Estimation and measurement of the size of software is crucial for project management activities. Functional size measurement is one of the most frequently used methods to measure size of software and COSMIC is one of the popular methods for functional size measurement. Although precise size measurement is critical, the results may differ because of the errors made in the measurement process. The erroneous measurement results cause lack of confidence for the methods as well as reliability problems for effort and cost estimations. This research proposes an error prevention model for COSMIC Functional Size Measurement method to increase the reliability of the measurements. The prevention model defines data movement patterns for different types of the functional processes and a cardinality table to prevent errors. We validated the prevention model with two different case studies and observed that it can decrease errors up to 90% in our case studies.

Functional size is among the few software size measures for which well-structured and standardized methods exists for its measurement. Although Functional Size Measurement(FSM) methods have gone a long way, one ongoing criticism on FSM methods is the discrepancies in the measurement results of the same software obtained by different measures. In this thesis study the sources of discrepancies that involve the functional properties of measurands and constructs of the FSM method models are investigated in two exploratory case studies. In the light of the findings, a software functionality model for functional size measurement is proposed. The model is founded on a characterization of software functionality from a requirements engineering point of view and it aims is to facilitate reliable size measurements on the basis of formalized concepts and rules. Two case studies are conducted in order to evaluate the applicability of the model and validate its effectiveness.

The cost and effort estimation of projects depend on software size. A software product size is needed at as early a phase of the project as possible. Conventional Early Functional Size Estimation methods generate size at the early phase but result in subjectivity and unrepeatability due to manual calculation. On the other hand, automated Functional Size Measurement calculation approaches require constructs which are available in considerably late software development phases. In this study we developed an approach called e-Cosmic to calculate and automate the functional size measurement based on the business processes. Functions and input and output relationship types of each function are identified in the business process model. The size of each relationship type is determined by assigning appropriate data movements based on the COSMIC Measurement Manual. Then, relationship type size is aggregated to produce the size of each function. The size of the software product is the sum of the size of these functions. Automation of this process based on business process model is performed by developing a script in the ARIS tool concept. Three case studies were conducted to validate the proposed functional size estimation method (e-Cosmic). The size of the products in the case studies are measured manually with COSMIC FSM (Abran et al, 2007) as well as using a conventional early estimation method, called Early and Quick COSMIC FFP. We compared the results of different approaches and discussed the usability of e-Cosmic based on the findings.

This thesis study aims to examine the conceptual and theoretical differences of Functional Size Measurement (FSM) methods, to identify the improvement opportunities of these methods and to develop a new FSM method. A comprehensive literature review is performed and two multiple-case studies are conducted as a research strategy. In the light of the results obtained, some improvement suggestions on two of the most challenging improvement opportunities identified for FSM methods are made &ndash / improvement opportunities which are related to the conceptual and theoretical basis of FSM and the extension of the applicability of these methods to different software functional domain types. The work behind these suggestions involves the critical examination of the concepts &ldquo / functionality&rdquo / and &ldquo / functional size&rdquo / and the depiction of &ldquo / types of functionality&rdquo / considering the components of software architecture and the forms of information processing logic performed in different software functional domain types. Based on the suggestions made, a new FSM method, called ARCHItectural DIMensions Based FSM (ARCHI-DIM) is developed conforming to the ISO/IEC 14143-1 standard. A third multiple-case study is conducted in order to evaluate the new method and to identify future directions for FSM methods.

Software size measurement provides a basis for software project management and plays an important role for its activities such as project management estimations, process benchmarking, and quality control. As size can be measured with functional size measurement (FSM) methods in the early phases of the software projects, functionality is one of the most frequently used metric. On the other hand, FSMs are being criticized by being subjective. The main aim of this thesis is increasing the accuracy of the measurements, by decreasing the number of defects concerning FSMs that are measured by COSMIC FSM method. For this purpose, an approach that allows detecting defects of FSMs automatically is developed. During the development of the approach, first of all error classifications are established. To detect defects of COSMIC FSMs automatically, COSMIC FSM Defect Detection Approach (DDA) is proposed. Later, based on the proposed approach, COSMIC FSM DDT (DDT) is developed.

Software size estimation/measurement has been the objective of a lot of research in the software engineering community due to the need of reliable size estimates. FSM Methods have become widely used in software project management to measure the functional size of software since its first publication, late 1970s. Although all FSM methods measure the functional size by quantifying the FURs, each method defined its own measurement process and metric. Therefore, a piece of software has several functional sizes when measured by different methods. In order to be able to compare functional sizes of software products measured by different methods, we need to convert them to each other. In this thesis study, the similarities and differences between four FSM methods, IFPUG FPA, Mark II FPA, COSMIC FFP and ARCHI DIM FSM are investigated and the common core concepts are presented. Accordingly a unification model of the measurement process of all four methods is proposed. The main objective of this model is to measure the functional size of a software system by applying all four methods simultaneously, using a single source of data. In order to have an infrastructure to validate the unification model by conducting empirical studies, a software tool is designed and implemented based on the unification model. Two empirical studies are conducted by utilizing the data of a real project to evaluate both the unification model proposed and the developed tool and the measurement results are discussed.

In this study, we identified one of the reasons of the low correlation between functional size and development effort which is overlooking the similarity of the functions during the mapping of the functional size and development effort. We developed a methodology (SiRFuS) that is based on the idea of the reuse of the similar functions internally to provide high correlation between functional size and development effort. The method is developed for the identification of the similar functions based on the method of Santillo and Abran. Similarity percentages among the functional processes and Similarity Reflective Functional Sizes are computed to attain adjusted functional sizes. The similarity reflective functional sizes were named as Discrete Similarity Reflective Functional Size and Continuous Similarity Reflective Functional Size based on the characteristics of the adjusted functional sizes. The SiRFuS method consists of three stages: measurement of the software product with COSMIC Functional Size Measurement (FSM) method / identification of the functional similarities bases on the measurement results and calculation of the similarity reflective functional sizes. In order to facilitate the detection of similar functions, calculation of the percentage of the similarities and similarity reflective functional sizes / a software tool is developed based on the SiRFuS method. Two case studies were performed in order to identify the improvement opportunities and evaluate the applicability of the method and the tool.

Software effort estimation still remains a challenging and debatable research area. Most of the software effort estimation models take software size as the base input. Among the others, Constructive Cost Model (COCOMO II) is a widely known effort estimation model. It uses Source Lines of Code (SLOC) as the software size to estimate effort. However, many problems arise while using SLOC as a size measure due to its late availability in the software life cycle. Therefore, a lot of research has been going on to identify the nature of relationship between software functional size and effort since functional size can be measured very early when the functional user requirements are available. There are many other project related factors that were found to be affecting the effort estimation based on software size. Application Type, Programming Language, Development Type are some of them. This thesis aims to investigate the nature of relationship between software size and development effort. It explains known effort estimation models and gives an understanding about the Function Point and Functional Size Measurement (FSM) method. Factors, affecting relationship between software size and development effort, are also identified. In the end, an effort estimation model is developed after statistical analyses. We present the results of an empirical study which we conducted to investigate the significance of different project related factors on the relationship between functional size and effort. We used the projects data in the International Software Benchmarking Standards Group (ISBSG) dataset. We selected the projects which were measured by utilizing the Common Software Measurement International Consortium (COSMIC) Function Points. For statistical analyses, we performed step wise Analysis of Variance (ANOVA) and Analysis of Co-Variance (ANCOVA) techniques to build the multi variable models. We also performed Multiple Regression Analysis to formalize the relation. / Software effort estimation still remains a challenging and debatable research area. Most of the software effort estimation models take software size as the base input. Among the others, Constructive Cost Model (COCOMO II) is a widely known effort estimation model. It uses Source Lines of Code (SLOC) as the software size to estimate effort. However, many problems arise while using SLOC as a size measure due to its late availability in the software life cycle. Therefore, a lot of research has been going on to identify the nature of relationship between software functional size and effort since functional size can be measured very early when the functional user requirements are available. There are many other project related factors that were found to be affecting the effort estimation based on software size. Application Type, Programming Language, Development Type are some of them. This thesis aims to investigate the nature of relationship between software size and development effort. It explains known effort estimation models and gives an understanding about the Function Point and Functional Size Measurement (FSM) method. Factors, affecting relationship between software size and development effort, are also identified. In the end, an effort estimation model is developed after statistical analyses. We present the results of an empirical study which we conducted to investigate the significance of different project related factors on the relationship between functional size and effort. We used the projects data in the International Software Benchmarking Standards Group (ISBSG) dataset. We selected the projects which were measured by utilizing the Common Software Measurement International Consortium (COSMIC) Function Points. For statistical analyses, we performed step wise Analysis of Variance (ANOVA) and Analysis of Co-Variance (ANCOVA) techniques to build the multi variable models. We also performed Multiple Regression Analysis to formalize the relation. / +46-(0)-739763245

Context: Software cost and effort estimation are important activities for planning and estimation of software projects. One major player for cost and effort estimation is functional size of software which can be measured in variety of methods. Having several methods for measuring one entity, converting outputs of these methods becomes important. Objectives: In this study we investigate different techniques that have been proposed for conversion between different Functional Size Measurement (FSM) techniques. We addressed conceptual similarities and differences between methods, empirical approaches proposed for conversion, evaluation of the proposed approaches and improvement opportunities that are available for current approaches. Finally, we proposed a new conversion model based on accumulated data. Methods: We conducted a systematic literature review for investigating the similarities and differences between FSM methods and proposed approaches for conversion. We also identified some improvement opportunities for the current conversion approaches. Sources for articles were IEEE Xplore, Engineering Village, Science Direct, ISI, and Scopus. We also performed snowball sampling to decrease chance of missing any relevant papers. We also evaluated the existing models for conversion after merging the data from publicly available datasets. By bringing suggestions for improvement, we developed a new model and then validated it. Results: Conceptual similarities and differences between methods are presented along with all methods and models that exist for conversion between different FSM methods. We also came with three major contributions for existing empirical methods; for one existing method (piecewise linear regression) we used a systematic and rigorous way of finding discontinuity point. We also evaluated several existing models to test their reliability based on a merged dataset, and finally we accumulated all data from literature in order to find the nature of relation between IFPUG and COSMIC using LOESS regression technique. Conclusions: We concluded that many concepts used by different FSM methods are common which enable conversion. In addition statistical results show that the proposed approach to enhance piecewise linear regression model slightly increases model’s test results. Even this small improvement can affect projects’ cost largely. Results of evaluation of models show that it is not possible to say which method can predict unseen data better than others and it depends on the concerns of practitioner that which model should be used. And finally accumulated data confirms that empirical relation between IFPUG and COSMIC is not linear and can be presented by two separate lines better than other models. Also we noted that unlike COSMIC manual’s claim that discontinuity point should be around 200 FP, in merged dataset discontinuity point is around 300 to 400. Finally we proposed a new conversion approach using systematic approach and piecewise linear regression. By testing on new data, this model shows improvement in MMRE and Pred(25). / Javad Amiri: Nabshe Kooche 3, Bolvare shadi, Farhangian 2, Qom, Iran, phone: +989127476593 Vinod Kumar: s/o P.V.Kondala Rao, Main Road Khaji Street Rajahmundry. A.P. India pin: 533101 phone: +917396449336

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]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/11237