Part4: Debugging in R

  Debugging tools are built with R do not part of any package. There are couple of indications that something is not right. It could be a diagnostic message something to happed.Basically three type of main indications.

1. message: A generic notification/diagnostic message produced by the message function; execution of the function continues 
2. warning: An indication that something is wrong but not necessarily fatal;execution of the function continues generated by the warning function 
3. error: An indication that a fatal problem has occurred; execution stops;produced by the stop function

condition: A generic concept for indicating that something unexpected can occur; programmers can create their own conditions

So this is our basic warning,  take a log of negative number

>log(-1)
[1] NaN
Warning message:
In log(-1) : NaNs produced

The below function gives a message when the value of x is greater than one or less than one. The function invisible hide the value of x in output 

printmessage <- function(x) 
{if(x > 0)
print("x is greater than zero")
else
print("x is less than or equal to zero")
invisible(x)  
}

The output when x = 1.

> printmessage(1)
[1] "x is greater than zero"

 The value of x is NA gives an error in output. It expecting a logical value True or False. This problem is fixed in below function. This function check the value is NA.

printmessage2 <- function(x) {
if(is.na(x))
print("x is a missing value!")
else if(x > 0)
print("x is greater than zero")
else
print("x is less than or equal to zero")
invisible(x)
}

The output of the function when x = log(-1) is

> x <- log(-1)
Warning message:
In log(-1) : NaNs produced
> printmessage2(x)
[1] "x is a missing value!"

How do you know that something is wrong with your function?

• What was your input? How did you call the function?
• What were you expecting? Output, messages, other results?
• What did you get?
• How does what you get differ from what you were expecting?
• Were your expectations correct in the first place?
• Can you reproduce the problem (exactly)?

 Debugging Tools in R

The primary tools for debugging functions in R are

1. traceback: prints out the function call stack after an error occurs; does nothing if there’s no error 
2. debug: flags a function for “debug” mode which allows you to step through execution of a function one line at a time 
3. browser: suspends the execution of a function wherever it is called and puts the function in debug mode 
4. trace: allows you to insert debugging code into a function a specific places 
5. recover: allows you to modify the error behavior so that you can browse the function call stack

These are interactive tools specifically designed to allow you to pick through a  function. There’s also the more blunt technique of inserting print/cat statements in
the function.
  
traceback

> mean(x)
Error in mean(x) : object ’x’ not found
> traceback()
1: mean(x)
>  
> lm(y ~ x)
Error in eval(expr, envir, enclos) : object ’y’ not found
> traceback()
7: eval(expr, envir, enclos)
6: eval(predvars, data, env)
5: model.frame.default(formula = y ~ x, drop.unused.levels = TRUE)
4: model.frame(formula = y ~ x, drop.unused.levels = TRUE)
3: eval(expr, envir, enclos)
2: eval(mf, parent.frame())
1: lm(y ~ x)

debug

> debug(lm)
> lm(y ~ x)
debugging in: lm(y ~ x)
debug: {
ret.x <- x
ret.y <- y
cl <- match.call()
...
if (!qr)
z$qr <- NULL
z
}
Browse[2]>
Browse[2]> n
debug: ret.x <- x
Browse[2]> n
debug: ret.y <- y
Browse[2]> n
debug: cl <- match.call()
Browse[2]> n
debug: mf <- match.call(expand.dots = FALSE)
Browse[2]> n
debug: m <- match(c("formula", "data", "subset", "weights", "na.action",
"offset"), names(mf), 0L)

 recover

> options(error = recover)
> read.csv("nosuchfile")
Error in file(file, "rt") : cannot open the connection
In addition: Warning message:
In file(file, "rt") :
cannot open file ’nosuchfile’: No such file or directory
Enter a frame number, or 0 to exit
1: read.csv("nosuchfile")
2: read.table(file = file, header = header, sep = sep, quote = quote, dec =
3: file(file, "rt")
Selection:

Summary

• There are three main indications of a problem/condition: message, warning, error;only an error is fatal

• When analyzing a function with a problem, make sure you can reproduce the problem, clearly state your expectations and how the output differs from your expectation

• Interactive debugging tools traceback, debug, browser, trace, and recover can be used to find problematic code in functions

• Debugging tools are not a substitute for thinking!