scholarly journals A Proposal of Effort Estimation Method for Information Mining Projects Oriented to SMEs

2013 ◽  
pp. 58-74 ◽  
Author(s):  
Pablo Pytel ◽  
Paola Britos ◽  
Ramón García-Martínez
Keyword(s):  
Estimation Method ◽  
Effort Estimation ◽  
Information Mining ◽  
Mining Projects

Feasibility and effort estimation models for medium and small size information mining projects

2015 ◽  
Vol 47 ◽  
pp. 1-14 ◽  
Author(s):  
Pablo Pytel ◽  
Alejandro Hossian ◽  
Paola Britos ◽  
Ramón García-Martínez
Keyword(s):  
Effort Estimation ◽  
Information Mining ◽  
Size Information ◽  
Mining Projects ◽  
Estimation Models

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.

scholarly journals Application of Fuzzy Sets to the Expert Estimation of Scrum-Based Projects

Symmetry ◽  
2019 ◽  
Vol 11 (8) ◽  
pp. 1032 ◽  
Author(s):  
Rola ◽  
Kuchta
Keyword(s):  
Case Studies ◽  
Fuzzy Numbers ◽  
Estimation Method ◽  
Human Interaction ◽  
Effort Estimation ◽  
It Projects ◽  
Quality Estimation ◽  
Symmetry Principle ◽  
Expert Estimation ◽  
Estimation Quality

The paper is basically dedicated to the problem of effort estimation for the Product Backlog items of IT projects led accordingly to the Scrum framework. The effort estimation issue is important, because low quality estimation decreases the efficiency of project implementation. The paper proposes an estimation method for the Product Backlog items of Scrum-based IT projects (which can be adapted also to other projects), which has two original elements with respect to the state of art in Scrum estimation: the usage of fuzzy numbers and strict rules for consensus forming, combined with a space for human interaction. The assumptions of the method should be complied with and were formulated on the basis of literature and authors experience. Two case studies were used for an initial method validation. The case studies confirmed a high potential of the method to increase estimation quality in Scrum-based projects, as well as in other project types. The case studies were conducted using research methods fulfilling the symmetry principle. The paper is thus an example of symmetry in management research.

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.

Application of Function Point Estimating

2014 ◽  
Vol 644-650 ◽  
pp. 3357-3360
Author(s):  
Chang Hong Zhou
Keyword(s):  
Data Gathering ◽  
Estimation Method ◽  
Effort Estimation ◽  
Integrated Monitoring ◽  
Point Counts ◽  
Point Analysis ◽  
Function Point ◽  
Monitoring Module ◽  
External Interface ◽  
High Level

Function point estimating is an important method for system of effort estimation. This article is based on a telecommunication surveillance module system-integrated monitoring module as example. It explains how this estimation method is applied in the project measurement process in detail.Function Point AnalysisFunction point analysis evaluates the functionality of a software system from the software end users perspective. Software functionality comes down to five basic functional elements[1], two of which represent end user demand for data: internal logical files (ILF) and external interface files (EIF). The other three are data gathering and processing features: external inputs (EI), external outputs (EO), external inquiries (EQ)[2].To determine the complexity of each functional element, the following data items are defined: record element type (RET), file type referenced, (FTR), data e1ement type (DET)[3]. To determine all functionalities complexity level, each data and transactional capabilities is assigned with low, average and high level based on standard matrix, see table 1 complexity matrix[4]. After determining the complexity of each feature, using the complexity value defined in table 2[5] multiply by the corresponding function point counts, accumulate to get the totals.Table 1: complexity matrixTable 2: IFPUG unadjusted function point basis

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