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<p>How much will it cost?" "How long will it take?" These questions are notoriously difficult to answer accurately and early in software development. Software metrics tackle this problem by assuming a statistical correlation between the size of a software project and the amount of effort typically required to realize it. To be useful in estimating cost, a size metric must take into account the inherent complexity of the system. Such metrics have been applied with varying degrees of success, but the nature of software development has been changing, and some of the assumptions behind the established cost-estimation techniques are slowly being invalidated. The System Meter (SM) is a new software sizing approach based on the notion of system description. System descriptions encompass all kinds of software artifacts, from requirement documents to final code. For each kind or level of artifacts, there is a corresponding flavor of SM. In our studies we used the first operational flavor, the SM at the preliminary analysis level, or Pre-SM. In contrast to the well-known Function Point (FP) metric, which is measurable after the more detailed but costly phase of domain analysis only, the SM explicitly takes OO concepts into account. It also distinguishes between components to be developed and those to be reused, thus reflecting the idea of incremental functionality. In this article we present results of a field study of 36 projects developed using object technology. We measured both FP and the Pre-SM method in all 36 projects and compared their correlation to the development effort. </p>

O. Nierstrasz and S. Moser, "The Effect of Object-Oriented Frameworks on Developer Productivity," in Computer, vol. 29, no. , pp. 45-51, 1996.
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