Predicting software project effort: A grey relational analysis based method

This is the post-print version of the final paper published in Expert Systems with Applications. The published article is available from the link below. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. Copyright @ 2011 Elsevier B.V.The inherent uncertainty of the software development process presents particular challenges for software effort prediction. We need to systematically address missing data values, outlier detection, feature subset selection and the continuous evolution of predictions as the project unfolds, and all of this in the context of data-starvation and noisy data. However, in this paper, we particularly focus on outlier detection, feature subset selection, and effort prediction at an early stage of a project. We propose a novel approach of using grey relational analysis (GRA) from grey system theory (GST), which is a recently developed system engineering theory based on the uncertainty of small samples. In this work we address some of the theoretical challenges in applying GRA to outlier detection, feature subset selection, and effort prediction, and then evaluate our approach on five publicly available industrial data sets using both stepwise regression and Analogy as benchmarks. The results are very encouraging in the sense of being comparable or better than other machine learning techniques and thus indicate that the method has considerable potential.National Natural Science Foundation of Chin

Effort Estimation Development Model for Web-Based Mobile Application Using Fuzzy Logic

Effort estimation becomes a crucial part in software development process because false effort estimation result can lead to delayed project and affect the successful of a project. This research proposes a model of effort estimation for web-based mobile application developed using object oriented approach. In the proposed model, functional size measurement of object oriented based web application named OOmFPWeb, web metric and mobile characteristic for web-based mobile application size measurement are combnined. The estimation process is done by using mamdani fuzzy logic method. To evaluate the proposed model, the comparison between OOmFPWeb as the variable that affect effort estimation for web-based mobile application and the proposed model are performed. The evaluation result shows that effort estimation for web-based mobile application with the proposed model is better than just using OOmFPWeb

Estimating, planning and managing Agile Web development projects under a value-based perspective

Context: The processes of estimating, planning and managing are crucial for software development projects, since the results must be related to several business strategies. The broad expansion of the Internet and the global and interconnected economy make Web development projects be often characterized by expressions like delivering as soon as possible, reducing time to market and adapting to undefined requirements. In this kind of environment, traditional methodologies based on predictive techniques sometimes do not offer very satisfactory results. The rise of Agile methodologies and practices has provided some useful tools that, combined with Web Engineering techniques, can help to establish a framework to estimate, manage and plan Web development projects. Objective: This paper presents a proposal for estimating, planning and managing Web projects, by combining some existing Agile techniques with Web Engineering principles, presenting them as an unified framework which uses the business value to guide the delivery of features. Method: The proposal is analyzed by means of a case study, including a real-life project, in order to obtain relevant conclusions. Results: The results achieved after using the framework in a development project are presented, including interesting results on project planning and estimation, as well as on team productivity throughout the project. Conclusion: It is concluded that the framework can be useful in order to better manage Web-based projects, through a continuous value-based estimation and management process.Ministerio de Economía y Competitividad TIN2013-46928-C3-3-

Complementing Measurements and Real Options Concepts to Support Inter-iteration Decision-Making in Agile Projects

Agile software projects are characterized by iterative and incremental development, accommodation of changes and active customer participation. The process is driven by creating business value for the client, assuming that the client (i) is aware of it, and (ii) is capable to estimate the business value, associated with the separate features of the system to be implemented. This paper is focused on the complementary use of measurement techniques and concepts of real-option-analysis to assist clients in assessing and comparing alternative sets of requirements. Our overall objective is to provide systematic support to clients for the decision-making process on what to implement in each iteration. The design of our approach is justified by using empirical data, published earlier by other authors

EffortEst- An Enhanced Software Effort Estimation by Analogy Method

Abstract:Over the past few years, large-scale software project development has become the point of growing interest to many organizations and thus, predicting the size, cost and effort of software projects has become a very significant task to project managers. Often inaccurate prediction results into software projects exceeding budget as well as being out of schedule. Therefore, software project managers have been introduced to numerous software tools and methods in recent years to automate their tasks. The paper presents some existing analogy-based software estimation tools used by project managers and these tools are critically analyzed to identify shortcomings. Finally an enhanced software effort estimation method is proposed. A system prototype named EffortEst has been implemented and evaluated based on the enhanced method. EffortEst provides the near-best estimation of software project effort with limited user intervention.Keywords: Software Effort Estimation, Analogy, Case- Based Reasoning, Prototype(Article history: Received 16 September 2016 and accepted 9 December 2016

A Review on Software Development and Project Estimation Process

Software Development is a term to enclose the processes of software engineering combined with the research and targets of software marketing to develop computer software products. As the development of software increases it required to estimate the projects. Estimation of the various resources is required, which is required for the conclusion of any project. Cost estimation is the important part of every type projects management and control. The Accurate cost estimation helps us complete the project within time and budget. One of the greatest challenges for a project leader is to successfully deliver on all aspects of a project both according to the client’s specifications and within the allotted budget. Accurate cost estimation helps to complete project within time and budget. In this paper we describe the development of the software according to last three decades and Software Development Priorities after that we studied about the software estimation process, its needs, its development and the steps required for the estimation of the software

Numerical Simulation and Design of Ensemble Learning Based Improved Software Development Effort Estimation System

This research paper proposes a novel approach to improving software development effort estimation by integrating ensemble learning algorithms with numerical simulation techniques. The objective of this study is to design an ensemble learning-based software development effort estimation system that leverages the strengths of multiple algorithms to enhance accuracy and reliability. The proposed system combines the power of ensemble learning, which involves aggregating predictions from multiple models, with numerical simulation techniques that enable the modelling and analysis of complex software development processes. A diverse set of software development projects is collected, encompassing various domains, sizes, and complexities. Ensemble learning algorithms such as Random Forest, Gradient Boosting, Bagging, and AdaBoost are selected for their ability to capture different aspects of the data and produce robust predictions. The proposed system architecture is presented, illustrating the flow of data and components. A model training and evaluation pipeline is developed, enabling the integration of ensemble learning and numerical simulation modules. The system combines the predictions generated by the ensemble models with the simulation results to produce more accurate and reliable effort estimates. The experimental setup involves a comprehensive evaluation of the proposed system. A real-world dataset comprising historical project data is utilized, and various performance metrics, including Mean Absolute Error (MAE) and Root Mean Squared Error (RMSE), are employed to assess the effectiveness of the system. The results and analysis demonstrate that the ensemble learning-based effort estimation system outperforms traditional techniques, showcasing its potential to enhance project planning and resource allocation

Calibration and Validation of the Sage Software Cost/Schedule Estimating System to United States Air Force Databases

This research entailed calibration and validation of the SAGE Software Cost/Schedule Estimating System, Version 1.7 as a means to improve estimating accuracy for DoD software-intensive systems, and thereby introduce stability into software system development. SAGE calibration consisted of using historical data from completed projects at the Space and Missile Systems Center (SMC) and the Electronic Systems Center (ESC) to derive average performance factors (i.e., calibration factors) for pre-defined categories of projects. A project was categorized for calibration by either its primary application or by the contractor that developed it. The intent was to determine the more appropriate categorization for calibration. SAGE validation consisted of using the derived calibration factors to predict completed efforts, not used in deriving the factors. Statistical resampling employing Monte Carlo simulation was used to calibrate and validate the model on each possible combination of a category\u27s projects. Three statistical measures were employed to measure model performance in default and calibrated estimating modes. SAGE generally did not meet pre-established criteria for estimating accuracy, although the model demonstrated some improvement with calibration. Calibration of projects categorized by contractor resulted in better calibrated model performance than calibration of projects categorized by application. This categorization is suggested for future consideration

Project Estimation with NDT

Software Project Estimation is one of the most critical and complex task for a Project manager. Several techniques, tools and mechanisms were proposed in the literature. However, these solutions are sometimes difficult and expensive to be applied and too frequently, the final estimation is made according to the manager experience. In this paper we present a preliminary approach based on the Use Case Points technique, which is adapted for the Model-Driven environment of NDT. This technique is automatically applied, thanks to the metamodels definition, and it is presented in a tool named NDT-Counter. Additionally, the paper presents an initial empirical evaluation of the results.Ministerio de Ciencia e Innovación TIN2010-20057-C03-02Ministerio de Ciencia e Innovación TIN 2010-12312-EJunta de Andalucía TIC-578