mirror of
https://gitlab.torproject.org/tpo/core/tor.git
synced 2024-11-20 10:12:15 +01:00
bb46630513
These scripts are now a little more bulletproof, cache data a little better, and generate more information. Notably, they search for the vectors or edges to cut that would lower the size of the largest SCC.
220 lines
5.0 KiB
Python
Executable File
220 lines
5.0 KiB
Python
Executable File
#!/usr/bin/python
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import re
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import sys
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import copy
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import cPickle
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import os
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class Parser:
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def __init__(self):
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self.calls = {}
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def enter_func(self, name):
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if self.infunc and not self.extern:
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self.calls.setdefault(self.infunc, set()).update( self.calledfns )
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self.calledfns = set()
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self.infunc = name
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self.extern = False
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def parse_callgraph_file(self, inp):
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self.infunc = None
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self.extern = False
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self.calledfns = set()
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for line in inp:
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m = re.match(r"Call graph node for function: '([^']+)'", line)
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if m:
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self.enter_func(m.group(1))
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continue
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m = re.match(r" CS<[^>]+> calls external node", line)
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if m:
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self.extern = True
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m = re.match(r" CS<[^>]+> calls function '([^']+)'", line)
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if m:
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self.calledfns.add(m.group(1))
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self.enter_func(None)
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def extract_callgraph(self):
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c = self.calls
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self.calls = {}
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return c
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def transitive_closure(g):
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passno = 0
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changed = True
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g = copy.deepcopy(g)
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import random
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while changed:
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passno += 1
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changed = False
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keys = g.keys()
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idx = 0
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for k in keys:
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idx += 1
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print "Pass %d/?: %d/%d\r" %(passno, idx, len(keys)),
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sys.stdout.flush()
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newset = g[k].copy()
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for fn in g[k]:
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newset.update(g.get(fn, set()))
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if len(newset) != len(g[k]):
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g[k].update( newset )
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changed = True
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print
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return g
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def strongly_connected_components(g):
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# From https://en.wikipedia.org/wiki/Tarjan%27s_strongly_connected_components_algorithm, done stupidly.
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index_of = {}
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index = [ 0 ]
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lowlink = {}
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S = []
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onStack = set()
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all_sccs = []
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def strongconnect(fn):
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index_of[fn] = index[0]
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lowlink[fn] = index[0]
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index[0] += 1
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S.append(fn)
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onStack.add(fn)
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for w in g.get(fn, []):
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if w not in index_of:
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strongconnect(w)
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lowlink[fn] = min(lowlink[fn], lowlink[w])
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elif w in onStack:
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lowlink[fn] = min(lowlink[fn], index_of[w])
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if lowlink[fn] == index_of[fn]:
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this_scc = []
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all_sccs.append(this_scc)
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while True:
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w = S.pop()
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onStack.remove(w)
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this_scc.append(w)
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if w == fn:
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break
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for v in g.keys():
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if v not in index_of:
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strongconnect(v)
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return all_sccs
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def biggest_component(sccs):
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return max(len(c) for c in sccs)
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def connection_bottlenecks(callgraph):
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callers = {}
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for fn in callgraph:
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for fn2 in callgraph[fn]:
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callers.setdefault(fn2, set()).add(fn)
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components = strongly_connected_components(callgraph)
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components.sort(key=len)
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big_component_fns = components[-1]
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size = len(big_component_fns)
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function_bottlenecks = fn_results = []
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total = len(big_component_fns)
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idx = 0
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for fn in big_component_fns:
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idx += 1
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print "Pass 1/3: %d/%d\r"%(idx, total),
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sys.stdout.flush()
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cg2 = copy.deepcopy(callgraph)
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del cg2[fn]
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fn_results.append( (size - biggest_component(strongly_connected_components(cg2)), fn) )
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print
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bcf_set = set(big_component_fns)
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call_bottlenecks = fn_results = []
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result_set = set()
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total = len(big_component_fns)
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idx = 0
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for fn in big_component_fns:
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fn_callers = callers[fn].intersection(bcf_set)
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idx += 1
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if len(fn_callers) != 1:
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continue
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print "Pass 2/3: %d/%d\r"%(idx, total),
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sys.stdout.flush()
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caller = fn_callers.pop()
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assert len(fn_callers) == 0
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cg2 = copy.deepcopy(callgraph)
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cg2[caller].remove(fn)
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fn_results.append( (size - biggest_component(strongly_connected_components(cg2)), fn, "called by", caller) )
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result_set.add( (caller, fn) )
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print
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total = len(big_component_fns)
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idx = 0
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for fn in big_component_fns:
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fn_calls = callgraph[fn].intersection(bcf_set)
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idx += 1
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if len(fn_calls) != 1:
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continue
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print "Pass 3/3: %d/%d\r"%(idx, total),
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sys.stdout.flush()
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callee = fn_calls.pop()
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if (fn, callee) in result_set:
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continue
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assert len(fn_calls) == 0
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cg2 = copy.deepcopy(callgraph)
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cg2[fn].remove(callee)
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fn_results.append( (size - biggest_component(strongly_connected_components(cg2)), callee, "called by", fn) )
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print
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return (function_bottlenecks, call_bottlenecks)
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if __name__ == '__main__':
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p = Parser()
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for fname in sys.argv[1:]:
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with open(fname, 'r') as f:
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p.parse_callgraph_file(f)
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sys.stdout.flush
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print "Building callgraph"
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callgraph = p.extract_callgraph()
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print "Finding strongly connected components"
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sccs = strongly_connected_components(callgraph)
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print "Finding the transitive closure of the callgraph.."
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closure = transitive_closure(callgraph)
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print "Finding bottlenecks..."
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bottlenecks = connection_bottlenecks(callgraph)
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data = {
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'callgraph' : callgraph,
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'sccs' : sccs,
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'closure' : closure,
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'bottlenecks' : bottlenecks }
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with open('callgraph.pkl', 'w') as f:
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cPickle.dump(data, f)
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