留学生辅导 CIS 547 – Introduction to Software Analysis

CIS 547 – Introduction to Software Analysis

CIS 547 – Software Analysis

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Introduction to Software Analysis

The LLVM Framework

Random Input Generation

Delta Debugging

Statistical Debugging

Dataflow Analysis

Pointer Analysis

Constraint-Based Analysis

Dynamic Symbolic Analysis

Introduction to Software Analysis

The LLVM Framework

Software Specifications

Random Testing

Delta Debugging

Statistical Debugging

Dataflow Analysis – Part I

Dataflow Analysis – Part II

Pointer Analysis

Constraint-Based Analysis

Automated Test Generation

Type Systems – Part I

Type Systems – Part II

Dynamic Symbolic Execution

Lab 1: Introduction to Software Analysis

Understanding basic concepts of software analysis and metrics used to estimate the effectiveness of analysis.

The objective of this lab is to use standard analysis tools for static and
dynamic analysis on C programs to discover divide-by-zero errors and interpreting
their results to better understand various trade-offs between the techniques.

Pre-Requisites

Watch the video lectures corresponding to the module on
“Introduction to Software Analysis”.
The lectures introduce various terminology used throughout this lab such as:
static and dynamic analysis, soundness, completeness, precision, F1, and more.

Set up the course development environment by following the instructions outlined
in Course VM and Lab Instructions.
The skeleton code for Lab 1 is located under /lab1.
We will refer to this top-level directory for Lab 1 simply as lab1
when describing file locations for the lab.

Run the following command on your local machine under cis547vm folder to obtain
the latest changes to the lab:

./cis547vm$ git pull

Throughout the labs, we will use CMake, a modern tool for
managing the build process.
If you’re unfamiliar with CMake we recommend reading the
CMake tutorial
(especially pay attention to Step 1 and Step 2 in the tutorial).
Running cmake produces a Makefile that you might be more familiar with.
If you are not familiar with Make, read either the
Makefile tutorial
or Learn Make in Y minutes first,
and then peruse file lab1/Makefile.
Ensure that you are comfortable with using Makefile in this lab.

Inspect the Makefile to see the commands used to run AFL and IKOS.

# Compile the program with AFL
AFL_DONT_OPTIMIZE=1 afl-gcc c_programs/test1.c -o test1
# Run AFL for 30s on test1
timeout 30s afl-fuzz -i afl_input -o afl_output test1
# Run IKOS on test1.c with interval and DBM abstraction respectively
ikos –opt none -a dbz -d interval c_programs/test1.c
ikos –opt none -a dbz -d dbm c_programs/test1.c

Lab Instructions

In this lab, you will run two analysis tools on a suite of C programs,
study the tools’ results, and report your findings.

Run the provided analysis tools, AFL and IKOS, on all C programs
located under the lab1/c_programs directory.
To do so, simply run the following command,
which first runs AFL with a timeout of 30 seconds per program,
and then runs IKOS with interval (int)
and difference bound matrix (dbm) abstractions.

/lab1$ make

On running the above command, you will see the output that looks
something like this:

AFL_DONT_OPTIMIZE=1 afl-gcc c_programs/test1.c -o …
timeout 30s afl-fuzz -i afl_input -o …
Makefile:8: recipe for target ‘results/afl_logs/test1/out.txt’ failed
make: [results/afl_logs/test1/out.txt] Error 124 (ignored)
ikos –opt none -a dbz -d interval c_programs/test1.c …
ikos –opt none -a dbz -d dbm c_programs/test1.c …

Ignore the error reported by Make above; it is normal because
AFL keeps running until it is forcibly terminated by the timeout command.
Feel free to experiment by changing the timeout which is set to 30 seconds.
We do not expect everyone to report the same solutions since
AFL is non-deterministic anyway.

On running the make command, the following files and directories should be generated
under the lab1/results directory:

├── afl_logs/
│ ├── test1/
│ │ ├── out.txt
│ │ ├── afl_output/
│ │ └── test1
│ ├── … // similar for test2
└── ikos_logs/
├── test1_dbm_out.txt
├── test1_int_out.txt
├── … // similar for test2

Determine the ground truth (right vs. wrong) of the C programs with respect to
division-by-zero errors.
In particular, for each division instruction in each program, determine by
inspecting the program whether it can result in a division-by-zero error on
some program input.
Write your answers in file lab1/answers.txt in the “ground truth” column
of the table for each test.

Study the output of AFL and IKOS and determine if they accept or reject each program.
Fill in your answers in file lab1/answers.txt in the corresponding columns of
the table for each test program.

The crashing inputs discovered by AFL are stored in separate files under
directories lab1/results/afl_logs//afl_output/crashes/.
The files have idiosyncratic names of the form
id:000000,sig:08,src:000000,op:arith8,pos:2,val:-8.1
It is the contents of these files that AFL used as the input
to the test program when it encountered a crash.

Using your entries from Steps 2 and 3, calculate the
Precision, Recall, and F1 Score of each column.
Enter them in the corresponding rows in lab1/answers.txt

Answer the questions in answers.txt with the help of the table you filled in.

Submission

Once you are done with the lab, you can create a submission.zip file by using the following command:

lab1$ make submit
submission.zip created successfully.

Then upload the submission.zip file to Gradescope.

The file name encodes various things such as the ID of the crashing input, the crashing signal, the non-crashing seed input from which this crashing input was produced – which in our case is always the file lab1/afl_input/seed.txt, and the operations by which the non-crashing seed input was transformed into this crashing input. ↩

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