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test_cdg.py
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test_cdg.py
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import sys
import os
import networkx
import nose.tools
import angr
from angr.analyses.cdg import TemporaryNode
test_location = str(os.path.join(os.path.dirname(os.path.realpath(__file__)), "..", "..", "binaries", "tests"))
def test_graph_0():
# This graph comes from Fig.1 of paper An Efficient Method of Computing Static Single Assignment Form by Ron Cytron,
# etc.
# Create a project with a random binary - it will not be used anyways
p = angr.Project(test_location + "/x86_64/datadep_test",
load_options={'auto_load_libs': False},
use_sim_procedures=True)
# Create the CDG analysis
cfg = p.analyses.CFGAccurate(no_construct=True)
# Create our mock control flow graph
g = networkx.DiGraph()
edges = [
('Entry', 1),
(1, 2),
(2, 3),
(2, 7),
(3, 4),
(3, 5),
(4, 6),
(5, 6),
(6, 8),
(7, 8),
(8, 9),
(9, 10),
(9, 11),
(11, 9),
(10, 11),
(11, 12),
(12, 2),
(12, 'Exit'),
('Entry', 'Exit')
]
for src, dst in edges:
# Create a TemporaryNode for each node
n1 = TemporaryNode(src)
n2 = TemporaryNode(dst)
g.add_edge(n1, n2)
# Manually set the CFG
cfg._graph = g
cfg._nodes = { }
cfg._edge_map = { }
cfg._loop_back_edges = [ ]
cfg._overlapped_loop_headers = [ ]
# Call _construct()
cdg = p.analyses.CDG(cfg=cfg, no_construct=True)
cdg._entry = TemporaryNode('Entry')
cdg._construct()
standard_result = {
'Entry': { 1, 2, 8, 9, 11, 12 },
1: set(),
2: { 3, 6, 7 },
3: { 4, 5 },
4: set(),
5: set(),
6: set(),
7: set(),
8: set(),
9: { 10 },
10: set(),
11: { 9, 11 },
12: { 2, 8, 9, 11, 12 }
}
for node, cd_nodes in standard_result.iteritems():
# Each node in set `cd_nodes` is control dependent on `node`
for n in cd_nodes:
nose.tools.assert_true(cdg.graph.has_edge(TemporaryNode(node), TemporaryNode(n)))
nose.tools.assert_equal(len(cdg.graph.out_edges(TemporaryNode(node))), len(cd_nodes))
def test_dominance_frontiers():
from angr.utils.graph import compute_dominance_frontier
# This graph comes from Fig.1 of paper An Efficient Method of Computing Static Single Assignment Form by Ron Cytron,
# etc.
# Create our mock control flow graph
g = networkx.DiGraph()
g.add_edge('Entry', 1)
g.add_edge(1, 2)
g.add_edge(2, 3)
g.add_edge(2, 7)
g.add_edge(3, 4)
g.add_edge(3, 5)
g.add_edge(4, 6)
g.add_edge(5, 6)
g.add_edge(6, 8)
g.add_edge(7, 8)
g.add_edge(8, 9)
g.add_edge(9, 10)
g.add_edge(9, 11)
g.add_edge(11, 9)
g.add_edge(10, 11)
g.add_edge(11, 12)
g.add_edge(12, 2)
g.add_edge(12, 'Exit')
g.add_edge('Entry', 'Exit')
# Create the mock post-dom graph
postdom = networkx.DiGraph()
postdom.add_edge('Entry', 1)
postdom.add_edge(1, 2)
postdom.add_edge(2, 3)
postdom.add_edge(3, 4)
postdom.add_edge(3, 5)
postdom.add_edge(3, 6)
postdom.add_edge(2, 7)
postdom.add_edge(2, 8)
postdom.add_edge(8, 9)
postdom.add_edge(9, 10)
postdom.add_edge(9, 11)
postdom.add_edge(11, 12)
postdom.add_edge('Entry', 'Exit')
# Call df_construct()
df = compute_dominance_frontier(g, postdom)
standard_df = {
1: { 'Exit' },
2: { 'Exit', 2 },
3: { 8 },
4: { 6 },
5: { 6 },
6: { 8 },
7: { 8 },
8: { 'Exit', 2 },
9: { 'Exit', 2, 9 },
10: { 11 },
11: { 'Exit', 2, 9 },
12: { 'Exit', 2 },
'Entry': set(),
'Exit': set()
}
nose.tools.assert_equal(df, standard_df)
def run_all():
g = globals()
for k, v in g.iteritems():
if k.startswith('test_') and hasattr(v, '__call__'):
v()
if __name__ == "__main__":
if len(sys.argv) > 1:
globals()['test_' + sys.argv[1]]()
else:
run_all()