Using Function Point Analysis and COSMIC for Measuring the Functional Size of Real-Time and Embedded Software: a Comparison

Function Points Analysis and the COSMIC method are very often used for measuring the functional size of programs. The COSMIC method was proposed to solve some shortcomings of Function Points, including not being well suited for representing the functionality of real-time and embedded software. However, little evidence exists to support the claim that COSMIC Function Points are better suited than traditional Function Points for the measurement of real-time and embedded applications. To help practitioner choose a method for measuring real-time or embedded software, some evidence of the merits and shortcomings of the two methods is needed. Accordingly, our goal is to compare how well the two methods can be used in the functional measurement of real-time and embedded systems. To this end, we applied both measurement methods to the situations that occur quite often in real-time and embedded software and are not considered by standard measurement practices. Our results indicate that, overall, COSMIC Function Points are better suited than traditional Function Points for measuring characteristic features of real-time and embedded systems

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

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

Cocomo II as productivity measurement: a case study at KBC.

Software productivity is generally measured as the ratio of size over effort, whereby several techniques exist to measure the size. In this paper, we propose the innovative approach to use an estimation model as productivity measurement. This approach is applied in a case-study at the ICT-department of a bank and insurance company. The estimation model, in this case Cocomo II, is used as the norm to judge about productivity of application development projects. This research report describes on the one hand the set-up process of the measurement environment and on the other hand the measurement results. To gain insight in the measurement data, we developed a report which makes it possible to identify productivity improvement areas in the development process of the case-study company.

A Report on Using Simplified Function Point Measurement Processes

Background: Function Point Analysis is widely used, especially to quantify the size of applications in the early stages of development, when effort estimates are needed. However, the measurement process is often too long or too expensive or requires more knowledge than available when development effort estimates are due. To overcome these problems, simplified methods have been proposed to measure Function Points. Objectives: The work reported here concerns the experimentation of simplified functional size measurement methods in the sizing of both \u201ctraditional\u201d and real-time applications. The goal is to evaluate the accuracy of the sizing with respect to full-fledged Function Point Analysis. Method: A set of projects, which had already been measured by means of Function Point Analysis, have been measured using the NESMA and Early&Quick Function Points simplified processes: the resulting size measures were compared. Results: while NESMA indicative method appears to quite overestimate the size of the considered applications, the other methods provide much more accurate estimates of functional size. EQFP methods proved more accurate in estimating the size of non Real-Time applications, while the NESMA estimated method proved fairly good in estimating both Real-Time and non Real-Time applications. Conclusions: The results of the experiment reported here show that in general it is possible to size software via simplified measurement processes with an 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 internals of both data and operations

Un Procedimiento de Medición de Tamaño Funcional para Modelos Conceptuales en entornos MDA

Esta tesis presenta el diseño, la aplicación y la automatización de un procedimiento de medición de tamaño funcional basado en el método COSMIC, que permite medir el tamaño funcional de aplicaciones generadas en entornos MDA en sus modelos conceptuales.Marín Campusano, BM. (2008). Un Procedimiento de Medición de Tamaño Funcional para Modelos Conceptuales en entornos MDA. http://hdl.handle.net/10251/12305Archivo delegad

Towards the automation of a defect detection protocol for functional size measurements

There is a need to develop formal protocols to verify the accuracy of software functional size measurements and to calibrate the measurement processes. These protocols offer a mechanism for accomplishing such verification regardless of who performed the measurements (an expert or an automated tool). The detailed analysis of functional size measurement procedures results is necessary to understand the nature of the defects. The automation of these protocols decreases the effort and time required to verify the measurements accuracy and supports the calibration of procedures and tools for functional size measurement. This paper presents an empirical study for evaluating the results of a prototype tool that automates an accuracy verification protocol for IFPUG FPA measurements. Our tool uses a graph-based model to search for the causes of measurement mismatches detected in the verification process. The current prototype has reached an accuracy of 93.92%, a precision of 98.69% and a recall of 94.94%.Ministerio de Ciencia, Tecnología y Telecomunicaciones//MICITT/Costa RicaUniversidad de Costa Rica/[834-B5-A18]/UCR/Costa RicaUCR::Vicerrectoría de Docencia::Ingeniería::Facultad de Ingeniería::Escuela de Ciencias de la Computación e InformáticaUCR::Vicerrectoría de Investigación::Unidades de Investigación::Ingeniería::Centro de Investigaciones en Tecnologías de Información y Comunicación (CITIC