Design of software effort estimation models an approach based on linear genetic programming

2017 ◽  
Author(s):  
Roberto Sanchez ◽  
Diego P. Pinto-Roa
Keyword(s):  
Genetic Programming ◽  
Effort Estimation ◽  
Software Effort Estimation ◽  
Linear Genetic Programming ◽  
Estimation Models

SOFTWARE DEVELOPMENT EFFORT ESTIMATION USING CLASSICAL AND FUZZY ANALOGY: A CROSS-VALIDATION COMPARATIVE STUDY

2014 ◽  
Vol 13 (03) ◽  
pp. 1450013 ◽  
Author(s):  
FATIMA AZZAHRA AMAZAL ◽  
ALI IDRI ◽  
ALAIN ABRAN
Keyword(s):  
Software Development ◽  
Case Based Reasoning ◽  
Development Effort ◽  
Software Project ◽  
Effort Estimation ◽  
Software Effort Estimation ◽  
Software Projects ◽  
Software Development Effort ◽  
Research Questions ◽  
Estimation Models

Software effort estimation is one of the most important tasks in software project management. Of several techniques suggested for estimating software development effort, the analogy-based reasoning, or Case-Based Reasoning (CBR), approaches stand out as promising techniques. In this paper, the benefits of using linguistic rather than numerical values in the analogy process for software effort estimation are investigated. The performance, in terms of accuracy and tolerance of imprecision, of two analogy-based software effort estimation models (Classical Analogy and Fuzzy Analogy, which use numerical and linguistic values respectively to describe software projects) is compared. Three research questions related to the performance of these two models are discussed and answered. This study uses the International Software Benchmarking Standards Group (ISBSG) dataset and confirms the usefulness of using linguistic instead of numerical values in analogy-based software effort estimation models.

scholarly journals Optimizing Software Effort Estimation Models Using Firefly Algorithm

2015 ◽  
Vol 08 (03) ◽  
pp. 133-142 ◽  
Author(s):  
Nazeeh Ghatasheh ◽  
Hossam Faris ◽  
Ibrahim Aljarah ◽  
Rizik M. H. Al-Sayyed
Keyword(s):  
Firefly Algorithm ◽  
Effort Estimation ◽  
Software Effort Estimation ◽  
Estimation Models

scholarly journals Estimation Models Generation using Linear Genetic Programming

2009 ◽  
Vol 12 (3) ◽  
Author(s):  
Javier Martínez Canillas ◽  
Roberto Sánchez ◽  
Benjamín Barán
Keyword(s):  
Time Series ◽  
Evolutionary Algorithms ◽  
Genetic Programming ◽  
Price Index ◽  
Consumer Price Index ◽  
Decision Rules ◽  
Time Series Forecasting ◽  
Linear Genetic Programming ◽  
Estimation Techniques ◽  
Estimation Models

The use of decision rules and estimation techniques is increasingly common for decision mak-ing. In recent years studies were conducted which applies Genetic Programming (GP) to obtainrules to make predictions. A new branch in the area of Evolutionary Algorithms (EA) is LinearGenetic Programming (LGP). LGP evolves instructions sequences of an imperative programminglanguage. This paper proposes estimation models generation for time series forecasting using LGP.The forecasting result for the Consumer Price Index (CPI) and the price of soybeans per ton showsthe potential of this new proposal.

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