Elements of simulation
Software engineering metrics and models
Software engineering metrics and models
An empirical validation of software cost estimation models
Communications of the ACM
Cost estimation for software development
Cost estimation for software development
Modern structured analysis
Function point analysis
Function Points in the Estimation and Evaluation of the Software Process
IEEE Transactions on Software Engineering
Quality assurance potential of analyst/designer workbenches
Information and Software Technology - Software quality assurance
An experiment in software sizing with structured analysis metrics
Journal of Systems and Software
A comparison of Albrecht's function point and Symons' Mark II metrics
ICIS '92 Proceedings of the thirteenth international conference on Information systems
Empirical studies of assumptions that underlie software cost-estimation models
Information and Software Technology
Elements of Software Science (Operating and programming systems series)
Elements of Software Science (Operating and programming systems series)
Function Point Analysis: Difficulties and Improvements
IEEE Transactions on Software Engineering
Structured Analysis and System Specification
Structured Analysis and System Specification
A Causal Model for Software Cost Estimating Error
IEEE Transactions on Software Engineering
Formalization Studies in Functional Size Measurement: How Do They Help?
IWSM '09 /Mensura '09 Proceedings of the International Conferences on Software Process and Product Measurement
ICSP'08 Proceedings of the Software process, 2008 international conference on Making globally distributed software development a success story
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Software size estimates provide a basis for software cost estimation during software development. Hence, it is important to measure the system size reliably as early as possible. Two of the best known specification level metrics, Albrecht's function points (A.J. Albrecht, 1979) and DeMarco's function bang metrics (T. DeMarco, 1982) are compared by a simulation study in which automatically generated randomized dataflow diagrams (DFDs) were used as a statistical sample to automatically count function points and function bang in a built CASE environment. These value counts were correlated statistically using correlation coefficients and regression analysis. The simulation study permits sufficient variation in the base material to cover most types of system specifications. Moreover, it allows sufficient sampling sizes to make statistical analysis of data. The obtained results show that in certain cases there is a relatively good statistical correlation between these metrics.