A certification exam is a test of knowledge on a specific subject to ensure qualification to perform a certain job or task. For the COSMIC organization, the scope of the certification exam includes the set of rules and procedures for measuring the functional size of software. The first exam was held in April 2006 and, since then, hundreds of participants from various countries have become COSMIC-certified. The motivation for the analysis reported here was to identify and investigate certification questions causing difficulties for examinees. The analysis presented is based on versions 3.1 and 4.0.1 of the COSMIC Measurement Manual and on the certification exams conducted in 2016. The data collected allows identification, for training purposes, of variations in the levels of understanding of the distinct sections of the COSMIC Measurement Manual or, if the source of wrong answers were not examinee-dependent, identification of questions needing improvements in wording.

This paper introduces the concepts of functional size measurement (FSM) patterns. These FSM patterns apply to the COSMIC FSM method and may help in solving several issues, such as being able to do an early sizing for estimation, helping inexperienced measurers in learning how to apply the COSMIC method by establishing the relationship between the method rules and the measurement results, avoiding measurement errors, and reducing measurement effort. The approach used to define FSM patterns is Design Science Research. This paper explores the motivation factors, defines the objectives of the solution, and describes the design and development of FSM patterns. FSM patterns can be defined for a portion of a functional process, a single functional process type, a set of functional process types having a main data group - or object of interest - as their common starting point, or a large set of functional processes handling multiple data groups. These types of FSM patterns have been defined as "micro FSM pattern", "basic FSM pattern", "composite FSM pattern", and "multi-composite FSM pattern" respectively. FSM patterns examples are given to demonstrate their applicability in information systems for all four FSM pattern types. Application of FSM pattern with embedded real-time systems is discussed, along with other potential usage benefits for the industry.

Measuring the performance of cloud computing-based applications using ISO quality characteristics is a complex activity for various reasons, among them the complexity of the typical cloud computing infrastructure on which an application operates. To address this issue, the authors use Bautista's proposed performance measurement framework [1] on log data from an actual data centre to map and statistically analyze one of the ISO quality characteristics: time behavior. This empirical case study was conducted on an industry private cloud. The results of the study demonstrate that it is possible to use the proposed performance measurement framework in a cloud computing context. They also show that the framework holds great promise for expanding the experimentation to other ISO quality characteristics, larger volumes of data, and other statistical techniques that could be used to analyze performance.

Mobile applications are gaining in popularity because of the significant advantages of mobile devices, such as portability, location awareness, electronic identity, and an integrated camera. However, these devices have a number of disadvantages in terms of usability, like limited resources and small screen size. Evaluating the usability of applications developed for mobile operating systems is a very important step in addressing these disadvantages and achieving success in mobile application markets, such as Apple's App Store. Usability evaluation must be tailored to all the various mobile operating systems in use, as they each have their own particular characteristics. This paper presents a mobile application usability evaluation framework for one of the most popular mobile operating systems, iOS. A set of questions is defined and applied to evaluate the usability of eleven applications available at the App Store.

The data repository of the International Software Benchmarking Standards Group (ISBSG) can be used by researchers to investigate cause and effect relationships by enabling them to study which variables contribute to achieving certain objectives, such as increasing productivity and improving quality. The ISO 9126 series proposes a number of software quality models, and a large inventory of candidate derived measures for those models. However, even if in the 25000 series (an upcoming version of ISO 9126) there is a plan to better define the base and derived measures, neither the ISO 9126 nor ISO 25000 series include a data repository or intend to create one, and without data for comparison purposes or for analyzing actual relationships across quality attributes and models, the series is challenging to use in practice. This paper concurrently analyzes ISO 9126 and the ISBSG data repository on software projects in order to identify the subset of ISO 9126 quality characteristics that is referenced in the ISBSG repository. It also identifies a number of quality-related data fields from the ISBSG which can be useful in empirical and benchmarking studies.

Function Point Analysis (FPA) measurement method was proposed primarily to measure the functional size of management information systems. The method has been criticized as an inadequate method to measure the functional size of Real Time (RT) applications. Many extensions have been made to the original method to extend its applicability to size RT applications. The Common Software Measurement International Consortium (COSMIC) designed COSMIC function point measurement method to meet the requirement of measuring a wider scope of software domains, particularly, RT applications. This paper aims to derive a convertibility equation between the two methods for small-size RT applications. A systematic conversion approach was applied using two types of conversion (using the unadjusted FPA size and transaction functions size) using 13 small-size RT applications, considering the quality of requirements, via linear and non-linear regression models. The results show that RT applications have a varied functional size for processes, in which FPA method could not quantify it adequately, mainly because of the FPA weighting system tables and the inadequate representation of data files. Moreover, the results show that there is a significant correlation between the two methods, but the conversion factor is slightly larger than the previous studies, in which the conversion factor is more than 1. However, some limitations of FPA method rules relative to RT applications cast some doubts on the possibility to extend the conversion for larger applications size.

Functional Size Measurement (FSM) has been widely adopted by software organizations over the past years. In particular, Function Point Analysis (FPA) measurement method as the eldest and the most globally FSM method used. In the middle of 90s, COSMIC measurement method was designed to cover the limitations of previous FSM methods, and to size wider scope of application domains. COSMIC measurement method had received special attention due to its novelties and merits it offers. In this respect, many organizations have moved from using FPA to the COSMIC measurement method, mainly because FPA cannot size as many software project types as COSMIC. Since there have been many projects sized with FPA are available in various databases, researchers undertook to compare the Unadjusted FPA (UFP) size and COSMIC Function Point (CFP) size unit statistically, towards converting FPA data in to its corresponding value in CFP. In the literature, there is only one conversion model that converts the size at the level of Basic Functional Components (BFCs) between the two methods. This paper examines the accuracy of the conversion model that converts the size at the level of BFCs. Moreover, this paper presents a theoretical and probabilistic conversion model that converts the FPA transaction functions size to the most likely corresponding CFP size at the level of BFCs. The proposed model considers the primary intent and the processing logic forms of each FPA transaction function BFC, measurement best practices and COSMIC method rules. The proposed model has been validated using 14 industrial business applications. The model was found to adequately and high accurately convert all the projects tested precisely. The model might be useful for companies that are using both methods or planning to adopt the COSMIC method as a conversion or validation procedure.

SUMMARY Measurement based on the international standards for measurement (i.e., metrology) is not the same as judgmental‐based quantification of implicit relationships across a mix of entities and attributes without due consideration of admissible mathematical operations on numbers of different scale types. This paper presents first the Measurement Information Model in ISO 15939 and clarifies next what in it refers to the classical metrology field, and what refers to the quantitative analysis of relationships. The paper concludes with two examples of the designs of a measure for ISO 9126, one focusing on a single attribute and the second attempting to quantify a set of relationships across a number of entities and attributes. Copyright © 2010 John Wiley & Sons, Ltd.

Agile Project Management (APM) must adopt dynamic project plans to better handle the uncertainty and unpredictability associated with the Agile Software Development (ASD) methodologies. For these dynamic project plans, the functional size of the evolving requirements can be measured with COSMIC measurement method. To support this measurement activity, the quality of the documentation of the user stories, which represent the user requirements, is important to be interpreted correctly. In the research reported here, the COSMIC method is used to analyze and report on the quality of the documentation of user stories.

Abstract This paper is concerned with the identification and measurement of reuse within projects in which functional enhancements have been added to existing software applications. The proposed approach is based on the measurement of reuse from a functional perspective rather than from a technical perspective. Two key concepts are introduced: a reuse indicator and a predictor ratio. The reuse indicator is derived from an analysis of the function types as currently defined in Function Points Analysis. The predictor ratio is derived from an understanding of the avoided‐cost concept and of how it can be captured using historical databases of function points from previous development projects. This paper indicates how, in functional enhancement projects, the predictor ratio can be combined into the reuse indicator to derive an alternative size measure which takes into account functions reused and not redeveloped. The paper also demonstrates how these ratios can then be integrated in a maintenance productivity model to analyse the benefits of reuse by taking into account the avoided cost of functions reused. A case study based on an industrial data set is provided to illustrate the measurement of functional reuse in an enhancement project and its impact in maintenance productivity analysis.