Machine learning for detecting bugs

Requires presentation , word document and experiments using orange for machine learning Based on performance for the ppt other parts of the project would be awarded (it may run for a month ) first part of project Presentation due in 24hrs Title: Machine learning for detecting bugs in code in open source projects Objective Detect security bugs in code commits in an open source project Deliverables Text mining features for security bug detection Model for security bug detection in code commits Bug triage model that incorporates bug detection Questions (for presentation and subsequent document) 1. What information do you need to collect to detect security bugs? This information should come from the literature. 2. Have you conducted any experiments that would help you understand what information you should be collecting? That is, did you collect any data on bug commits in the Tiki project? Did you experiment how you could extract data that you need, but that you have to derive from the commits and other information? Presentation requirements (see attached parts, needs to be updated) 1. Literature review streams should capture information in deliverables and subsequent methods - See attachments below to get a fee of the articles , also areas concerning bug triage need to be explored in the stream 2. Data acquisition : should encompass were information was derived - answers Q1 above 3. Data analysis answers Q2 above Project should be done in Orange software (subsequent parts)