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Explaining the Cost of European Space and Military Projects
|IEEE Computer Society, Technical Council on Software Engineering; Association for Computing Machinery -ACM-, Special Interest Group on Software Engineering -SIGSOFT-:|
International Conference on Software Engineering 1999. Proceedings. Preparing for the software century
New York: ACM Press, 1999
S.303-312 : Ill., Lit.
|International Conference on Software Engineering (ICSE) <21, 1999, Los Angeles/Calif.>|
|Fraunhofer IESE ()|
| economies of scale; model specification; software cost estimation|
There has been much controversy in the literature on several issues underlying the construction of parametric software development cost models. For example, it has been argued whether (dis)economies of scale exist in software production, what functional form should be assumed between effort and product size, whether COCOMO factors were useful, and whether the COCOMO factors are independent. Answers to such questions should help software organizations define suitable data collection programs and well-specified cost models. The only way to address these issues and obtain a generalizable conclusion is to investigate them on a large number of consistent data sets. In this paper we use a data set collected by the European Space Agency to perform such an investigation. To ensure a certain degree of consistency in our data, we focus our analysis on a set of space and military projects that represent an important application domain and the largest subset in the database. These projectshave be en performed, however, by a variety of organizations. First, our results indicate that two functional forms are plausible between effort and product size: linear and log-linear. This also means that different project subpopulations are likely to follow different functional forms. Second, besides product size, the strongest factor influencing cost appears to be team size. Larger teams result in substantially lower productivity, which is interesting considering this attribute is rarely collected in software engineering cost data bases. Third, although some COCOMO factors appear to be useful and significant covariates, they play a minor role in explaining project effort. Overall, the most plausible model appears to be a log-linear model involving KLOC, team size, and a principal component influenced by three COCOMO factors: reliability requirements (RELY), storage constraints (STOR), and execution time constraints (TIME). High values for these factors are likely to be associatedwith emb e dded systems, which usually share these characteristics.