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.

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 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