Train and test data fixed during boosting?

I have question about boosting algorithm.

I know that boosting is a sequential process and it gives high weight to misclassification of previous model.

Then, its' train and test data are fixed through this sequential process?

Is it predicting data used for training to determine if it is misclassification, and then giving a larger weight to training the model?

Thanks in advance

discussion