Chapter 9
Debugging and Profiling
9.1 Introduction
In this chapter we provide some guidance on tools and strategies that should
make debugging your code easier and faster. Basically, you must first try to
identify the source of the error. While it is generally easy to find where the
program actually failed, that is not usually the place where the programming
error occurred. Some bugs are reproducible; that is, they occur every time a
sequence of commands is executed on all platforms, and others can be more
elusive; they arise intermittently and perhaps only under some operating sys-
tems. One of the first things that you should do when faced with a likely bug
is to try and ensure its reproducibility. If it is not easily reproduced, then
your first steps should be to find situations where it is, as only then is there
much hope of finding the problem.
One of the best debugging strategies is to write code so that bugs are
less likely to arise in the first place. You should prefer the use of simple
short functions, each performing a particular task. Such functions are easy to
understand and errors are often obvious. Long, convoluted functions tend to
b oth give rise to more bugs and to be more dicult to debug.
This chapter is divided into several sections. First we discuss the browser
function, which is the main tool used in debugging code in R. R functions such
as debug, trace and recover make use of browser as a basic tool. The debugging
to ols are all intended primarily for interactive use and most require some form
of user input. We then discuss debugging in R, beginning by recommending
that static code analysis using functions from the codetools package be used,
and then covering some of the basic tools that are available in R. Then we cover
debugging procedures that can be applied to detect problems with underlying
compiled code. We conclude by discussing tools and methods for profiling
memory and the execution of R functions.
274 R Programming for Bioinformatics
9.2 The browser function
The browser function is the building block for many R debugging techniques.
A call to browser halts evaluation and starts a special interactive session where
the user can inspect the current state of the computations and step through
the code one command at a time. The browser can be called from inside any
function, and there are ways to invoke the browser when an error or other
exception is raised.
Once in the browser, users can execute any R command; they can view
the local environment by using ls; and they can set new variables, or change
the values assigned to variables simply by using the standard methods for
assigning values to variables. The browser also understands a small set of
commands specific to it. A summary of the available browser commands
and other useful R commands are given in Table 9.1 and Table 9.2. Of these,
p erhaps the most important to remember for new users is Q, which causes R to
quit the debugger and to return control to the command line. Any user input
is first parsed to see if it is consistent with a special debugger instruction and,
if so, the debugger instruction will be performed. Most of these commands
consist of a single letter and are described below. Any local variable with the
same name as one of these commands cannot be viewed by simply typing its
name, as is standard practice in R, but rather will need to be wrapped in a
call to print.
ls() list the variables defined inside the function
x print the value of variable x
print(x) print the value of variable x useful when x is one of n, l, Q or cont
where print the call stack
Q stop the current execution and return to the top-level R interpreter
Table 9.1: Browser commands with non-mo dal functionalities.
When the browser is active, the prompt changes to Browse[i]> for some
p ositive integer i. The browser can be invoked while a browser session is
active, in which case the integer is incremented. Any subsequent calls to
browser are nested and control returns to the previous level once a session has

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