Computer Science CS134
Debugging (due 5pm Thursday)
Objective. Developing skills that help nd mistakes in programs.
This week we’re going to look at a number of small scripts or programs that are not currently functional.
This lab considers code that might have three types of errors:
1. Syntax errors. The\
se are textual errors that are identi ed by Python before it attempts to run
the program. For example, if you misspell the keyword for as fro, Python will complain that your
syntax is incorrect. These errors, while annoying, are typically the easiest to correct.
2. Runtime errors. When the program begins running, there are some conditions that may unexpectedly arise that Python will complain about. For example, suppose you compute the average of a list
speeds in the following de nition, found in a le physics.py:
it is possible that speeds is empty. If so, the computation attempts to illegally divide by zero:
Traceback (most recent call last):
File “physics.py”, line 29, in meanSpeed
ZeroDivisionError: division by zero
3. Logic errors. Sometimes when we translate an algorithm into code we may introduce mistakes in
logic. If we pick a random character from a 6 character string by selecting a random integer between
1 and 6, we are forgetting that string indices start at 0, not 1. That’s a mistake of logic.
As we investigate our scripts this week, we will want to carefully read the hints that Python gives us. For
example, when syntax error messages are printed, they include line numbers. The error is very likely at
or before that line number. Fortunately, all modern editors show us line numbers for the current location.
When runtime errors occur, the Python system often prints a stack trace or traceback. This is a list
of lines in the program that are currently being executed. Information about the most recent line appears
near the bottom of the trace. Carefully reading the stack trace can give you important clues about what
your program was doing when it stopped running.
The hardest errors to x are logical errors. Since these errors stem from bad assumptions about the
state of the program, it is often helpful to get a better view of the program’s variables. The judicious use
of print statements can help to isolate sections of the code that lead to unexpected values in state. This
process, however, can take a long time as you run multiple experiments with di erent print statements
in di erent locations. A more interactive approach is to use a debugger , like the builtin debugger pdb, or
a web-based program visualizer, like the Python Tutor1
To get started, you should clone the lab4 repository in the usual manner:
git clone https://evolene.cs.williams.edu/cs134-labs/22xyz3/lab04.git ~/cs134/lab04
https://docs.python.org/3/library/pdb.html and http://www.pythontutor.com
Required Tasks. We would like you to x errors in at least two of the scripts we’ve included in this
week’s repository. These scripts have varied purposes:
1. The prime.py script. Ideally, when this script is working, you can run it as follows:
$ python3 prime.py 17
17 is prime.
The script contains a number of errors that should be xed before it is fully functional. You should
think about values that would be good to test.
2. The shuffle.py script. This script reads all the arguments that are provided and prints them,
possibly shued. For example, the following is a possible behavior:
$ python3 shuffle.py a b c
c a b
Again, think about ways that you could test the functioning of this script.
3. The rot13.py script. This is an implementation of the rotate-by-13 cypher once used by unix. It
reads input, translates it, and writes the rotated text on the output. You can use it in the following
way to translate hello into uryyb (remember, input is ended by hitting Control-D):
$ python3 rot13.py
We’ve included a more extensive test as well. When the program works, you can run rot13.input
through the script and test to see if it matches the ideal rot13.output (a list of pangrams) with:
$ python3 rot13.py <rot13.input | diff – rot13.output
Any di erences reported suggest remaining errors.
4. The cribbage.py script. This script allows you to score a hand in cribbage. The precise scoring is
described in the script and requires care. This is the hardest script to x. You can run it in the
following way to score a cribbage hand with three 2’s and two 9’s:
$ python3 cribbage.py 2S 2D 2H 9C 9S
The score is 12.
(The three 2’s count for 6, the two 9’s count for 2, and there are two ways to sum to 15, for 4 more.)
Each of these scripts contains several errors. Your grade will depend on how carefully you’ve tested the
scripts. Again, you need only correct two scripts, but more experience will make you a better programmer.
Submit your work. As you nish identifying and removing bugs in each script, do not forget to add,
commit, and push your work to the server for grading.