Traceability/Code Clones

Learning Outcomes

• describe how ML can be used to connect software artifacts
• identify four types of code clones and their potential benefits and harms

Before Class

Lectures

• No lecture notes for this module.

Readings

• Roy and Cordy, A Survey on Software Clone Detection Research Section 1-7, and then 16-17.
• Majdinasab et al., Trained without My Consent: Detecting Code Inclusion in Language Models Trained on Code Sections 1,2, 3.2, 3.3, 4.2, 4.5,5.1,7,8,9

In Class

Slides

• In-class notes

• exercise

Optional Readings and Activities

• Germán, cregit: token-level blame information in git version control repositories
• Cleland-Huang, A machine learning approach for tracing regulatory codes to product specific requirements
• Guo, Semantically Enhanced Software Traceability using DL Techniques