Towards making functional size measurement easily usable in practice

Functional Size Measurement methods \u2013like the IFPUG Function Point Analysis and COSMIC methods\u2013 are widely used to quantify the size of applications. However, the measurement process is often too long or too expensive, or it requires more knowledge than available when development effort estimates are due. To overcome these problems, simplified measurement methods have been proposed. This research explores easily usable functional size measurement method, aiming to improve efficiency, reduce difficulty and cost, and make functional size measurement widely adopted in practice. The first stage of the research involved the study of functional size measurement methods (in particular Function Point Analysis and COSMIC), simplified methods, and measurement based on measurement-oriented models. Then, we modeled a set of applications in a measurement-oriented way, and obtained UML models suitable for functional size measurement. From these UML models we derived both functional size measures and object-oriented measures. Using these measures it was possible to: 1) Evaluate existing simplified functional size measurement methods and derive our own simplified model. 2) Explore whether simplified method can be used in various stages of modeling and evaluate their accuracy. 3) Analyze the relationship between functional size measures and object oriented measures. In addition, the conversion between FPA and COSMIC was studied as an alternative simplified functional size measurement process. Our research revealed that: 1) In general it is possible to size software via simplified measurement processes with acceptable accuracy. In particular, the simplification of the measurement process allows the measurer to skip the function weighting phases, which are usually expensive, since they require a thorough analysis of the details of both data and operations. The models obtained from out dataset yielded results that are similar to those reported in the literature. All simplified measurement methods that use predefined weights for all the transaction and data types identified in Function Point Analysis provided similar results, characterized by acceptable accuracy. On the contrary, methods that rely on just one of the elements that contribute to functional size tend to be quite inaccurate. In general, different methods showed different accuracy for Real-Time and non Real-Time applications. 2) It is possible to write progressively more detailed and complete UML models of user requirements that provide the data required by the simplified COSMIC methods. These models yield progressively more accurate measures of the modeled software. Initial measures are based on simple models and are obtained quickly and with little effort. As V models grow in completeness and detail, the measures increase their accuracy. Developers that use UML for requirements modeling can obtain early estimates of the applications\u2018 sizes at the beginning of the development process, when only very simple UML models have been built for the applications, and can obtain increasingly more accurate size estimates while the knowledge of the products increases and UML models are refined accordingly. 3) Both Function Point Analysis and COSMIC functional size measures appear correlated to object-oriented measures. In particular, associations with basic object- oriented measures were found: Function Points appear associated with the number of classes, the number of attributes and the number of methods; CFP appear associated with the number of attributes. This result suggests that even a very basic UML model, like a class diagram, can support size measures that appear equivalent to functional size measures (which are much harder to obtain). Actually, object-oriented measures can be obtained automatically from models, thus dramatically decreasing the measurement effort, in comparison with functional size measurement. In addition, we proposed conversion method between Function Points and COSMIC based on analytical criteria. Our research has expanded the knowledge on how to simplify the methods for measuring the functional size of the software, i.e., the measure of functional user requirements. Basides providing information immediately usable by developers, the researchalso presents examples of analysis that can be replicated by other researchers, to increase the reliability and generality of the results

Towards making functional size measurement easily usable in practice

Functional Size Measurement methods –like the IFPUG Function Point Analysis and COSMIC methods– are widely used to quantify the size of applications. However, the measurement process is often too long or too expensive, or it requires more knowledge than available when development effort estimates are due. To overcome these problems, simplified measurement methods have been proposed. This research explores easily usable functional size measurement method, aiming to improve efficiency, reduce difficulty and cost, and make functional size measurement widely adopted in practice. The first stage of the research involved the study of functional size measurement methods (in particular Function Point Analysis and COSMIC), simplified methods, and measurement based on measurement-oriented models. Then, we modeled a set of applications in a measurement-oriented way, and obtained UML models suitable for functional size measurement. From these UML models we derived both functional size measures and object-oriented measures. Using these measures it was possible to: 1) Evaluate existing simplified functional size measurement methods and derive our own simplified model. 2) Explore whether simplified method can be used in various stages of modeling and evaluate their accuracy. 3) Analyze the relationship between functional size measures and object oriented measures. In addition, the conversion between FPA and COSMIC was studied as an alternative simplified functional size measurement process. Our research revealed that: 1) In general it is possible to size software via simplified measurement processes with acceptable accuracy. In particular, the simplification of the measurement process allows the measurer to skip the function weighting phases, which are usually expensive, since they require a thorough analysis of the details of both data and operations. The models obtained from out dataset yielded results that are similar to those reported in the literature. All simplified measurement methods that use predefined weights for all the transaction and data types identified in Function Point Analysis provided similar results, characterized by acceptable accuracy. On the contrary, methods that rely on just one of the elements that contribute to functional size tend to be quite inaccurate. In general, different methods showed different accuracy for Real-Time and non Real-Time applications. 2) It is possible to write progressively more detailed and complete UML models of user requirements that provide the data required by the simplified COSMIC methods. These models yield progressively more accurate measures of the modeled software. Initial measures are based on simple models and are obtained quickly and with little effort. As V models grow in completeness and detail, the measures increase their accuracy. Developers that use UML for requirements modeling can obtain early estimates of the applications‘ sizes at the beginning of the development process, when only very simple UML models have been built for the applications, and can obtain increasingly more accurate size estimates while the knowledge of the products increases and UML models are refined accordingly. 3) Both Function Point Analysis and COSMIC functional size measures appear correlated to object-oriented measures. In particular, associations with basic object- oriented measures were found: Function Points appear associated with the number of classes, the number of attributes and the number of methods; CFP appear associated with the number of attributes. This result suggests that even a very basic UML model, like a class diagram, can support size measures that appear equivalent to functional size measures (which are much harder to obtain). Actually, object-oriented measures can be obtained automatically from models, thus dramatically decreasing the measurement effort, in comparison with functional size measurement. In addition, we proposed conversion method between Function Points and COSMIC based on analytical criteria. Our research has expanded the knowledge on how to simplify the methods for measuring the functional size of the software, i.e., the measure of functional user requirements. Basides providing information immediately usable by developers, the researchalso presents examples of analysis that can be replicated by other researchers, to increase the reliability and generality of the results

A Lightweight Size Estimation Approach for Embedded System using COSMIC Functional Size Measurement

Functional Size Measurement (FSM) is an important component of a software project that provides information for estimating the effort required to develop the measured software. Although the embedded software is time-consuming to develop, COSMIC FSM can be estimated to get more accurate function size. The traditional Function Point methods are designed to measure only business application domain and are problematic in the real-time domain. As a result, COSMIC Functional Size Measurement (FSM) method is designed to measure both application domains. The design diagrams such as UML, SysML and the well-defined FSM procedure must use to accurately measure the functional size of embedded system. We have already developed the generation model based on SysML metamodel with an example of elevator control system. In this paper, we applied the generation model that is the classification of the instance level of object based on UML metamodel. After that, this paper also showed the mapping rules which mapped between the generation model and COSMIC FSM to estimate the functional size of embedded software with the case study of cooker system. This paper also proposed the light weight generation method of COSMIC FSM by using the generation model

Functional Size Measurement and Model Verification for Software Model-Driven Developments: A COSMIC-based Approach

Historically, software production methods and tools have a unique goal: to produce high quality software. Since the goal of Model-Driven Development (MDD) methods is no different, MDD methods have emerged to take advantage of the benefits of using conceptual models to produce high quality software. In such MDD contexts, conceptual models are used as input to automatically generate final applications. Thus, we advocate that there is a relation between the quality of the final software product and the quality of the models used to generate it. The quality of conceptual models can be influenced by many factors. In this thesis, we focus on the accuracy of the techniques used to predict the characteristics of the development process and the generated products. In terms of the prediction techniques for software development processes, it is widely accepted that knowing the functional size of applications in order to successfully apply effort models and budget models is essential. In order to evaluate the quality of generated applications, defect detection is considered to be the most suitable technique. The research goal of this thesis is to provide an accurate measurement procedure based on COSMIC for the automatic sizing of object-oriented OO-Method MDD applications. To achieve this research goal, it is necessary to accurately measure the conceptual models used in the generation of object-oriented applications. It is also very important for these models not to have defects so that the applications to be measured are correctly represented. In this thesis, we present the OOmCFP (OO-Method COSMIC Function Points) measurement procedure. This procedure makes a twofold contribution: the accurate measurement of objectoriented applications generated in MDD environments from the conceptual models involved, and the verification of conceptual models to allow the complete generation of correct final applications from the conceptual models involved. The OOmCFP procedure has been systematically designed, applied, and automated. This measurement procedure has been validated to conform to the ISO 14143 standard, the metrology concepts defined in the ISO VIM, and the accuracy of the measurements obtained according to ISO 5725. This procedure has also been validated by performing empirical studies. The results of the empirical studies demonstrate that OOmCFP can obtain accurate measures of the functional size of applications generated in MDD environments from the corresponding conceptual models.Marín Campusano, BM. (2011). Functional Size Measurement and Model Verification for Software Model-Driven Developments: A COSMIC-based Approach [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/11237Palanci

Non-functional requirements: size measurement and testing with COSMIC-FFP

The non-functional requirements (NFRs) of software systems are well known to add a degree of uncertainty to process of estimating the cost of any project. This paper contributes to the achievement of more precise project size measurement through incorporating NFRs into the functional size quantification process. We report on an initial solution proposed to deal with the problem of quantitatively assessing the NFR modeling process early in the project, and of generating test cases for NFR verification purposes. The NFR framework has been chosen for the integration of NFRs into the requirements modeling process and for their quantitative assessment. Our proposal is based on the functional size measurement method, COSMIC-FFP, adopted in 2003 as the ISO/IEC 19761 standard. Also in this paper, we extend the use of COSMIC-FFP for NFR testing purposes. This is an essential step for improving NFR development and testing effort estimates, and consequently for managing the scope of NFRs. We discuss the merits of the proposed approach and the open questions related to its design

Early Quantitative Assessment of Non-Functional Requirements

Non-functional requirements (NFRs) of software systems are a well known source of uncertainty in effort estimation. Yet, quantitatively approaching NFR early in a project is hard. This paper makes a step towards reducing the impact of uncertainty due to NRF. It offers a solution that incorporates NFRs into the functional size quantification process. The merits of our solution are twofold: first, it lets us quantitatively assess the NFR modeling process early in the project, and second, it lets us generate test cases for NFR verification purposes. We chose the NFR framework as a vehicle to integrate NFRs into the requirements modeling process and to apply quantitative assessment procedures. Our solution proposal also rests on the functional size measurement method, COSMIC-FFP, adopted in 2003 as the ISO/IEC 19761 standard. We extend its use for NFR testing purposes, which is an essential step for improving NFR development and testing effort estimates, and consequently for managing the scope of NFRs. We discuss the advantages of our approach and the open questions related to its design as well

Reviews on functional size measurement in mobile application and UML model

The increasing popularity of game industry has motivated some exploratory research in mobile games technology.This maturing technology,provided with complex functionality in development process requires software analyst to measure the size of mobile application properly, which relatively affect the software development cost and duration.Expert judgement is used in most of the mobile application development estimation.However, literatures suggest that formal effort estimation is more comprehensive and able to avoid misunderstandings.Therefore, most of literatures adapted Functional Size Measurement (FSM) in estimating the mobile development effort.Some literatures use FSM with UML modelling because UML model can represent the functional requirement of mobile application.This paper aims to review the FSM in mobile application and UML modelling in terms of measurement process and rules

Cosmic FPA Calculator for Mobile Application Development Cost Based on Unity3D Game Engine

The emergence technology and popularity of mobile game application has led to higher demands in producing more colorful game environment, interactive design and selecting targeted platforms.To fulfil these requirements, mobile game engine; a framework to create mobile game application should provide greater complexity and parameters to be added in the mobile game properties.Thus, the effort costing of mobile application development is difficult to be estimated accurately. Therefore, this mobile game requirement is a new software concept that still needs to be tested properly to match the existing estimation models as these models are invented before the emergence of mobile application requirements. Hence, the motivation is to adapt COSMIC Functional Size Measurement (COSMIC FSM) for sizing the mobile game application development as it is one of the estimation models suitable to sizing embedded software and real-time system. This research uses Unity3D game engine as the platform to represent the mobile game requirements. These requirements are illustrated in the form of component diagrams and class diagrams in order to order to maintain and control the behavior of Unity3D features. The functional processes from component diagrams and class diagrams are captured to be used later in the sizing process using COSMIC FSM from the mapping between UML based-COSMIC FSM rules and measurement. A tool, COSMIC FPA Calculator for Mobile Application is developed to demonstrate the COSMIC FSM counting process for mobile game application costing

Using Functional Complexity Measures in Software Development Effort Estimation

Several definitions of measures that aim at representing the size of software requirements are currently available. These measures have gained a quite relevant role, since they are one of the few types of objective measures upon which effort estimation can be based. However, traditional Functional Size Measures do not take into account the amount and complexity of elaboration required, concentrating instead on the amount of data accessed or moved. This is a problem since the amount and complexity of the required data elaboration affect the implementation effort, but are not adequately represented by the current size measures, including the standardized ones. Recently, a few approaches to measuring aspects of user requirements that are supposed to be related with functional complexity and/or data elaboration have been proposed by researchers. In this paper, we take into consideration some of these proposed measures and compare them with respect to their ability to predict the development effort, especially when used in combination with measures of functional size. A few methods for estimating software development effort \u2013both based on model building and on analogy\u2013 are experimented with, using different types of functional size and elaboration complexity measures. All the most significant models obtained were based on a notion of computation density that is based on the number of computation flows in functional processes. When using estimation by analogy, considering functional complexity in the selection of analogue projects improved accuracy in all the evaluated cases. In conclusion, it appears that functional complexity is a factor that affects development effort; accordingly, whatever method is used for effort estimation, it is advisable to take functional complexity into due consideration