AEMOS or AI Enabled Multi Objective Scheduler is a system written in Python used for optimizing software test cases by using a combination of classic AI techniques (heuristics and Simulated Annealing), clustering and a flexible representation based on STRIPS.
This code implements the research done in my Master's Degree Thesis.
A project created as a final assignment for an Intelligent Systems class, it is a C++ application that uses the EASEA Genetics framework to solve a software test case optimisation problem.
Part of the theory was used as reference for my Master's Degree Thesis.
risk rank pro:
A Python application presented as the final project for a Data Mining class. It consists of an static code analizer that scans python code for module references and using an implementation of Google PageRank calculates the risk of performing a code change. The result is a list of modules ranked by the risk that a change represents.