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Assignment 4
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Using Program Analysis Tools
For this project, you will gain experience using
dynamic analysis tools on real world software.
You will work in groups of two or three students,
and the requirements will scale with the group size.
Overview
As a group, you will apply two types dynamic
analysis tools we examined in class to open source
projects and report on the results. One set of tools
will look for bugs in a preexisting set of executions,
while the other will create new executions/tests in
an effort to find bugs. Note that not all tools will
work with all programs, so the type of program that
you analyze must be compatible with the tools that
you use.
Detecting bugs in an existing test suite
Possible dynamic analysis tools for this assignment
include:
Valgrind
Clang/GCC Sanitizers
Recall that dynamic analysis tools analyze a single
execution at a time. Thus, it is common practice to
integrate the dynamic analysis tools with the test
process for a project in order to detect potential
bugs over a set of predetermined executions. In
order to apply your selected tool to a given open
source project, you shall integrate the dynamic
analysis tool into the existing test suite and
automated testing infrastructure for the project and
run the analysis over every execution in the test
suite. If you are interested in using an unlisted
dynamic analysis tool, ask to make sure that it is
appropriate. Your write-up for the assignment
should include the challenges you faced during this
process, as well as your approaches for
overcoming them. You should also report any
errors indicated by the analysis. For groups of k
members, the groups should also explain whether k
of the errors found were real bugs or not. If fewer
than k bugs were found, then all errors should be
explained. Include the full instructions for
reproducing your results based on files that you
had to modify and how.
Be careful. A very common mistake is to run
valgrind on make instead of running it on the project
you wish to analyze. We discussed issues like this
in class, and I expect you to not make this mistake.
Fuzzing
Possible fuzz testing tools for this assignment
include:
american fuzzy lop
libFuzzer
If you wish, you may alternatively try out one of
these tools, but I won’t provide support for them:
AFLFast
VUzzer
In contrast to the previous set of tools, fuzz testing
tools attempt to generate new inputs (and thus
executions) of a program and look for general
correctness issues as those new tests run. They do
not need to be integrated into a test suite, but you
sometimes need to construct a test harness for
particular functions of interest, as we saw in class.
You will use one of these fuzz testing tools to test
the behavior of a program or library when reading
in some sort of input from the user. You should run
the fuzzer for at least 8 hours. Ideally, and if you
want more interesting results, you would let it run
for longer. You can use the screen command to log
out of a machine while your tools continues to run
and then log back in later to see the results. If you
are interested in using an unlisted fuzz testing tool,
ask the instructor to ensure that it is appropriate.
Your write-up for the assignment should again
include the challenges you faced during this
process, as well as your approaches for
overcoming them. You should also report any
errors indicated by the analysis. For groups of k
members, the groups should also explain whether k
of the crashes/hangs found were real bugs or not. If
fewer than k bugs were found, then all discovered
errors should be explained. You should also explain
why fewer than k bugs were found if possible. This
may depend on both the tool and the observed
results.
In addition to this write-up, you should also submit
any test harnesses, invocations, and the full set of
constructed outputs that cause problems as well as
the overall statistics. For AFL, this means that you
should submit the crashes/ and hangs/
subdirectories of the output directory as well as the
fuzzer_stats file. For libFuzzer, you should include
any test files corresponding to failures along with
the output of the overall testing process.
Be careful. afl may warn you that the program you
are analyzing is not instrumented or that you are
only identifying one path after many executions.
These are signs that you are not correctly running
afl to fuzz the program of interest. Again, I expect
you to not make these mistakes.
Selecting Projects to Analyze
For software that you analyze should be an open
source project of some sort. Any analyzed project
should contain at least 4000 lines of code and must
include an established test suite and automated
test process. You are also free to analyze two
different projects, one for each type of tool. Once
again, you are free to consider different projects
listed on www.github.com, www.sourceforge.net,
www.openhub.net, www.gnu.org, or other major
collections of open source software. If you have
questions about the suitability of a particular
project, please ask. Finally, do not select one of the
programs that I already showed you in class.
Once again, you should identify and consider:
1. Identification of the open-source project.
2. Identification of the supporting organization.
3. Size of the code base.
4. Build time to compile and link an executable
from source code.
5. Execution time for the test suite.
Again, include this information in your report.
Submission
As a group, you should reflect on the challenges
faced, effort required, and either potential or
recieved benefits of the tools you used for the
projects you examined. What are the strengths and
weaknesses of the different types of dynamic
analysis tools that you used? Are these reflected in
your results? Why or why not? How? How might
these compare to the strengths and weaknesses of
static analysis tools? You should form and justify an
opinion as to which was more useful for the
project(s) you examined.
The assignment is due 11:59 pm on Wednessday,
March 21.
2018 Nick Sumner
HTML – CSS – Jekyll
2018-03-22, 4*17 PM
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