Improving Use Case Point (UCP) Based on Function Point (FP) Mechanism

To maintain customer trust, Islamic banking continues to improve its services which rely on the use of information technology (software and its supporting peripherals). In the meantime, research on software in Islamic banking are still finite. Thus, the authors are interested in calculating the size and effort of working on the core application of an Islamic bank, which is called the Islamic Banking Application (IBA). Two methods are used in the study to see the size of the IBA. The size can be seen from the point of view of functional-based processes and non-functional aspects. The functional one, we propose the Use Case Points (UCP) method. In the UCP method, there are at least4 steps that must be passed for measuring software size. On the other hand, for non-functional measurement, we used the original Function Points Analysis (FPA) concepts. As a result, this research produces size measurement software using the FPA technique of 2,109.40 function points, while the UCP method results in 3,024.54 use case points. To convert size measurement into effort estimation, the author uses previous research with a productivity rate of 8.2 person/hour. Thus, the predicted effort consumed to develop the IBA is 17,297.08 person/hour (based on FPA technique) and 24, S01.23 person/hour (by UCP method). We found the deviation of 7,504 person/hour between both methods. This is due to the existence of different measurement parameters.

Estimating the cost of development is one of the most crucial and daunting tasks for a software project manager. A lot of cost estimation models were reported in the literature but many of these models became obsolete because of the rapid changes in technology. Earlier cost estimation models used the size of the ultimate software product as the primary factor which, in many cases, was difficult to estimate. For example, COCOMO model used the number of Delivered Source Instructions (DSI) which is hard to estimate for products developed using modern programming languages. On the other hand, models such as Function Point (FP) metrics were designed to consider functional requirements instead of lines of code. These models were applicable only to procedural paradigm, and are not directly applicable to software products developed using the object-oriented methodology. It is this idea that gave birth to the creation of Use Case Point (UCP) metrics, originally developed by Gustav Karner[1993]. UCP uses use cases as the primary factor; use case model is the first model developed in an object-oriented design process using UML. In this paper, the authors extended the original UCP model with additional information obtained from use case narratives.

The size of a software project is a key measure of predicting software effort at the requirements and analysis phase. Use case points (UCP) is among software size metrics that achieved good reputation because of the increasing popularity of use case driven development methodologies in software industry. Nevertheless, there is no consistent method that can effectively translate the UCP into its corresponding effort. Previous estimation models were built using a very limited number of projects, and they were not well examined. The soft computing techniques were rarely applied for such problem and their performances have not been well investigated using a systematic procedure. This study looks into the accuracy and stability of some soft computing methods for the problem of effort estimation based on UCP. Four neural network methods, adaptive neuro fuzzy inference system and support vector regression have been used in this comparative study. The results suggest that most used soft computing techniques can work well with good accuracy for such problem. Among them, the general regression neural network is the superior one with stable ranking across different accuracy measures. Also, it has been found that using adjustment variables with basic UCP variables, solely or together, have positive impact on the accuracy and stability.

Software effort estimation is crucial task in software development life cycle. There are many model exists for estimating the software project effort like regression model, expert judgment, algorithmic and non-algorithmic. But, still software industries are lacking to have more accurate effort estimation method due to which they will lead to failure. In this work, an enhanced Use Case Point model (Algorithmic model) is introduced to overcome this problem which is based on the existing Use Case Point (UCP) model. A case study is also performed for comparative analysis by taking five software projects into consideration and different evaluation criteria like MMRE, MMER, MSE, RMSE and PRED(x) are used to estimate the accuracy of the proposed model.

There are many different ways to size estimate of software projects. However, software developers always have problems in choosing the right method for their projects. The Use Case Points (UCP) is among these common methods, but there is still some complexity in using them in a way that greatly contributes to obtaining accurate estimates. This paper presents an improvement of the UCP method, whereby an activity diagram is used and adapted and a weighting mechanism is developed. The improved method "Merging use case points (M-UCP)" will contribute to reducing the complexity of the traditional UCP method in the estimation process. In addition, a case study is introduced to test the refined method, and the results showed that the method performed better in comparison with previous methods in size estimating software development.

Software cost estimation is a key open issue for the software industry, which suffers from cost overruns frequently. As the most popular technique for object-oriented software cost estimation, Use Case Points(UCP) method, however, has two major drawbacks: the uncertainty of the cost factors and the abrupt classification. To address these two issues, we propose the Extended Use Case Points (EUCP) method. With a probabilistic cost model constructed from integrating fuzzy set theory and Bayesian Belief Networks(BBNs) with the UCP method, EUCP provides a probability distribution of cost and a refined gradual classification, which mitigate the uncertainty of cost factors and improve the accuracy of classification. In this paper, we provides two case studies to demonstrate the effectiveness of EUCP in the real life.

Accurate software effort estimation is a persistent challenge in project management, as a significant share of project failures is attributed to inadequate prior risk consideration. Among the widely adopted methodologies that are used for early estimation of the success of a project is the Use Case Points (UCP) method, yet its framework does not take into consideration risk factors, undermining its reliability. To improve upon this limitation, this study introduces UCPRisk, a rule-based expert-guided UCP model that explicitly integrates risk factors across six dimensions: requirements, planning and control, project complexity, user involvement, team dynamics, and organizational environment. The model was evaluated through three public service application case studies, producing effort estimates of 1,564.42 man-hours (agriculture application), 7,287.91 man-hours (company registration), and 4,669.17 man-hours (industrial permit registration). Compared to traditional UCP, UCPRisk reduced the average Relative Error (RE) to 24.3%, demonstrating improved alignment with actual project outcomes. While not a definitive cost calculation tool, UCPRisk provides a structured framework that embeds risk into early estimation, offering more realistic projections for software development.

Estimating the software size and effort helps in early prediction of uncertainties in software development. Determining the size helps in ascertaining the effort, cost, and schedule for entire project. In context of mobile software, the existing techniques for software effort estimations could be adapted as such or with modifications. There are many software size and effort estimation metrics. In this paper, Use Case Point (UCP) metric is aimed for estimating size and effort for mobile application. Five android mobile applications are considered as a case study, and difference in actual effort and estimated effort is evaluated. Modified UCP has been also proposed to improve the results by considering mobile-specific characteristics.

Empirical studies are important in software engineering to evaluate new tools, techniques, methods and technologies. In object-oriented analysis, use case models describe the functional requirements of a software system, so they can be the basis for software measurement and sizing. The purpose of this study is to develop a new metric called Architectural Element Points (AEPoint) that enables to calculate the effort required to develop a software solution, using the 4-Step Rule Set (4SRS) method. This paper describes a case study with 60 undergraduate students grouped in four teams that developed a software system (Web application) for a real customer. In this study, we used the AEPoint metric to estimate the resources needed to develop a software system. The results of the AEPoint and Use Case Points (UCP) metrics and the real software development effort are compared, conclusions drawn and recommendations are proposed.

Function point elements are metrics to measure the size of software projects. This article investigates the relationship among function point elements using principle component analysis. Principle component analysis reveals the relationship of different function point elements such that they may be measuring the same attribute of a software project. Therefore, principle component analysis brings out the influence of a function point element over each other. Principle component analysis can help to integrate the function point elements. Function Point elements have attracted much attention in the software research and development industry. Ever since function point were introduced by IBM in 70's their nature, behaviour, impact, distribution and correlation have been studied by the software researchers and the software practitioners. The idea behind function points is to standardize the measurement of the various software functions to estimate the software development effort which is independent of the computer language, development methodology, technology and the capability of the team developed the software. The International Function Point Users Group (IFPUG) was founded in the late 80s and is a membership governed, non-profit organization committed to promoting and supporting function point analysis and other software measurement techniques. There have been various releases of the Function Point by the International Function Point Users Group (IFPUG) which includes release 'Counting Practice Manual - 4.2' release. It is critical to understand the relationship of the function point elements with other components of software projects; for example software quality, software reliability, software defects and testing requirements. Similarly, it is essential to understand the relationship of function point elements with each other. The degree of influence of a function point element over other elements shows that the function point element may be measuring the same attribute of a software project which other function point elements are measuring. Furthermore, based on this relationship, a function point element can be predicted from other function point elements. Previous studies (1-3) discussed the relationships among function point elements. This paper further extends this discussion and use principle component analysis to investigate the relationship of function point elements. The paper is organized in the following way: Section 2 discusses the function point elements, Section 3 describes the dataset used for the principle component analysis, Section 4 presents the principle component analysis of the function point elements and Section 5 draws some conclusions.

Changes in nucleolar size and nucleolar vacuolation at early stages of fiber development and final fiber dimensions were determined for cotton of different species: Gossypium hirsutum L. cv. B49, Gossypium barbadense L. cv. Menoufi and Gossypium arboreum L. cv. Virnar. Size of the nucleolus in combination with its vacuolation at an early stage of development was found to be clearly associated with the final result of fiber development.

Predicted effects of anthropogenic climate change on estuarine and coastal organisms are complex, and early life history stages of calcified ectotherms are amongst the most sensitive groups. Despite the importance of understanding their vulnerability, we lack information on the effects of multiple stressors on the embryonic development of estuarine and burrowing organisms, mainly mangrove-associated species. Here, we determined the combined effects of elevated temperature and decreased pH on the embryonic development of the estuarine fiddler crab Leptuca thayeri. Initially, the microhabitat (burrow) of ovigerous (egg-bearing) females was measured for temperature, pH, and salinity, which provided control values in our laboratory experiment. Embryos at the early stage of development were subjected to cross-factored treatments of predicted temperature and pH and evaluated for development rate, survivorship, and volume until their later embryonic stage. Embryo development was faster at early and later stages of development, and survivorship was lower under elevated temperature. Embryos under reduced pH showed advanced embryonic stages at their late development stage. Higher egg volume was observed in a warmer and acidified environment, and lower volume in warmer and non-acidified conditions, indicating that embryo development is synergistically affected by warming and acidification. More than 70% of embryos developed until late stages under the multiple-stressors treatment, giving insights on the effects of a warm and acidified environment on burrowing estuarine organisms and their early stages of development.

Expression of lipoxygenase isoenzymes in developing barley grains

<div class="section abstract"><div class="htmlview paragraph">Ensuring software quality is one of the key challenges associated with the development of automotive embedded systems. Software architecture plays a pivotal role in realizing functional and non-functional requirements for automotive embedded systems. Software architecture is a work-product of the early stages of software development. The design errors introduced at the early stages of development will increase cost of rework. Hence, an early evaluation of software architecture is important.</div><div class="htmlview paragraph">PERSIST (Powertrain control architecture Enabling Reusable Software development for Intelligent System Tailoring) is a model-based software product line approach which focuses on cross-project standardization of powertrain software. The product line is characterized by common design guidelines and adherence to industry standards like ISO 25010, AUTOSAR and ISO 26262. This paper shows a systematic approach to ensure objective, early and repeated analysis of software architecture for the PERSIST product line using metrics. The systematic approach for architecture metrics involves the definition, implementation, measurement and, evaluation of the metrics for hybrid control unit software. With a new approach of architecture-driven development, this paper demonstrates how an early evaluation of the software architecture helps to frontload development efforts and improves software quality.</div></div>

Early-life experiences and neuromodulatory mechanisms shape discontinuous behavioral plasticity across developmental stages and modify the spectrum of long-term individuality patterns within isogenic populations.