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Optimizing design parameters of fuzzy model based COCOMO using genetic algorithms

  • Sonia ChhabraEmail author
  • Harvir Singh
Original Research
  • 1 Downloads

Abstract

Software development process is a series of planned activities undertaken to design a software product. The major concern in this process is estimation of cost and effort. Algorithmic as well as non algorithmic techniques are used to estimate cost and effort. Algorithmic techniques use mathematical equations; however, in case of imprecise information these techniques are overpowered by non algorithmic techniques. Intermediate COCOMO suffers from a problem of imprecise definition of cost drivers resulting in inaccurate estimations. Thus in the current research, implementation of non algorithmic modelling is carried out using soft computing techniques like fuzzy logic and genetic algorithms. The fuzzy approach is implemented to design a fuzzy model for each cost driver. The fuzzy model handles imprecise and ambiguous definition of input ranges of cost drivers. Selection of parameters characterising fuzzy sets in proposed fuzzy model is further optimized using genetic algorithms. The proposed model is tested on COCOMO NASA dataset and COCOMO NASA2 dataset using MATLAB. The improvement in performance of proposed optimized model is measured in terms of mean magnitude of relative error (MMRE) and Pred (25%). A significant improvement in %MMRE and Pred (25%) justifies the suitability of genetic algorithms for optimizing proposed fuzzy model.

Keywords

Fuzzy logic Genetic algorithms Genetic tuning Software cost estimation Soft computing techniques 

Abbreviations

ACO

Ant colony optimization

COCOMO

Constructive cost model

DB

Data base

EAF

Effort adjustment factor

EM

Effort multiplier

FIS

Fuzzy inference system

GA

Genetic algorithms

KB

Knowledge base

RB

Rule base

MF

Membership function

MMRE

Mean magnitude of relative error

MRE

Magnitude of relative error

TS

Takagi–Sugeno

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Copyright information

© Bharati Vidyapeeth's Institute of Computer Applications and Management 2019

Authors and Affiliations

  1. 1.Uttrakhand Technical UniversityDehradunIndia
  2. 2.IIMT UniversityMeerutIndia

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