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In the last few years it has been seen that many software vendors have started delivering projects incrementally with very short release cycles. Best examples of success of this approach has been Ubuntu Operating system that has a 6 months release cycle and popular web browsers such as Google Chrome, Opera, Mozilla Firefox. However there is very little knowledge available to the project managers to validate the chosen release cycle length. We propose a decision support system that helps to validate and estimate release cycle length in the early development phase by assuming that release cycle length is directly affected by three factors, (i) choosing right requirements for current cycle, (ii) estimating proximal time for each requirement, (iii) requirement wise feedback from last iteration based on product reception, model accuracy and failed requirements. We have altered and used the EVOLVE technique proposed by G. Ruhe to select best requirements for current cycle and map it to time domain using UCP (Use Case Points) based estimation and feedback factors. The model has been evaluated on both in-house as well as industry projects.
Context:Software Development Analytics is a research area concerned with providing insights to improve product deliveries and processes. Many types of studies, data sources and mining methods have been used for that purpose. Objective:This systematic
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