Durbin Watson test it's not applicable in small sample sizes. If your data set has more than p*10 (number of independent variables * 10) observations then you can consider it large. If your data set has less than p*5 observations than you can consider it small. In a case of small sample, DW test cannot be applied and in such a situation bootstrap procedure may be a solution to this problem.
Also you can check the table of Critical Values of the Durbin-Watson Statistic to see if they are correlated or not, because DW ~2 it's a rule of thumb, also DW ~1.6 value are used often.