Regression Analysis Based Software Effort Estimation Method

2016 ◽  
Vol 26 (05) ◽  
pp. 807-826 ◽  
Author(s):  
Fatih Yücalar ◽  
Deniz Kilinc ◽  
Emin Borandag ◽  
Akin Ozcift
Keyword(s):  
Regression Analysis ◽  
Linear Regression ◽  
Linear Regression Analysis ◽  
Estimation Method ◽  
Estimation Methods ◽  
Estimation Accuracy ◽  
Development Effort ◽  
Software Project ◽  
Effort Estimation ◽  
Software Effort Estimation

Estimating the development effort of a software project in the early stages of the software life cycle is a significant task. Accurate estimates help project managers to overcome the problems regarding budget and time overruns. This paper proposes a new multiple linear regression analysis based effort estimation method, which has brought a different perspective to the software effort estimation methods and increased the success of software effort estimation processes. The proposed method is compared with standard Use Case Point (UCP) method, which is a well-known method in this area, and simple linear regression based effort estimation method developed by Nassif et al. In order to evaluate and compare the proposed method, the data of 10 software projects developed by four well-established software companies in Turkey were collected and datasets were created. When effort estimations obtained from datasets and actual efforts spent to complete the projects are compared with each other, it has been observed that the proposed method has higher effort estimation accuracy compared to the other methods.

Size and Effort Estimation Based on Problem Domain Measures for Object-Oriented Software

2018 ◽  
Vol 28 (02) ◽  
pp. 219-238 ◽  
Author(s):  
Tülin Erçelebi Ayyildiz ◽  
Altan Koçyiğit
Keyword(s):  
Regression Analysis ◽  
Linear Regression ◽  
Linear Regression Analysis ◽  
Object Oriented ◽  
Development Effort ◽  
Effort Estimation ◽  
Size Estimation ◽  
Problem Domain ◽  
Estimation Model ◽  
Software Projects

This paper analyzes the correlations between the problem domain measures such as the number of distinct nouns and distinct verbs in the requirements artifacts and the solution domain measures such as the number of software classes and methods in the corresponding object-oriented software. For this purpose, 14 completed software development projects of a CMMI Level-3 certified defense industry company have been analyzed. The observed strong correlation is taken as the indication of linear relationship between the measures and a size estimation model based on linear regression analysis is proposed. Prediction performance of the method is analyzed on the 14 software projects. Moreover, it has been observed that there is a high correlation between the problem domain measures and the development effort. Therefore, the linear regression analysis is also used to estimate the effort in terms of the problem domain measures. The effort estimations are also evaluated and compared with the efforts predicted using the size measured by the COSMIC Function Point (CFP) method. The results show that the proposed method provides more accurate effort estimates compared to the effort estimated by using CFP size measurement.

scholarly journals Keberhasilan Progam Pengembangan Usaha Agribisnis Perdesaan (Puap) Di Kecamatan Sungai Kunyit Kabupaten Mempawah

2019 ◽  
Vol 7 (1) ◽  
Author(s):  
Syamsuria, Novira Kusrini, Dewi Kurniati
Keyword(s):  
Regression Analysis ◽  
Linear Regression ◽  
Multiple Linear Regression ◽  
Linear Regression Analysis ◽  
Development Program ◽  
Multiple Linear Regression Analysis ◽  
Development Effort ◽  
Development Programs ◽  
Entrepreneurial Spirit

This study aimed to analyze the influence of the entrepreneurial spirit of farmer group caretaker to the success of rural agribusiness development program. The analysis used in this research is multiple linear regression analysis. This study uses 36 board of farmer group in Sei Kunyit, Mempawah District. The results showed that entrepreneurship has a positive and significant value to the success of the rural agribusiness development program. While the application of management has a negative value and not significant to the success of rural agribusiness development program in Sei Kunyit, Mempawah District. Attribute entrepreneurship provides the effect of 0.261. This sshows that for the success of rural agribusiness development programs to consider and foster the entrepreneurial spirit of farmer group caretaker.Keywords :  Entrepreneurial Spirit, Applicaton of Busness Magement, Success of Rural Agrbusiness Development Effort

scholarly journals Improving Effort Estimation by Voting Software Estimation Models

2009 ◽  
Vol 2009 ◽  
pp. 1-8 ◽  
Author(s):  
Luiz Fernando Capretz ◽  
Venus Marza
Keyword(s):  
Estimation Accuracy ◽  
Data Repository ◽  
Development Effort ◽  
Software Project ◽  
Effort Estimation ◽  
Software Projects ◽  
Software Estimation ◽  
Software Development Effort ◽  
Commercial Purpose ◽  
Estimation Models

Estimating software development effort is an important task in the management of large software projects. The task is challenging, and it has been receiving the attentions of researchers ever since software was developed for commercial purpose. A number of estimation models exist for effort prediction. However, there is a need for novel models to obtain more accurate estimations. The primary purpose of this study is to propose a precise method of estimation by selecting the most popular models in order to improve accuracy. Consequently, the final results are very precise and reliable when they are applied to a real dataset in a software project. Empirical validation of this approach uses the International Software Benchmarking Standards Group (ISBSG) Data Repository Version 10 to demonstrate the improvement in software estimation accuracy.

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 Enhancing Delphi Method with Algorithmic Estimates for Software Effort Estimation: An Experimental Study

2021 ◽  
Vol 12 (04) ◽  
pp. 01-18
Author(s):  
Tharwon Arnuphaptrairong
Keyword(s):  
Delphi Method ◽  
Cost Estimation ◽  
Expert Judgment ◽  
Delphi Process ◽  
Estimation Methods ◽  
Estimation Accuracy ◽  
Effort Estimation ◽  
Software Effort Estimation ◽  
Delphi Experiment ◽  
Individual Expert

Literature review shows that more accurate software effort and cost estimation methods are needed for software project management success. Expert judgment and algorithmic model estimation are two predominant methods discussed in the literature. Both are reported almost at the comparable level of accuracy performance. The combination of the two methods is suggested to increase the estimation accuracy. Delphi method is an encouraging structured expert judgment method for software effort group estimation but surprisingly little was reported in the literature. The objective of this study is to test if the Delphi estimates will be more accurate if the participants in the Delphi process are exposed to the algorithmic estimates. A Delphi experiment where the participants in the Delphi process were exposed to three algorithmic estimates –Function Points, COCOMO estimates, and Use Case Points, was therefore conducted. The findings show that the Delphi estimates are slightly more accurate than the statistical combination of individual expert estimates, but they are not statistically significant. However, the Delphi estimates are statistically significant more accurate than the individual estimates. The results also show that the Delphi estimates are slightly less optimistic than the statistical combination of individual expert estimates but they are not statistically significant either. The adapted Delphi experiment shows a promising technique for improving the software cost estimation accuracy.

scholarly journals Applying COCOMO II for a DO-178C Safety-Critical Software Effort Estimation

2019 ◽  
Author(s):  
Lucas Pereira dos Santos ◽  
Maurício Ferreira
Keyword(s):  
Estimation Accuracy ◽  
Development Effort ◽  
Effort Estimation ◽  
Software Effort Estimation ◽  
Software Projects ◽  
Software Application ◽  
Safety Critical ◽  
Software Development Effort ◽  
Software Practitioners ◽  
Cocomo Ii

This paper provides a real example of applying COCOMO II as an estimation technique for the required software development effort in a safety-critical software application project following the DO-178C processes. The main goal and contribution of the case study is to support the research on software effort estimation and to provide software practitioners with useful data based on a real project. We applied the method as it is, by correlating the effort multiplier factors with the complexity and objectives introduced by the DO-178C level A application, resulting in an estimated effort. The rationales for each scale factor and effort multiplier selection were also described in detail. By comparing the estimated values with the actual required data, we found a magnitude of relative error (MRE) of 40% and provided alternatives for future work in order to increase the effort estimation accuracy in safety-critical software projects.

scholarly journals Software Development Effort Estimation Using Regression Fuzzy Models

2019 ◽  
Vol 2019 ◽  
pp. 1-17 ◽  
Author(s):  
Ali Bou Nassif ◽  
Mohammad Azzeh ◽  
Ali Idri ◽  
Alain Abran
Keyword(s):  
Fuzzy Logic ◽  
Regression Analysis ◽  
Statistical Tests ◽  
Critical Role ◽  
Machine Learning Techniques ◽  
Development Effort ◽  
Effort Estimation ◽  
Software Effort Estimation ◽  
Inference System ◽  
Logic Models

Software effort estimation plays a critical role in project management. Erroneous results may lead to overestimating or underestimating effort, which can have catastrophic consequences on project resources. Machine-learning techniques are increasingly popular in the field. Fuzzy logic models, in particular, are widely used to deal with imprecise and inaccurate data. The main goal of this research was to design and compare three different fuzzy logic models for predicting software estimation effort: Mamdani, Sugeno with constant output, and Sugeno with linear output. To assist in the design of the fuzzy logic models, we conducted regression analysis, an approach we call “regression fuzzy logic.” State-of-the-art and unbiased performance evaluation criteria such as standardized accuracy, effect size, and mean balanced relative error were used to evaluate the models, as well as statistical tests. Models were trained and tested using industrial projects from the International Software Benchmarking Standards Group (ISBSG) dataset. Results showed that data heteroscedasticity affected model performance. Fuzzy logic models were found to be very sensitive to outliers. We concluded that when regression analysis was used to design the model, the Sugeno fuzzy inference system with linear output outperformed the other models.

scholarly journals Tuning of Cost Drivers by Significance Occurrences and Their Calibration with Novel Software Effort Estimation Method

2013 ◽  
Vol 2013 ◽  
pp. 1-10 ◽  
Author(s):  
Brajesh Kumar Singh ◽  
Shailesh Tiwari ◽  
K. K. Mishra ◽  
A. K. Misra
Keyword(s):  
Estimation Method ◽  
Project Work ◽  
Estimation Accuracy ◽  
Effort Estimation ◽  
Software Effort Estimation ◽  
Software Projects ◽  
Cost Drivers ◽  
Binary Genetic Algorithm ◽  
The Cost ◽  
Engineering Projects

Estimation is an important part of software engineering projects, and the ability to produce accurate effort estimates has an impact on key economic processes, including budgeting and bid proposals and deciding the execution boundaries of the project. Work in this paper explores the interrelationship among different dimensions of software projects, namely, project size, effort, and effort influencing factors. The study aims at providing better effort estimate on the parameters of modified COCOMO along with the detailed use of binary genetic algorithm as a novel optimization algorithm. Significance of 15 cost drivers can be shown by their impact on MMRE of efforts on original 63 NASA datasets. Proposed method is producing tuned values of the cost drivers, which are effective enough to improve the productivity of the projects. Prediction at different levels of MRE for each project reflects the percentage of projects with desired accuracy. Furthermore, this model is validated on two different datasets which represents better estimation accuracy as compared to the COCOMO 81 based NASA 63 and NASA 93 datasets.

scholarly journals Models for Predicting Development Effort of Small-Scale Visualization Projects

2018 ◽  
Vol 27 (3) ◽  
pp. 413-431
Author(s):  
M.A. Jayaram ◽  
T.M. Kiran Kumar ◽  
H.V. Raghavendra
Keyword(s):  
Neural Network ◽  
Linear Regression ◽  
Network Models ◽  
Small Scale ◽  
Development Effort ◽  
Software Project ◽  
Effort Estimation ◽  
Neural Network Models ◽  
Grade Point ◽  
Postgraduate Students

Abstract Software project effort estimation is one of the important aspects of software engineering. Researchers in this area are still striving hard to come out with the best predictive model that has befallen as a greatest challenge. In this work, the effort estimation for small-scale visualization projects all rendered on engineering, general science, and other allied areas developed by 60 postgraduate students in a supervised academic setting is modeled by three approaches, namely, linear regression, quadratic regression, and neural network. Seven unique parameters, namely, number of lines of code (LOC), new and change code (N&C), reuse code (R), cumulative grade point average (CGPA), cyclomatic complexity (CC), algorithmic complexity (AC), and function points (FP), which are considered to be influential in software development effort, are elicited along with actual effort. The three models are compared with respect to their prediction accuracy via the magnitude of error relative to the estimate (MER) for each project and also its mean MER (MMER) in all the projects in both the verification and validation phases. Evaluations of the models have shown MMER of 0.002, 0.006, and 0.009 during verification and 0.006, 0.002, and 0.002 during validation for the multiple linear regression, nonlinear regression, and neural network models, respectively. Thus, the marginal differences in the error estimates have indicated that the three models can be alternatively used for effort computation specific to visualization projects. Results have also suggested that parameters such as LOC, N&C, R, CC, and AC have a direct influence on effort prediction, whereas CGPA has an inverse relationship. FP seems to be neutral as far as visualization projects are concerned.

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