Design and evaluate a Difference-in-Differences (DiD) approach to estimate the effect of a new coding policy on developer productivity.

Instruction: Outline a study design using the DiD methodology to measure the causal impact of implementing a new coding standard policy across different teams within a tech company. Discuss potential data requirements, control and treatment group selection, and how you would address possible sources of bias.

Context: This question requires the candidate to demonstrate their understanding of the Difference-in-Differences (DiD) approach as a quasi-experimental design for causal inference. The candidate needs to show their ability to design a study that accounts for time and group differences, select appropriate control and treatment groups, and discuss how to manage confounders and biases in the study setup.