I am writing a program that tries to compare two methods. I would like to generate Control flow graphs (CFG) for all matched methods and use either a topological sort to compare the two graphs.
Note: Secret to drawing a CFG is to treat every statement independent to the program, draw it and then link it's entry and exit to the rest of the graph. Statement 1, 2, and 3 are non conditional so I created three blocks linking them together. Statement 4 is a conditional statement.
A Control Flow Graph (CFG) is the graphical representation of control flow or computation during the execution of programs or applications. Control flow graphs are mostly used in static analysis as well as compiler applications, as they can accurately represent the flow inside of a program unit.
There's a Python package called staticfg
which does exactly the this -- generation of control flow graphs from a piece of Python code.
For instance, putting the first quick sort Python snippet from Rosseta Code in qsort.py
, the following code generates its control flow graph.
from staticfg import CFGBuilder
cfg = CFGBuilder().build_from_file('quick sort', 'qsort.py')
cfg.build_visual('qsort', 'png')
Note that it doesn't seem to understand more advanced control flow like comprehensions.
RPython, the translation toolchain behind PyPy, offers a way of grabbing the flow graph (in the pypy/rpython/flowspace
directory of the PyPy project) for type inference.
This works quite well in most cases but generators are not supported. The result will be in SSA form, which might be good or bad, depending on what you want.
I found py2cfg has a better representation of Control Flow Graph (CFG) than one from staticfg.
Let's take this function in Python:
def fib():
a, b = 0, 1
while True:
yield a
a, b = b, a + b
fib_gen = fib()
for _ in range(10):
next(fib_gen)
Image from StaticCFG:
Image from PY2CFG:
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