Develop a cosysmo prediction of person months

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Reference no: EM132454749

CoSysMo is a detailed, systems engineering planning tool. It predicts person months by looking at size and effort factors. The SolarSPELL project at ASU needs your help in predicting how much it will cost to set-up SolarSPELL in Fiji, Comoros, Puerto Rico, and Tonto Creek Camp. In addition, your design contribution is realizing that while SolarSPELL has a functional Web server, you need to develop solar charging stations for the laptops and devices that access SolarSPELL in remote locations with no electrical grid power. They have past data for the"calibration" factor called "A" in the equation from previous projects. The resources you have to help you are solarspell.org.

Please develop a CoSysMo prediction of person months (pm) required given the following data:

Question i. Previous performance against CoSysMo predictions that used an "A" = 1 are as follows:

Prediction using A = 1 Actual PM Required

125 pm           150 pm

85 pm            102 pm

105 pm           126 pm

Question ii. Economies of Scale are nominal at 1.0

Question iii. Requirements are balanced between normal and difficult with 100 of each.

Question iv. Estimate the number of interfaces and decide how many are easy, normal, and difficult, and why you reached these conclusions.

Question v. We have only two (2) nominal algorithms to develop.

Question vi. Describe and estimate the number of scenarios that must be managed and decide how many are easy, normal, and difficult, and why.

Question vii. SolarSPELL has done something similar in the past so our understanding of the requirements is nominal.

Question viii. The technical risk and architectural understanding are low for this effort.

Question ix. Because of student help and instructor turn over at remote locations, continuity of our team has been low and must be addressed, but you need to validate these assumptions.

Question x. There are also other effort cost drivers, please estimate those and their level of severity, and show why.

Reference no: EM132454749

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