Understanding How CodeLLMs (Mis)Predict Types with Activation Steering

CodeLLMs are transforming software development as we know it. This is especially true for tasks where rule-based approaches fall short, like type prediction. The type prediction task consists in adding a new type annotation to a partially typed program, such that the resulting program is closer to being fully typed. The intractability of rule-based approaches and high cost of manual annotation make CodeLLMs an attractive solution to the problem. However, CodeLLMs are still far from being deployed on the large-scale due to doubts surrounding their reliability.