Development of Cost Estimation Tool

Unified Modeling Language (UML) is a standardized general-purpose modeling language in the field of software engineering. The Unified Modeling Language includes a set of graphic notation techniques to create visual models of object-oriented software-intensive systems. In software engineering, a class diagram in the UML is a type of static structure diagram that describes the structure of a system by showing the system's classes, their attributes, operations (or methods), and the relationships among the classes. The aim of my project is to develop a tool to estimate the cost of a software using UML class diagram. This is achieved by converting UML class diagram to XML (Extensible Markup Language) representation. XML is a markup language that defines a set of rules for encoding documents in a format that is both human-readable and machine-readable. By using the concept of class point approach, it calculates the total number of adjusted class point by parsing the XML file. First step for development of cost estimation tool requires understanding the concept of UML and XMI (XML Metadata Interchange). XMI is an Object Management Group (OMG) standard for exchanging metadata information via Extensible Markup Language (XML). The most common use of XMI is as an interchange format for UML models, although it can also be used for serialization of models of other languages. Conversion of UML class Diagram to XML representation using Magic Draw for parsing. Creating a XMI parser to find the NEM (Number of External Methods), NSR (Number of Service Requested) and NOA (Number of Attributes) and the type of classes. Using class point object oriented approach, calculate the effort required to develop a software system by NEM, NSR and NOA. Information procession size estimation includes identification and classification of classes, evaluation of complexity level of each class using 24 different type of drivers, estimation of the Total Unadjusted Class Point

Functional Size Measurement Tool-based Approach for Mobile Game

Nowadays, software effort estimation plays an important role in software project management due to its extensive use in industry to monitor progress, and performance, determine overall productivity and assist in project planning. After the success of methods such as IFPUG Function Point Analysis, MarkII Function Point Analysis, and COSMIC Full Function Points, several other extension methods have been introduced to be adopted in software projects. Despite the efficiency in measuring the software cost, software effort estimation, unfortunately, is facing several issues; it requires some knowledge, effort, and a significant amount of time to conduct the measurement, thus slightly ruining the advantages of this approach. This paper demonstrates a functional size measurement tool, named UML Point tool, that utilizes the concept of IFPUG Function Point Analysis directly to Unified Modeling Language (UML) model. The tool allows the UML eXchange Format (UXF) file to decode the UML model of mobile game requirement and extract the diagrams into component complexity, object interface complexity, and sequence diagram complexity, according to the defined measurement rules. UML Point tool then automatically compute the functional size, effort, time, human resources, and total development cost of mobile game. Besides, this paper also provides a simple case study to validate the tool. The initial results proved that the tool could be useful to improve estimation accuracy for mobile game application development and found to be reliable to be applied in the mobile game industry

Materials takeoff in building information modeling

Appropriate cost estimation, monitoring and controlling are the key point of construction project td succeed. 2D drawing has been a normal source of information and procedure since 1970's. The drawback of drawing based estimating however is its nature where it has limited information that is required by the estimators. In addition, it also requires manual estimation and thus introduces inaccuracy and error in measurement. The source of inaccuracy and error comes from the estimator that needs to review many sheets of drawing for extracting building component and quantification measurement to perform materials takeoff. Therefore, more time is needed to establish unit measurement of the building component. Material takeoff in Building Information Modeling (BIM) is performing takeoff, counts and measurement of building components quantification by using parametric underlying 3D model instead of using conventional method for conducted manual materials takeoff for cost estimation. By performing takeoff, count and measurement by using parametric model instead of conventional method, all possible problems due to miscalculation and human error can be minimized. Besides that, by using BIM model based approach on estimating and materials takeoff, takeoff, count and measurement for quantification can be done quickly and more accurately. The scope of this is study is to perform takeoff, count and measurement by using BIM 3D parametric Architecture Model. The aim of this study is to explore the BIM model based approach on estimating and materials takeoffs. Research method that been used in this study is extracted all building component information about measurement, count and takeoff by using Revit Suite 2014 software as an input for conducting cost estimation. Finally, all the quantification takeoff extracted from parametric model is used for performing cost estimation of the architecture components of this bungalow construction. All the cost estimation is calculated by using Excel data sheet that have been developed by researcher. By using this BIM model approach, researcher believe that it will helps construction project teams for better project coordination in the coming years

A Power Consumption Estimation Approach for Embedded Software Design using Trace Analysis

International audienceWith the explosion of advanced power control knobs such as dynamic voltage frequency scaling, mastering energy constraints in embedded systems is becoming challenging for software developers. Several power estimation techniques have been proposed over the past years, from electrical level to more abstract models such as SystemC/TLM. They offer various trade-offs between performance and accuracy, but suffer from a number of shortcomings. They are expensive and time-consuming, requiring intricate models of the architecture and finally, fail to be applied from the software developer perspective. In this paper, we propose a lightweight and cost-effective approach suitable for software developers. It relies on trace analysis and high-level modeling of architectures to perform quick and efficient power consumption estimations without loosing accuracy. This approach is fully supported by a tool and is validated using a simple thermal mitigation case study and checked against physical measurements. We show that, for our case study, the relative error between our tool and real values is 8% in average

GAMMA SHAPE MIXTURES FOR HEAVY-TAILED DISTRIBUTIONS

An important question in health services research is the estimation of the proportion of medical expenditures that exceed a given threshold. Typically, medical expenditures present highly skewed, heavy tailed distributions, for which a) simple variable transformations are insufficient to achieve a tractable low- dimensional parametric form and b) nonparametric methods are not efficient in estimating exceedance probabilities for large thresholds. Motivated by this context, in this paper we propose a general Bayesian approach for the estimation of tail probabilities of heavy-tailed distributions,based on a mixture of gamma distributions in which the mixing occurs over the shape parameter. This family provides a flexible and novel approach for modeling heavy-tailed distributions, it is computationally efficient, and it only requires to specify a prior distribution for a single parameter. By carrying out simulation studies, we compare our approach with commonly used methods, such as the log-normal model and non parametric alternatives. We found that the mixture-gamma model significantly improves predictive performance in estimating tail probabilities, compared to these alternatives. We also applied our method to the Medical Current Beneficiary Survey (MCBS), for which we estimate the probability of exceeding a given hospitalization cost for smoking attributable diseases. The R software that implements the method is available from the authors

Improvement estimating of project cost and design for a hospital project by using (3D&5D) simulation

Building Information Modeling (BIM) is an approach of managing and generating building data during its life cycle, dimensional (2D) drawings and later developed to (3D). The scope of BIM 3D, 4D, 5D, in this research 3D model to understand the process project special for beginner's engineers and give idea about all steps the project. 5D the cost component helps create estimates. Estimator is consuming 70% of a cost estimator’s time which required to a project. BIM can provide the capability to create takeoffs the materials, measurements and counts immediately from a model. Building Information models are also more and more used by Owners, Designers, Contractors and Engineer during the project lifecycle. Planning and cost estimation used in design phases for huge project to detect errors before start in the work , through account the time required to set up a hospital and reduce the time needed to build the project through overlapping relationships and getting shorter period to build the project utilizing MS Project software and to detect estimated 5D costing of total construction project, BIM can support cost estimating, the period spent by the estimator on quantification differ by project, using BIM for takeoff or cost estimating, the removal of manual takeoffs saves cost ,time and minimize potential for human error.

A systematic review of software development cost estimation studies

This paper aims to provide a basis for the improvement of software estimation research through a systematic review of previous work. The review identifies 304 software cost estimation papers in 76 journals and classifies the papers according to research topic, estimation approach, research approach, study context and data set. A web-based library of these cost estimation papers is provided to ease the identification of relevant estimation research results. The review results combined with other knowledge provide support for recommendations for future software cost estimation research, including: 1) Increase the breadth of the search for relevant studies, 2) Search manually for relevant papers within a carefully selected set of journals when completeness is essential, 3) Conduct more studies on estimation methods commonly used by the software industry, and, 4) Increase the awareness of how properties of the data sets impact the results when evaluating estimation methods