Productivity Assessment of Neural Code Completion

A study examining how neural code completion tools affect developer productivity by comparing user perceptions with objective usage metrics across a real-world user base. Finds that suggestion acceptance rate — rather than whether completions persist in the codebase over time — is the strongest driver of developers' perceived productivity gains.

Albert ZieglerEirini KalliamvakouAndrew RiceDevon RifkinEddie Aftandilian
Albert Ziegler, Eirini Kalliamvakou, Andrew Rice, Devon Rifkin, Eddie Aftandilian

Presented at

PLDI 2022 – MAPS Workshop