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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.
40 lines
952 B
Python
Executable File
40 lines
952 B
Python
Executable File
#!/usr/bin/python
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import cPickle
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data = cPickle.load(open("callgraph.pkl"))
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callgraph = data['callgraph']
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closure = data['closure']
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sccs = data['sccs']
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fn_bottle, call_bottle = data['bottlenecks']
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for n_reachable, fn in sorted(list((len(r), fn) for fn, r in closure.iteritems())):
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print "%s can reach %s other functions." %(fn, n_reachable)
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c = [ (len(component), component) for component in sccs ]
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c.sort()
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print "\n================================"
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for n, component in c:
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if n < 2:
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continue
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print "Strongly connected component of size %d:"%n
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print component
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print "\n================================"
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print "====== Number of functions pulled into blob, by function in blob."
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fn_bottle.sort()
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for n, fn in fn_bottle[-30:]:
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print "%3d: %s"%(n, fn)
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print "====== Number of functions pulled into blob, by call in blob."
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call_bottle.sort()
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for n, fn1, _, fn2 in call_bottle[-30:]:
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print "%3d: %s -> %s "%(n, fn2, fn1)
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