Using Extremely Simplified Functional Size Measures for Effort Estimation

Mobile applications affect our everyday activities and have become more and more information centric. Effort estimation for mobile application is an essential factor to consider in the development cycle. Due to feature complexities and size, effort estimation of mobile applications poses a continued challenge for developers. This paper attempts to adapt COSMIC Function Point and Unified Modeling Language (UML) techniques to estimate the size of a given mobile application. The COSMIC concepts capture data movements of the functional processes whereas the UML class analyzes them. We utilize the Use Case Diagrams, sequence diagrams and class diagrams for mapping the Function user requirements for sizing mobile applications. We further present a new size measurement technique; Unadjusted Mobile COSMIC Function points (UMCFP) to get the functional size of mobile application using Mobile Complex Factors as an input. In this study eight mobile applications were analyzed using UMCFP, Function Point Analysis and COSMIC Function Point. The results were compared with the actual size of previous Mobile application projects.

Download Full-text

Impact of Base Functional Component Types on Software Functional Size Based Effort Estimation

Product-Focused Software Process Improvement - Lecture Notes in Computer Science ◽

10.1007/978-3-540-69566-0_9 ◽

2008 ◽

pp. 75-89 ◽

Cited By ~ 16

Author(s):

Luigi Buglione ◽

Cigdem Gencel

Keyword(s):

Effort Estimation ◽

Functional Component ◽

Functional Size

Download Full-text

AN EXPLORATION OF FUNCTIONAL SIZE BASED EFFORT ESTIMATION MODELS

International Journal of Software Engineering and Knowledge Engineering ◽

10.1142/s0218194011005347 ◽

2011 ◽

Vol 21 (03) ◽

pp. 413-429 ◽

Cited By ~ 1

Author(s):

SECKIN TUNALILAR ◽

ONUR DEMIRORS

Keyword(s):

Neural Network ◽

Artificial Neural Network ◽

Regression Analysis ◽

Measurement Unit ◽

Effort Estimation ◽

Total Size ◽

Generic Models ◽

Functional Components ◽

Estimation Models ◽

Functional Size

A number of methods have been proposed to build a relationship between effort and size. These models are generally based on regression analysis and a widely accepted model is not yet available. Although in some sizing methods, such as MKII and IFPUG, different multipliers for the base functional components (BFC) exist, their origin and the purpose of their usage are undefined. The COSMIC method does not treat components separately and assigns the same measurement unit to each of them. In this study we used the Artificial Neural Network and regression based methods to create effort estimation models that take the four components of the COSMIC method into consideration. In the research we compared several functional size based effort models in terms of accuracy using a reliable company dataset. These models comprised not only the generic models proposed in the literature or currently in use, but also specific models that we generated using our dataset with a single and multi-variate regression analysis and the ANN method. We also explored the effect of functional similarity (FS) using our specific models. We found that using BFC instead of total size improved effort estimation models and the ANN method is a useful approach to calibrate these components according to the company characteristics.

Download Full-text

Ontology-Oriented Software Effort Estimation System for E-commerce Applications Based on Extreme Programming and Scrum Methodologies

The Computer Journal ◽

10.1093/comjnl/bxy141 ◽

2019 ◽

Vol 62 (11) ◽

pp. 1605-1624 ◽

Cited By ~ 2

Author(s):

Muhammad Adnan ◽

Muhammad Afzal ◽

Khadim Hussain Asif

Keyword(s):

Description Logic ◽

Extreme Programming ◽

Effort Estimation ◽

Software Effort Estimation ◽

Software Projects ◽

Measurement Methodology ◽

Estimation System ◽

Comparative Results ◽

Project History ◽

Functional Size

Abstract Presently, software industry is severely suffering from inaccurate effort estimation and inadequate unstructured or semi-structured project history management. In fact, both are difficult to accomplish and hence badly impact the software projects. We proposed improvements in the effort estimation and the project history management of e-commerce projects focusing on Extreme Programing (XP) and Scrum methodologies using ontology models in our software effort estimation system. Proposed system infers suitable estimate in the form of time, resources and lessons learnt as per the project leader’s requirements by using description logic and HermiT reasoner. To validate our approach, we have performed a case study comprising 20 Business-to-Consumer (B2C) web projects and performed comparative analysis on the collected efforts in both XP and Scrum contexts by applying (Mean Magnitude of Relative Error) MMRE and PRED(25) prediction accuracy measures. Likewise, software functional size of understudy e-commerce projects was measured using COSMIC functional size measurement methodology. Regression analysis of relations among actual COSMIC function points, estimated effort, and actual effort spent for the projects show better significance-F and R2 values for our approach. The comparative results show that overall proposed approach provides accurate estimates and significantly improves over planning poker and delphi methods by 10% and 30%, respectively.

Download Full-text