NOVA is a code library for LISP programmers building decision support tools for software project managers.
NOVA supports a set of USC COCOMO-family models. These models offer predictions for:
How long it will take to build a software; measured in elapsed months; How many months of effort are required during those elapsed months (so your team size is effort/months); How many defects will be introduced or removed from your software; Number of projects threats; i.e how prone is your software to schedule overruns due to poor management decisions. In standard practice, these models are tuned to local conditions using historical data. NOVA is an experiment in an alternate approach. When historical data is absent, NOVA uses AI search methods to find policies that are useful across the space of possible tunings.
NOVA was written by the LISP gang at West Virginia University's CSEE department, from a code base initialized by Tim Menzies (http://menzies.us).
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