def CSourceToInputPair(source: str) -> InputPair:
"""Create a graph and bytecode for the given C source string.
This is a convenience method for generating test inputs. If this method fails,
it is because graph construction or clang is broken.
"""
bytecode = CSourceToBytecode(source)
graph = llvm2graph.BuildProgramGraphNetworkX(bytecode)
return InputPair(graph=graph, bytecode=bytecode)
def Main():
irs = [fs.Read(path) for path in LLVM_IR.iterdir()]
ir_count = len(irs)
with prof.ProfileToStdout(lambda t: (
f"STAGE 1: Construct unlabelled graphs (llvm2graph) "
f"({humanize.Duration(t / ir_count)} / IR)")):
graphs = [llvm2graph.BuildProgramGraphNetworkX(ir) for ir in irs]
encoder = node_encoder.GraphNodeEncoder()
with prof.ProfileToStdout(lambda t: (
f"STAGE 2: Encode graphs (inst2vec) "
f"({humanize.Duration(t / ir_count)} / IR)")):
for graph, ir in zip(graphs, irs):
encoder.EncodeNodes(graph, ir)
features_count = 0
features_lists = []
with prof.ProfileToStdout(lambda t: (
f"STAGE 3: Produce labelled graphs (reachability analysis) "
f"({humanize.Duration(t / features_count)} / graph)")):
for graph in graphs:
analysis = reachability.ReachabilityAnnotator(
programl.NetworkXToProgramGraph(graph))
features_list = analysis.MakeAnnotated(n=10).graphs
features_count += len(features_list)
features_lists.append(features_list)
def iter():
for features_list in features_lists:
for graph in features_list:
yield graph_tuple.GraphTuple.CreateFromNetworkX(graph)
with prof.ProfileToStdout(lambda t: (
f"STAGE 4: Construct graph tuples "
f"({humanize.Duration(t / features_count)} / graph)")):
batcher = graph_batcher.GraphBatcher(iter(), max_node_count=10000)
graph_tuples = list(batcher)
print("=================================")
print(f"Unlabelled graphs count: {ir_count}")
print(f" Labelled graphs count: {features_count}")
print(f" Graph tuples count: {len(graph_tuples)}")
print(
f" Total node count: {sum(gt.node_count for gt in graph_tuples)}"
)
print(
f" Total edge count: {sum(gt.edge_count for gt in graph_tuples)}"
)
def llvm_program_graph_nx(llvm_ir: str) -> nx.MultiDiGraph: """A test fixture which yields a nx program graph constructed from LLVM IR.""" return llvm2graph.BuildProgramGraphNetworkX(llvm_ir)
def test_400531():
"""Graph has no exit blocks."""
llvm2graph.BuildProgramGraphNetworkX(
fs.Read(REGRESSION_TESTS / "400531.ll"))
def test_4180():
"""Graph takes more than 120 seconds to construct."""
llvm2graph.BuildProgramGraphNetworkX(fs.Read(REGRESSION_TESTS / "4180.ll"))
def test_115532():
"""Number of callsites does not correlate with callgraph."""
llvm2graph.BuildProgramGraphNetworkX(
fs.Read(REGRESSION_TESTS / "115532.ll"))
def test_105975():
"""CFG has BBs without predecessors that need to be removed."""
llvm2graph.BuildProgramGraphNetworkX(
fs.Read(REGRESSION_TESTS / "105975.ll"))
def test_53():
"""github.com/ChrisCummins/ProGraML/issues/53"""
llvm2graph.BuildProgramGraphNetworkX(fs.Read(REGRESSION_TESTS / "53.ll"))