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The 'ignored' changesets are outside the bisection range, but are
changesets that may have an impact on the outcome of the bisection.
For example, in case there's a merge between the good and bad csets,
but the branch-point is out of the bisection range, and the issue
originates from this branch, the branch will not be visited by bisect
and bisect will find that the culprit cset is the merge.
So, the 'ignored' set is equivalent to:
( ( ::bisect(bad) - ::bisect(good) )
| ( ::bisect(good) - ::bisect(bad) ) )
- bisect(range)
- all ancestors of bad csets that are not ancestors of good csets, or
- all ancestors of good csets that are not ancestors of bad csets
- but that are not in the bisection range.
Signed-off-by: "Yann E. MORIN" <yann.morin.1998@anciens.enib.fr>
214 lines
7.6 KiB
Python
214 lines
7.6 KiB
Python
# changelog bisection for mercurial
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#
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# Copyright 2007 Matt Mackall
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# Copyright 2005, 2006 Benoit Boissinot <benoit.boissinot@ens-lyon.org>
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#
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# Inspired by git bisect, extension skeleton taken from mq.py.
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#
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# This software may be used and distributed according to the terms of the
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# GNU General Public License version 2 or any later version.
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import os, error
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from i18n import _
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from node import short, hex
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import util
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def bisect(changelog, state):
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"""find the next node (if any) for testing during a bisect search.
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returns a (nodes, number, good) tuple.
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'nodes' is the final result of the bisect if 'number' is 0.
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Otherwise 'number' indicates the remaining possible candidates for
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the search and 'nodes' contains the next bisect target.
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'good' is True if bisect is searching for a first good changeset, False
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if searching for a first bad one.
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"""
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clparents = changelog.parentrevs
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skip = set([changelog.rev(n) for n in state['skip']])
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def buildancestors(bad, good):
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# only the earliest bad revision matters
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badrev = min([changelog.rev(n) for n in bad])
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goodrevs = [changelog.rev(n) for n in good]
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goodrev = min(goodrevs)
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# build visit array
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ancestors = [None] * (len(changelog) + 1) # an extra for [-1]
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# set nodes descended from goodrevs
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for rev in goodrevs:
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ancestors[rev] = []
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for rev in xrange(goodrev + 1, len(changelog)):
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for prev in clparents(rev):
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if ancestors[prev] == []:
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ancestors[rev] = []
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# clear good revs from array
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for rev in goodrevs:
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ancestors[rev] = None
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for rev in xrange(len(changelog), goodrev, -1):
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if ancestors[rev] is None:
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for prev in clparents(rev):
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ancestors[prev] = None
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if ancestors[badrev] is None:
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return badrev, None
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return badrev, ancestors
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good = False
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badrev, ancestors = buildancestors(state['bad'], state['good'])
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if not ancestors: # looking for bad to good transition?
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good = True
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badrev, ancestors = buildancestors(state['good'], state['bad'])
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bad = changelog.node(badrev)
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if not ancestors: # now we're confused
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if len(state['bad']) == 1 and len(state['good']) == 1:
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raise util.Abort(_("starting revisions are not directly related"))
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raise util.Abort(_("inconsistent state, %s:%s is good and bad")
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% (badrev, short(bad)))
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# build children dict
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children = {}
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visit = [badrev]
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candidates = []
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while visit:
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rev = visit.pop(0)
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if ancestors[rev] == []:
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candidates.append(rev)
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for prev in clparents(rev):
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if prev != -1:
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if prev in children:
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children[prev].append(rev)
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else:
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children[prev] = [rev]
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visit.append(prev)
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candidates.sort()
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# have we narrowed it down to one entry?
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# or have all other possible candidates besides 'bad' have been skipped?
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tot = len(candidates)
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unskipped = [c for c in candidates if (c not in skip) and (c != badrev)]
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if tot == 1 or not unskipped:
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return ([changelog.node(rev) for rev in candidates], 0, good)
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perfect = tot // 2
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# find the best node to test
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best_rev = None
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best_len = -1
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poison = set()
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for rev in candidates:
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if rev in poison:
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# poison children
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poison.update(children.get(rev, []))
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continue
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a = ancestors[rev] or [rev]
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ancestors[rev] = None
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x = len(a) # number of ancestors
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y = tot - x # number of non-ancestors
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value = min(x, y) # how good is this test?
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if value > best_len and rev not in skip:
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best_len = value
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best_rev = rev
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if value == perfect: # found a perfect candidate? quit early
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break
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if y < perfect and rev not in skip: # all downhill from here?
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# poison children
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poison.update(children.get(rev, []))
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continue
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for c in children.get(rev, []):
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if ancestors[c]:
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ancestors[c] = list(set(ancestors[c] + a))
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else:
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ancestors[c] = a + [c]
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assert best_rev is not None
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best_node = changelog.node(best_rev)
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return ([best_node], tot, good)
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def load_state(repo):
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state = {'good': [], 'bad': [], 'skip': []}
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if os.path.exists(repo.join("bisect.state")):
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for l in repo.opener("bisect.state"):
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kind, node = l[:-1].split()
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node = repo.lookup(node)
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if kind not in state:
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raise util.Abort(_("unknown bisect kind %s") % kind)
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state[kind].append(node)
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return state
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def save_state(repo, state):
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f = repo.opener("bisect.state", "w", atomictemp=True)
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wlock = repo.wlock()
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try:
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for kind in state:
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for node in state[kind]:
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f.write("%s %s\n" % (kind, hex(node)))
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f.close()
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finally:
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wlock.release()
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def get(repo, status):
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"""
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Return a list of revision(s) that match the given status:
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- ``good``, ``bad``, ``skip``: as the names imply
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- ``range`` : all csets taking part in the bisection
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- ``pruned`` : csets that are good, bad or skipped
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- ``untested`` : csets whose fate is yet unknown
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- ``ignored`` : csets ignored due to DAG topology
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"""
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state = load_state(repo)
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if status in ('good', 'bad', 'skip'):
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return [repo.changelog.rev(n) for n in state[status]]
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else:
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# In the floowing sets, we do *not* call 'bisect()' with more
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# than one level of recusrsion, because that can be very, very
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# time consuming. Instead, we always develop the expression as
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# much as possible.
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# 'range' is all csets that make the bisection:
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# - have a good ancestor and a bad descendant, or conversely
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# that's because the bisection can go either way
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range = '( bisect(bad)::bisect(good) | bisect(good)::bisect(bad) )'
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# 'pruned' is all csets whose fate is already known:
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# - a good ancestor and a good ascendant, or
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# - a bad ancestor and a bad descendant, or
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# - skipped
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# But in case of irrelevant goods/bads, we also need to
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# include them.
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pg = 'bisect(good)::bisect(good)' # Pruned goods
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pb = 'bisect(bad)::bisect(bad)' # Pruned bads
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ps = 'bisect(skip)' # Pruned skipped
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pruned = '( (%s) | (%s) | (%s) )' % (pg, pb, ps)
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# 'untested' is all cset that are- in 'range', but not in 'pruned'
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untested = '( (%s) - (%s) )' % (range, pruned)
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# 'ignored' is all csets that were not used during the bisection
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# due to DAG topology, but may however have had an impact.
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# Eg., a branch merged between bads and goods, but whose branch-
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# point is out-side of the range.
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iba = '::bisect(bad) - ::bisect(good)' # Ignored bads' ancestors
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iga = '::bisect(good) - ::bisect(bad)' # Ignored goods' ancestors
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ignored = '( ( (%s) | (%s) ) - (%s) )' % (iba, iga, range)
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if status == 'range':
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return [c.rev() for c in repo.set(range)]
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elif status == 'pruned':
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return [c.rev() for c in repo.set(pruned)]
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elif status == 'untested':
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return [c.rev() for c in repo.set(untested)]
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elif status == 'ignored':
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return [c.rev() for c in repo.set(ignored)]
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else:
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raise error.ParseError(_('invalid bisect state'))
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