If you have a bug in your evaluator program, nl will produce, most probably, the following error:

your program returned 198
verify that your program is a function evaluator program
r(198);

The error indicates that your program cannot be evaluated.

The best way to spot any issues in your evaluator program is to run it interactively. You just need to define your sample (usually observations where none of the variables are missing), and a matrix with values for your parameters. Let me show you an example with nlces2. This is the code to fit the CES production function, from the documentation for the nl command:

cscript
program nlces2
version 12
syntax varlist(min=3 max=3) if, at(name)
local logout : word 1 of `varlist'
local capital : word 2 of `varlist'
local labor : word 3 of `varlist'
// Retrieve parameters out of at matrix
tempname b0 rho delta
scalar `b0' = `at'[1, 1]
scalar `rho' = `at'[1, 2]
scalar `delta' = `at'[1, 3]
tempvar kterm lterm
generate double `kterm' = `delta'*`capital'^(-1*`rho') `if'
generate double `lterm' = (1-`delta')*`labor'^(-1*`rho') `if'
// Fill in dependent variable
replace `logout' = `b0' - 1/`rho'*ln(`kterm' + `lterm') `if'
end

webuse production, clear
nl ces2 @ lnoutput capital labor, parameters(b0 rho delta) ///
               initial(b0 0 rho 1 delta 0.5)

Now, let me show you how to run it interactively:

webuse production, clear
*generate a variable to restrict my sample to observations
*with non-missing values in my variables
egen u = rowmiss(lnoutput capital labor)

*generate a matrix with parameters where I will evaluate my function
mat M = (0,1,.5)
gen nloutput_new = 1 
nlces2 nloutput_new capital labor if u==0, at(M)  

This will evaluate the program only once, using the parameters in matrix M. Notice that I generated a new variable to use as my dependent variable. This is because the program nlces2, when run by itself, will modify the dependent variable.
When you run this program by itself, you will obtain a more specific error message. You can add debugging code to this program, and you can also use the trace setting to see how each step is executed. Type help trace to learn about this setting.

Another possible source of error (which will generate error r(480) when run from nl) is when an evaluator function produces missing values for observations in the sample. If this is the case, you will see those missing values in the variable nloutput_new, i.e., in the variable you entered as dependent when running your evaluator by itself. You can then add debugging code, for example, using codebook or summarize to examine the different parts that contribute to the substitution performed in the dependent variable.

For example, after the line that generates `kterm’, I could write

summarize `kterm' if u == 0

to see if this variable contains any missing values in my sample.

This method can also be used to debug your function evaluator programs for nlsur. In order to preserve your dataset, you need to use copies for all the dependent variables in your model.