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Author: search.filters.author.Shet, K.C.Subject: search.filters.subject.Software estimation

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    Estimating and prediction of turn around time for incidents in application service maintenance projects
    (Academy Publisher, 2008) Basavaraj, M.J.; Shet, K.C.
    Application Service Maintenance Projects normally deals with Incidents as First Level support function. Incidents in majority directly link with Production Environment, so Turn around Time for Incidents is a significant factor. Many Companies are having Service Level Agreements with Customer for Turn around Time for Incidents. There is a need to focus on Estimating and Predicting Turn around Time for Incidents. Improvement in Turn around Time helps in improving the Service Level Agreements earlier agreed with the Customer. Saved time can be diverted to other Project Activities like Enhancements or for new requests. This will also helps as one of the paths for Companies to get new business with the Customer. We have used Capability Maturity Model Integration(CMMI)V1.2 Quantitative Project Management(QPM) methodology for Application Service Maintenance(ASM) Projects for estimating and predicting turn around time for incidents. By implementing this best practice in SEI CMMI Level 5 Company we have achieved a significant improvement of approximately 50 percent reduction in Average Turn around Time for incidents. © 2008 Academy Publisher.
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    Empirical validation of software development effort multipliers of intermediate COCOMO model
    (2008) Basavaraj, M.J.; Shet, K.C.
    Intermediate COCOMO Model computes effort as a function of program size and a set of cost drivers. Effort adjustment factor (EAF) is calculated using 15 cost drivers. EAF is an important significant factor in computing software development effort. We have taken one delivered development project of size of 479 function points and planned for 917 Person days of SEI CMM Level 5 "Excellent" Company as a case study to analyze the EAF. We have empirically validated the cost driver model for Intermediate COCOMMO using this projects data. Validation has been done by using other two development projects data of Excellent Company. From our analysis, we have found that cost drivers defined ratings need to be revisited for the projects of size less than 10 Person months. We have come out with ratings for some cost drivers where earlier it was not defined. This approach helps the project managers to anticipate and estimate the efforts for development projects preferably less than 10 Person months. We have achieved approximately 30% improvement in effort variance by following this approach. © 2008 Academy Publisher.