Function Point Analysis Research Articles

Towards Individualized Production with Flexible Shopfloor IT based on Distributed OPC UA Services

Nowadays, manufacturers face the problems to adjust their production according to the fast-changing global competition. Car manufacturers, for example, are in front of a new era of individual mobility. They need to switch from combustion engines to electric drives. In general, manufacturers have to develop production strategies to lower set up time and meet requirements faster. The classical production line is most effective if the product variety is low and the lot size is high but facing the rapid growing demand for individualized products and fast-changing requirements, manufacturers must discover new ways of manufacturing. One possibility is the flexible shopfloor. In this work, we will present our concept of a flexible shopfloor IT for controlling a robotic demonstrator. We use OPC UA over TSN as a platform for communication and CODESYS as Soft SPS for the control of sensors and actuators. In order to create valid data for ongoing discussions we use function point analysis and counting lines of sourcecode to measure software size. Our expectation is that the initial effort for implementing a flexible shopfloor IT is higher compared to the classic approach, but for all the following implementation it will take less time, because of the possibility of reuse already developed systems.

Early and quick function points analysis: Evaluations and proposals

Measuring Function Points following the standard process is sometimes long and expensive. To solve this problem, several early estimation methods have been proposed. Among these, the “NESMA Estimated” method is one of the most widely used; it has also been selected by the International Function Point User Group as the official early function point analysis method, under the name of ‘High-level FPA’ method. A large-scale empirical study has shown that the High-level FPA method – although sufficiently accurate – tends to underestimate the size of software. Underestimating the size of the software to be developed can easily lead to wrong decisions, which can even result in project failure. In this paper we investigate the reasons why the High-level FPA method tends to underestimate. We also explore how to improve the method to make it more accurate. Finally, we propose size estimation models built using different criteria and we evaluate the estimation accuracy of these new models. Our results show that it is possible to derive size estimation models from historical data using simple regression techniques: these models are slightly less accurate than those delivered by the High-level FPA method in terms of absolute estimation errors, but can be used earlier than the High-level FPA method, are cheaper, and do not underestimate software size.

FPA evaluation of digital projects using IFPUG Method

This article considers Function Point Analysis (FPA) as a tool for price substantiation and specification of liabilities for development of digital project, since each new project in the company is analyzed. Information acquired during the analysis forms basis for adoption of critical decisions regarding complexity, resources, frames, terms, expenses, etc. Even strictly defined projects may fall out at later stages without accurate analytical method. Reducing risks of software projects is the most important issue. In general, this starts from definition of exact measures regarding scale, productivity, duration, quality, and other key performances of project efficiency. Advanced methods of analysis, such as FPA, provide clear presentation of each of these metrics related mainly with the amount of project, personnel, expenses and time, which supports management, control, adjustment of software development at early stages of planning.

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.

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.

Efficiency Improvement of Function Point-Based Software Size Estimation With Deep Learning Model

Software cost estimation is crucial to software management, which has received considerable attention from both industry and academia. Software size is an important metric that forms the cornerstone of software cost estimation. The function point has been proven to be a useful software size unit for size estimation and has been successfully implemented in many countries. However, in current practice, the rule of function point size method is complicated and performed manually. Consequently, it is costly in both time and resources spent to apply these methods, especially in the scenario of large-scale software development in the industry. In this paper, a deep learning-based named entity recognition (NER) model was designed in place of manual function point recognition. In particular, a BiLSTM-CRF model was trained on previously labeled requirements in the industry to classify the function point type of new requirements in the same domain. The proposed method was verified on 29 real projects provided by our industry partner. A comparative experiment was designed for the quantitative evaluation of efficiency improvement of the proposed NER model aided function point estimation. The result suggests that, for the NER model, the precision and F1 of the BiLSTM-CRF-based function point analysis on test samples achieved 94.5% and 80.3%, respectively. Moreover, the improvement in the efficiency of the software size estimation process achieved an average of 38.6%, which is a significant enhancement for the function point-based software size estimation.

Enhancement in Function Point Analysis

Enhancement in Function Point Analysis

Design Complexity for Objective Function Points

This paper investigates correlating the basic elements of Unified Modeling Language and Cyclomatic Complexity with Function Point Analysis (FPA) principles to develop an automated software functional sizing tool. This concept has been difficult to achieve due to the logical nature of the FPA sizing methodology versus the physical nature of source lines of code (SLOC). In this approach, we examine software complexity from design and maintainability perspectives in order to understand relationships in physical code. Our hypothesis is that this method will “simulate” FPA principles and produce an objective sizing method. This would provide the foundation for an automated tool that scans physical software code to derive “Objective Function Points”(OFPs) functional size measure.

Improving Software Cost Estimation With Function Points Analysis Using Fuzzy Logic Method

Function Points Analysis (FPA) is amongst the most generally used method to assess software cost estimation frameworks. This process speaks to the measurement of an undertaking, application, and function by its relative functional complexity. In general, it has numerous effective applications used in both industry and scholarly research. This is noticed that customized estimate technologies which can confront genuine challenges utilizing on programming building information is normally constrained, loosely gathered and deficient. To enquire these queries composite programming models, blend of information, fuzzy logic and master judgment is proposed. This is trusted that outcomes announced here will animate, renew investigation of fuzzy logic to genuine programming designing issues. In this research paper, we use Function Points and apply some new models to pick up a superior estimation of programming properties. The utilization of ideas and characteristics from the fuzzy set hypothesis to stretch out function points analysis to fuzzy function points analysis. Fuzzy hypothesis tries to construct formal quantitative arrangement equipped for imitating imprecision of the human information. With the function points created by Fuzzy FPA, an estimate value for example, expenses/cost and software development can be more correctly determined.

A Pragmatic C ost Effective Model to Enhance the COCOMO Model in Software Estimation

This research work is aimed at to provide effective cost estimation methodology emphasize on cost effort and time . This paper summarizes the cost effort estimation of most conventionally used models like organic and semi-detached models using an improved version of genetic algorithm that enhances an empirical methodology to reduce the cost factor and time factor in software projects. Constructive cost model(Cocomo model) is broadly used for the fruitful valuation of cost estimation which is based on KLOC method(thousands of lines of code).This method yields beneficial result in case of lines of code method but lacks in terms of concept and logics. The same is estimated directly and is computed using the function point analysis. In the software development lifecycle, the software cost effort estimation is the most demanding process. The accuracy of the estimate in choosing the estimation model is an essential factor. Such conventional software effort estimation techniques fail to compute the accuracy of effort estimation and it is not up to the mark. So here, we tend to propose the cost reduction in the software projects by using the improved version of the known genetic algorithm.

Assessing the effectiveness of approximate functional sizing approaches for effort estimation

Context: Functional Size Measurement (FSM) methods, like Function Points Analysis (FPA) or COSMIC, are well-established approaches to estimate software size. Several approximations of these methods have been recently proposed as they require less time/information to be applied, however their effectiveness for effort prediction is not known. Objective: The effectiveness of approximated functional size measures for estimating the development effort is a key open question, since an approximate sizing approach may miss to capture factors affecting the effort. Therefore, we empirically investigated the use of approximate FPA and COSMIC sizing approaches, also compared with their standard versions, for effort estimation. Method: We measured 25 industrial software projects realised by a single company by using FPA, COSMIC, two approximate sizing approaches proposed by IFPUG for FPA (i.e. High Level and Indicative FPA), and three approximate sizing approaches proposed by the COSMIC organisation for COSMIC (i.e. Average Functional Process, Fixed Size Classification, and Equal Size Band). Then we investigated the quality of the regression models built using the obtained measures to estimate the development effort. Results: Models based on High Level FPA are effective, providing a prediction accuracy comparable to the one of the original FPA, while those based on the Indicative FPA method show poor estimation accuracy. Models based on COSMIC approximate sizing methods are also quite effective, in particular those based on the Equal Size Band approximation provided an accuracy similar to the one of standard COSMIC. Conclusion: Project managers should be aware that predictions based on High Level FPA and standard FPA can be similar, making this approximation very interesting and effective, while Indicative FPA should be avoided. COSMIC approximations can also provide accurate effort estimates, nevertheless, the Fixed Size Classification and Equal Size Band approaches introduce subjectivity in the measurement.

Literature review on Functional Requirements for Function Point Analysis in Mobile Game

Functional size measurement has been widely used as the effort prediction method for software project over the past decades. Despite the success in predicting the cost, time requirement, and staff resources utilizing the amount of functionality delivered by a system, the method still needs to be improved further especially in dealing with mobile application characteristics. In the domain of mobile game application, the functional features can be challenging to identify wholly due to various application platforms, diversity of game genre, and complex game scenario. This paper presents a literature review concerning the functional requirements of the mobile game. The review includes the process of defining the research question, search strategy, and selection of study. Fifty-three articles were found in the academic libraries, and only 30 relevant studies were selected for the review. This literature review aims to provide researchers and practitioners in software measurement and gaming technology with an overview of common functional characteristics in the mobile game, which can be integrated into the functional size measurement method.

Empirical Study of Function Point Analysis during Software Development Phase

During the development of the software, Software Requirement Changes (SRC) often occurs. Software estimation helps in maintaining a balance between the increase and decrease of the price, time, etc. Function Point Analysis (FPA) is a software effort estimation technique used for measuring the size and complexity of software by calculating the functionality from a user's point of view. Function count focuses on what functionality is being delivered. It enables programmers to perform function point counting themselves instead of contacting an expert. An empirical study has been conducted to analyze the capability of the FPA technique. The results of the FPA-SDP (Function Point Analysis for Software Development Phase) model can help software project managers in (i) knowing the inconsistent states of software artifacts (ii) estimating the actual size of a change request with its complexity level for the software development phase.

Determination of value price or computer application using function point analysis method

Some developer very capable of developing good quality working applications, but they don’t have the right value and price for their products, and it is because they did not use the right method to calculate the size of the product and valuate them correctly, most of them use analogy and expert judgment to perform their product sizing and valuation. This situation will create inconsistency in doing the pricing and it will create disadvantages for both developers and users. Function point analysis provides a methodology to perform software size calculation using algorithmic approaches that gives comprehensive and consistent results. In this document, I will explain step by step the processes of calculating the Function point using FPA procedures by implementing calculation formula of EI, EO, EQ, ILF, EIF, and VAP. I also will implement them to calculate the size of the “XIbar” application system, especially module customer care and customer info. By doing all these activities I hope will provide simple templates and procedures for calculating the size of application software that can be used easily by developers, students, and others who need it.

Implementasi Function Point Analysis Untuk Pengukuran Kualitas Situs (Studi Kasus: Alibaba.com)

To find out about how complex and useful a software is, a measurement needs to be done toward the software itself to found its complexity and its usefulness. From few methods that used for measuring a software, Function Point Analysis is most popular method to do the measurement, which measures a software from its functionality. From this research, three factors that very decisive were calculated, those are Crude Function Points (CFP), Relative Complexity Adjustment Factor (RCAF), and the Function Point (FP) calculation itself. This software measurement marks its end of the research at the point of doing a single transaction with the application. The results that came out with the calculation are Crude Function Points (CFP) with 183, Relative Complexity Adjustment Factor (RCAF) with 31, and the Function Point (FP) itself with 175.86, which shows that this web-based application is quite complex.

Revised approach for the prediction of functional size of mobile application

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.

A Study of Function Point Analysis: Some Suggestive Modifications

FPA (Function Point Analysis) is a standardized method aimed at establishing a software size measurement from its functional requirements, considering the features to be implemented in it. It was designed to be applied regardless of the programming language and implementation technology. The paper focuses on the requirements of the modification in the FPA. As from its origin to date there has been drastic changes occurred in the software development paradigm, but FPA exist in its previous form, so there is a need of examine the FPA with the current scenario.

40 Years Journey of Function Point Analysis: Against Real-time and Multimedia Applications

For various project of software development, the size, effort, and cost are essential aspects for planning schedules and control software development to achieve the preferred outcome. These aspects require a method to measure software accurately and reliably. Function Point Analysis is used as a standard method for that purpose. It is now 40 years old since Albrecht founded it in 1979. Bringing its advantages and some of the drawbacks from earlier versions, this method is now faced with current software development needs, namely, the real-time and the multimedia applications. Broadly translated our findings indicate that current software development does not only focus on system functionality, but non-functional factors also begin to influence the value of a system for the users. Therefore, in 40 years journey of Function Point Analysis, this method is not adequate for current software development, especially in real-time and multimedia applications because of the inability to measure non-functional factors.

Categorical Variable Segmentation Model for Software Development Effort Estimation

This paper proposes a new software development effort estimation model. The new model's design is based on the function point analysis, categorical variable segmentation (CVS), and stepwise regression. The stepwise regression method is used for the creation of the unique estimation model of each segment. The estimation accuracy of the proposed model is compared to clustering-based models and the international function point user group model. It is shown that the proposed model increases estimation accuracy when compared to baseline methods: non-clustered functional point analysis and clustering-based models. The new CVS model achieves a significantly higher accuracy than the baseline methods.

A Study of Function Point Analysis: Some Suggestive Modifications

A Study of Function Point Analysis: Some Suggestive Modifications