Implementation of Function Point Analysis in Measuring the Volume Estimation of Software System in Object. Oriented and Structural Model of Academic System. identifying logical data referenced by, not maintained within, this application; and is dependent upon the user's external business view of the application. echecs16.info Fundamentals of Function Point Analysis. By David Longstreet. [email protected] echecs16.info Abstract.
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PDF | Paul Vickers and others published An Introduction to Function Point Analysis. Function point analysis measures software by quantifying the functionality the software provides to the user based primarily on logical design. With this in mind, . which Albrecht developed is called the Function Point (FP). Function Point Analysis (FPA), or the method of sizing software in terms of its.
Story Points vs. Function Points 25 September Introduction This article aims to explain what are the main differences between Story Points and Function Points, and study their complementarity for agile projects. Story Points Story Points are a measure unit resting on the perception of the work to be done by the project team. The determination of that size is based on the level of comprehension of the complexity, and thus, the required effort. Story Points can be implemented more faster than Function Points.
Despite many unproven technologies are being advanced into production environments, the older technologies are actually doing a better job. It is a method to break systems into smaller components, so they can be better understood and analyzed. As a result, it is an application of the scientific method to the forecasting of development timelines.
Each of these components are called transactions because they transact against files. Albrecht in the mid s. The method was first published in , then again, later in Earlier, free versions are available from a variety of sites including Function Point Counting Practices Manual , which provides the 4. The later 4. The number of lines of code is a measure that can serve as a proxy for a number of important concerns, including program size and programming effort. When used in a standard fashion—such as thousand lines of code KLOC —it forms the basis for estimating resource needs.
Software size, as a standard measure of resource commitment, must be considered along with product and performance measurement. SLOC has traditionally been a measure for characterizing productivity. The real advantage of lines of code is that conventional managers can easily understand the concept. However, a lines-of-code measurement is not as simple and accurate as it might seem. In order to accurately describe software in terms of lines of code, code must be measured in terms of its technical size and functional size.
Technical size is the programming itself. Functional size includes all of the additional features such as database software, data entry software, and incident handling software.
The most common technical sizing method is still probably number of lines of code per software object. However, function point analysis FPA has become the standard for software size estimation in the industry.
FPA has a history of statistical accuracy and has been used extensively in application development management ADM or outsourcing engagements. In that respect, FPA serves as a global standard for delivering services and measuring performance. FPA includes the identification and weighting of user recognizable inputs, outputs, and data stores.
The size value is then available for use in conjunction with numerous measures to quantify and evaluate software delivery and performance. In effect, FPA can be used for comparative analysis across organizations and industries.
Regardless of language, development method, or hardware platform used, the number of function points for a system will remain constant. The only variable is the amount of effort needed to deliver a given set of function points. If it is shown that a project has grown, there has been scope creep. If the amount of growth of projects declines over time, it can be assumed that communication with the user community has improved.
Current application documentation should be utilized to complete a function point count. The Five Major Components Because computer systems usually interact with other computer systems, a boundary must be drawn around each system to be measured prior to classifying components.
In short, the boundary indicates the border between the project or application being measured and the external applications or user domain that it will interface with. Once the border has been established, components can be classified, ranked and tallied. External Inputs EI — These are elementary processes in which data crosses the boundary from outside to inside. This data may come from a data input screen or another application.
The data may be used to maintain one or more internal logical files. The data can be either control information or business information. If the data is control information it does not have to update an internal logical file. External Outputs EO — These are elementary processes in which derived data passes across the boundary from inside to outside.
The data creates reports or output files sent to other applications. These reports and files are created from one or more internal logical files and external interface file. External Inquiries EQ — These are elementary processes with both input and output components that result in data retrieval from one or more internal logical files and external interface files.
The input process does not update any Internal Logical Files, and the output side does not contain derived data.
The data resides entirely outside the application and is maintained by another application. The external interface file is an internal logical file for another application. A data element type is a unique user recognizable, non-recursive, field. Significantly security is becoming more and more important in most of the software construct.
By engineering security, it will substantially raise the software cost. Therefore estimation should be made earlier on the security costing to overcome the financial shortage in the project management. Selection of security standards Software security characteristics formulation: This formulation considered four common security standards that are widely referred by local software developers and developed over the past decade.
The differences from traditional software, in terms of technology, development model, time-to-market needs, and volatility of requirements and so on, pose serious challenges in adapting traditional size metrics, like Function Points, to measure Web applications. Web Objects  size measure can be considered as a significant contribute to web-based applications measurement field.
It adds four new elements, related to web development, to the five FP functions then, complexity weighting rules are applied, and the sum of these weights becomes the functional size of the web application.
The new elements describe the multimedia content of the pages Multimedia files , the blocks of different nature that compose the pages Web Building Blocks , as well as embedded Scripts and Links to external applications and databases.
Differently from previous approaches, the proposed technique works on the same conceptual model that is used for producing the implementation, eliminating any unnecessary ad-hoc specification task. We evaluate the precision of the FP computation algorithm on a set of real-world projects and de-scribe its implementation within a commercial Model Driven Development tool suite.
These methods advocate a stronger automation of the software life-cycle, based on the use of high-level conceptual models of software solutions and on the iterative transformation of high-level models into lower-level platform specific models, until an executable representation of the system is obtained. In the tool market, vendors are Also committing to MDD by progressively incorporating conceptual modeling and code generation capabilities in their integrated development environments, further contributing to the adoption of model-driven development.
The essential ingredient of the proposed approach is a formal modeling notation suitable both for code generation and size estimation. In this paper, we have adopted the Web Modeling language, a UML profile for representing interactive systems, especially suited for describing Web and Web Service applications. WebML exploits general-purpose UML class diagrams for representing the business objects underlying the application, and a domain specific notation, called hypertext diagrams, for expressing the structure of the application front-end be it a user interface or a Web Service interface.
WebML has enough expressive power to allow the specification of multi-actor, distributed Web and Web service applications and the complete generation of their code for the JAVA2EE platform. A WebML conceptual model can also be exploited as the input for the computation of the application s function points, according to the well-known IFPUG counting rules.
In practice, starting from the requirements of the ten examined systems, we kept the original FP evaluation, and added to it the specific evaluation of Web application characteristics, according to Web Objects approach Multimedia files, Web Building Blocks, Embedded Scripts and Links to External Applications and Databases.
Clearly, the new estimate using Web Objects is consistently higher than the original FP one, because points were added, and never subtracted. To correct for this systematic bias, we computed for each project the percentage increase of Web Object estimate with respect to FP and averaged the ten values.
This is Why we chose to apply Function Points. WO estimates are done web applications. The next step of the research will be the development or the choice of a cost model more suited to take as input a size expressed in Web Objects. In that way, we will also be able to compare the obtained results with those of the unique.
The future work comprises the application of the developed system to a large collection of projects developed using WebML and Web Ratio, with a twofold purpose: further evaluating and optimizing the precision of the automatic counter, and evaluating the productivity of model-driven development. The latter issue is very promising, as no quantitative data are available on the true benefits of MDD compared to traditional system development.
Determining a statistically sound estimation of the FP 60 5 ISSN: , Volume-1, Issue-1, March delivered per staff-months with the MDD approach could foster the adoption of this promising methodology by traditional developers. An improved function point analysis method for software size estimation is proposed.
It mainly is applied to program early. The method uses the fuzzy logical reference to modify the function point. It could eliminate the uncontinuous of the complexity weight. Modified function point as new samples are transmitted to the input layer of BP network.
According to BP network, some similar software programs are estimated. The results of research show that the improved method could effectively deal with the flaw in the weight complexity analysis. UML has been recognized as a powerful tool to model the object-oriented software systems.
Verification of Function Point Analysis for object-oriented software estimation is done through a case study of Web-based Document Management System. The concept of variable productivity and building a framework based on best unbiased linear estimator. The equivalent weighted least mean square problem is derived and solved it to arrive at an accurate estimate of needed effort for future projects based on the delivered function points.
The individual function point elements were not independent. Not all the function point elements were related to effort, an effort prediction model based on two function point elements input function points and output function points was just as good as a effort model based on total function points, an effort prediction model based on the raw counts of the number of files and number of outputs was only slightly worse than an effort model based on total function points.
It might be that this dataset is atypical, for example, the results might be different if the data were all from the same company. However, the results indicate that in this case function points do not exhibit the characteristics that would be expected of a valid size metric which requires the component elements to be independent.
In addition, the results suggest that simple counts may be as effective as more complex size models as effort predictors.
This is particularly useful because the basic counts are likely to be known reasonably accurately earlier in the life cycle than the weighted counts which rely on knowing details such as the number of data items involved and tiles accessed by each input. However, use of simple counts does rely on the ability of individual organizations to collect data and generate their own effort prediction models.
For example, in this dataset simple counts of number of inputs and number of master files was a reasonable effort predictor but in another dataset different counts might be better. Another advantage of using raw counts might an improvement in counting consistency as a result of simpler counting rules.
Kemerer investigated the consistency of function point counts and found that the differences in function point s counts of the same system averaged It is likely that simpler counts would reduce this counting error.
She received her B.