A receiver operating characteristic curve, or ROC curve, is a graphical plot that illustrates the performance of a binary classifier model at varying threshold values.
The ROC curve is the plot of the true positive rate (TPR) against the false positive rate (FPR) at each threshold setting.
To draw a ROC curve, only the true positive rate (TPR) and false positive rate (FPR) are needed (as functions of some classifier parameter). The TPR defines how many correct positive results occur among all positive samples available during the test. FPR, on the other hand, defines how many incorrect positive results occur among all negative samples available during the test.
See https://en.wikipedia.org/wiki/Receiver_operating_characteristic for more discussions.