46,752 research outputs found

    Optimizing Time and Effort Parameters of COCOMO II using Fuzzy Multi-Objective Particle Swarm Optimization

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    Estimating the efforts, costs, and schedules of software projects is a frequent challenge to software development projects. A bad estimation will result in bad management of a project. Various models of estimation have been defined to complete this estimate. The Constructive Cost Model II (COCOMO II) is one of the most famous models as a model for estimating efforts, costs, and schedules. To estimate the effort, cost, and schedule in project of software, the COCOMO II uses inputs: Effort Multiplier (EM), Scale Factor (SF), and Source Line of Code (SLOC). Evidently, this model is still lack in terms of accuracy rates in both efforts estimated and time of development. In this paper, we introduced to use Gaussian Membership Function (GMF) of Fuzzy Logic and Multi-Objective Particle Swarm Optimization (MOPSO) method to calibrate and optimize the parameters of COCOMO II. It is to achieve a new level of accuracy better on COCOMO II. The Nasa93 dataset is used to implement the method proposed. The experimental results of the method proposed have reduced the error downto 11.89% and 8.08% compared to the original COCOMO II. This method proposed has achieved better results than previous studies

    Cost of Quality in Software Products: An Empirical Analysis

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    Computer software has emerged as a major worldwide industry, estimated at 450Bfor1995ofwhich450B for 1995 of which 225B is attributable to US firms [Boehm, 1987]. Yet, in many organizations, costs and schedules for software projects are largely unpredictable, and product quality is often poor [DeMarco and Lister, 1993]. This underscores the need to study both the quality of the software product and the life-cycle cost incurred in the development and maintenance of the products. Increasing expenditure in software has caught the attention of researchers. Identifying software productivity factors and estimating software costs continue to be important research topics [Mukhopadhyay and Kekre, 1992; Banker et al., 1993]. Researchers have adopted both empirical and theoretical approaches to better understand the process of software development and maintenance. Though software cost continues to be an important research question, competition in the software industry and the increased role of software in everyday life have also made development cycle time and quality important research issues. The quality of software has been studied mainly from defect analysis and software maintenance perspectives. Empirical research has analyzed tradeoffs between software quality and maintenance, and examined drivers of software maintenance costs [Banker, et al., 1993]. Practitioners in the software industry are still faced with the challenge of understanding the key tradeoffs in a software project in order to deliver quality products to customers on time and without cost overruns. This underscores the need to study the various factors that influence the life-cycle cost and quality in software products. Moreover, the effect of the process used in a software project on the outcome of the project in terms of cost to the software developer and quality of the product has not been examined rigorously. Thus in this research, we propose to model the life-cycle cost and quality of software products based on the factorsrelated to product, people, process and technology deployed in the software project

    Calibration of the Softcost-R Software Cost Model to the Space and Missile Systems Center (SMC) Software Database (SWDB)

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    The rising number and importance of Department of Defense software developments, when combined with declining defense budgets, has resulted in a critical need to accurately plan and manage software development costs and schedules. Unfortunately, the increasing size, complexity, and diversity of these software developments has made accurate estimating problematic. Uncalibrated software cost models have not generally produced reliable results due to generic default parameters and improper usage. The default parameters cannot hope to accurately represent and predict the wide variability of software efforts to which the models are being applied. However, some of the models have achieved improved accuracy by calibration from their generic default parameters to new parameter values based on specific characteristics of the development efforts being estimated. This research effort focused on the calibration of SoftCost-R, Version 8.4, to specific stratified data sets obtained from the Space and Missile Systems Center (SMC) Software Database, Version 2.1, (SWDB). The accuracy of the new calibrated inputs was verified through comparisons between the calibrated and default estimates and the actual cost data. Statistical methods used to make the comparisons included magnitude of relative error (MRE), mean magnitude of relative error (MMRE), root mean square (RMS), relative root mean square (RRMS), and prediction level Pred (k/n) or percentage of estimates within (100 * k/n)% of the actual costs. The new calibrated parameters resulted in more accurate effort estimates and the calibration method appeared to be valid. However, the accuracy improvement was neither complete nor all encompassing

    An approach to software cost estimation

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    A general procedure for software cost estimation in any environment is outlined. The basic concepts of work and effort estimation are explained, some popular resource estimation models are reviewed, and the accuracy of source estimates is discussed. A software cost prediction procedure based on the experiences of the Software Engineering Laboratory in the flight dynamics area and incorporating management expertise, cost models, and historical data is described. The sources of information and relevant parameters available during each phase of the software life cycle are identified. The methodology suggested incorporates these elements into a customized management tool for software cost prediction. Detailed guidelines for estimation in the flight dynamics environment developed using this methodology are presented

    What is a system? NASA's phased project description

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    NASA phase A and B projects are addressed. The Phase A study is the preliminary analysis of a space concept. These concepts could have come from a pre-Phase A study or from other sources within or external to NASA. The majority of concepts that are studied at MSFC are assigned by NASA Headquarters and funded accordingly. The overall program schedule depicts important milestones that establish the start and finish dates of each study phase, including design, development, launch, and operations. The Phase B of the project consists of the refinement of preliminary requirements, cost estimates, schedules and risk assessments prior to starting final design and development. The goal of a concept definition activity is to determine the best and most feasible concept(s) that will satisfy the mission and science requirements

    Cost Estimate Modeling of Transportation Management Plans for Highway Projects, Research Report 11-24

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    Highway rehabilitation and reconstruction projects frequently cause road congestion and increase safety concerns while limiting access for road users. State Transportation Agencies (STAs) are challenged to find safer and more efficient ways to renew deteriorating roadways in urban areas. To better address the work zone issues, the Federal Highway Administration published updates to the Work Zone Safety and Mobility Rule. All state and local governments receiving federal aid funding were required to comply with the provisions of the rule no later than October 12, 2007. One of the rule’s major elements is to develop and implement Transportation Management Plans (TMPs). Using well-developed TMP strategies, work zone safety and mobility can be enhanced while road user costs can be minimized. The cost of a TMP for a road project is generally considered a high-cost item and, therefore, must be quantified. However, no tools or systematic modeling methods are available to assist agency engineers with TMP cost estimating. This research included reviewing TMP reports for recent Caltrans projects regarding state-of-the-art TMP practices and input from the district TMP traffic engineers. The researchers collected Caltrans highway project data regarding TMP cost estimating. Then, using Construction Analysis for Pavement Rehabilitation Strategies (CA4PRS) software, the researchers performed case studies. Based on the CA4PRS outcomes of the case studies, a TMP strategy selection and cost estimate (STELCE) model for Caltrans highway projects was proposed. To validate the proposed model, the research demonstrated an application for selecting TMP strategies and estimating TMP costs. Regarding the model’s limitation, the proposed TMP STELCE model was developed based on Caltrans TMP practices and strategies. Therefore, other STAs might require adjustments and modifications, reflecting their TMP processes, before adopting this model. Finally, the authors recommended that a more detailed step-by-step TMP strategy selection and cost estimate process be included in the TMP guidelines to improve the accuracy of TMP cost estimates

    Space transfer vehicle concepts and requirements study. Volume 3, book 1: Program cost estimates

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    The Space Transfer Vehicle (STV) Concepts and Requirements Study cost estimate and program planning analysis is presented. The cost estimating technique used to support STV system, subsystem, and component cost analysis is a mixture of parametric cost estimating and selective cost analogy approaches. The parametric cost analysis is aimed at developing cost-effective aerobrake, crew module, tank module, and lander designs with the parametric cost estimates data. This is accomplished using cost as a design parameter in an iterative process with conceptual design input information. The parametric estimating approach segregates costs by major program life cycle phase (development, production, integration, and launch support). These phases are further broken out into major hardware subsystems, software functions, and tasks according to the STV preliminary program work breakdown structure (WBS). The WBS is defined to a low enough level of detail by the study team to highlight STV system cost drivers. This level of cost visibility provided the basis for cost sensitivity analysis against various design approaches aimed at achieving a cost-effective design. The cost approach, methodology, and rationale are described. A chronological record of the interim review material relating to cost analysis is included along with a brief summary of the study contract tasks accomplished during that period of review and the key conclusions or observations identified that relate to STV program cost estimates. The STV life cycle costs are estimated on the proprietary parametric cost model (PCM) with inputs organized by a project WBS. Preliminary life cycle schedules are also included

    Space station final study report. Volume 1: Executive summary

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    Volume 1 of the Final Study Report provides an Executive Summary of the Phase B study effort conducted under contract NAS8-36526. Space station Phase B implementation resulted in the timely establishment of preliminary design tasks, including trades and analyses. A comprehensive summary of project activities in conducting this study effort is included

    Laser Atmospheric Wind Sounder (LAWS) phase 1. Volume 3: Project cost estimates

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    The laser atmospheric wind sounder (LAWS) cost modeling activities were initiated in phase 1 to establish the ground rules and cost model that would apply to both phase 1 and phase 2 cost analyses. The primary emphasis in phase 1 was development of a cost model for a LAWS instrument for the Japanese Polar Orbiting Platform (JPOP). However, the Space Station application was also addressed in this model, and elements were included, where necessary, to account for Space Station unique items. The cost model presented in the following sections defines the framework for all LAWS cost modeling. The model is consistent with currently available detail, and can be extended to account for greater detail as the project definition progresses
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