOMO II [8], [9].

For the COCOMO II models, three different sizing options are available: object points, function points, and lines of source code. The COCOMO II application composition model uses object points. Object Point

FECSCE: Fuzzy Emotional COCOMO II Software Cost Estimation model

The main goal of the FECSCE model considers team characteristics in such a way as to render the COCOMO II project cost estimation more accurate. There are two kinds of agent in FECSCE: “Team Member Agent” (TMA) and “Simulator Agent” (SA). TMA is a fuzzy agent for the simulation of a team member. Multi-TMA can simulate a team and TMAs communications can reflect intra-communication of the team. In this model, only the direction of communications is considered not the quality of the communications

FECSCE fuzzy inference

We have utilized the Tsukamoto fuzzy inference system in the three elements of each TMA. Tsukamoto aggregates each rule's output by the method of weighted average and the output is always crisp even when the inputs are fuzzy [16]. Considering that the transition of Gaussian MF in the intervals is smoother and more natural than triangular MF, we have utilized Gaussian MF in the variables of COCOMO [31] (prod and problem difficulty). For the variables, which need superior transition, we have

FECSCE simulator

The FECSCE simulator uses FuzzyJ package [47] to implement the fuzzy inference system and JADE4 [48] to implement the Multi-Agent System (MAS). The developed software includes screens for team members’ characteristics, project information, simulation results, and the team relationship graph. A sample screen shot of team members’

Conclusion

Accurate cost estimation is important for effective project management. Most of previous studies utilized fuzzy systems, Multi-Agent Systems and CMMI to improve cost estimation. One of the problems of the previous cost estimation studies is that they only considered project's characteristics not team members’ characteristics. The FECSCE was discussed as a novel cost estimation model, which includes the team members’ characteristics as another factor in project cost estimation. This novel model

Acknowledgements

We appreciate IRISA and FASA Companies, which permitted us to access their teams’ and projects’ information.

References (50)

  • R. Dillibabu et al.

    Cost estimation of a software product using COCOMO II.2000 model—a case study

    International Journal of Project Management

    (2004)
  • R. Gareis

    Emotional project management

  • J.M. Miranda et al.

    Emotions in human and artificial intelligence

    Computers in Human Behavior

    (2005)
  • J.M. Miranda et al.

    Simulation of work teams using a multi-agent system

  • B.W. Boehm

    Software Engineering Economics

    (1981)
  • B.W. Boehm

    Anchoring the software process

    IEEE Software

    (1996)
  • B.W. Boehm et al.

    Software Cost Estimation in COCOMO II

    (2000)
  • COCOMO II Model Definition Manual

    (2000)
  • T. Takagi et al.

    Fuzzy identification of systems and its application to modeling and control

    IEEE Transactions on Systems, Man, and Cybernetics

    (1985)
  • Y. Tsukamoto

    An Approach to Fuzzy Reasoning Method

  • P. Melin et al.

    Type-1 fuzzy logic

  • N. Ghasem-Aghaee et al.

    Towards fuzzy agents with dynamic personality for human behavior simulation

  • E.J. Phares

    Introduction to Psychology

    (1991)
  • P.T. Costa et al.

    Normal personality assessment in clinical practice: the NEO personality inventory

    Psychological Assessment

    (1992)
  • M.R. Barrick et al.

    The big five personality dimensions and job performance: a meta-analysis

    Personnel Psychology

    (1991)
  • Cited by (0)

    View full text