• Journal of Internet Computing and Services
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• v.8 no.4
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• pp.105-117
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• 2007

In order to succeed in a bid or development, the project manager should estimate its cost and schedule more accurately in the early stage of the project. Usually, the nominal schedule of most projects can be derived from rule of thumb, first-order estimation practice, or ball-park schedule estimation table. But the rule-of-thumb models for the nominal schedule estimation are so various, and the first-order estimation practice does not provide sufficient information. So they do not help much to decide on the proper development effort and schedule for a particular size of project. This paper presents a statistical regression model for deciding the development effort and schedule of a project using the ball-park schedule estimation table. First, we have redefined such words suggested in the ballpark schedule estimation table as shortest possible schedule, efficient schedule and nominal schedule, Next, we have investigated the relationship between the development effort and the schedule. Finally, we have suggested a model for estimating the development effort and the more accurate schedule of such particular sizes of software as are not presented in the ball-park schedule estimation table. The experimental results show that our proposed regression analysis model decreases the mean magnitude of relative error by 2% at maximum. Also this model can estimated the development effort and schedule for a particular size of software.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.13 no.4
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• pp.99-106
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• 2013

Generally, software development schedule compression is decided within 75% of nominal schedule. However, there are some difficulties when we judge the possibility of development schedule compression because a nominal schedule has not been definitely. Therefore, this paper investigates various nominal schedule estimation models and decides the optimum range. Basing on the performance of ISBSG Release 8,614 projects are extracted from the actual 1,595 projects. We presented development effort estimation model from those data. Also, we derived the development schedule model from the development effort. When you apply the proposed model, you will be able to estimate development effort and schedule required for the development more actually.