view tests/test-ancestor.py @ 23702:c48924787eaa

filectx.parents: enforce changeid of parent to be in own changectx ancestors Because of the way filenodes are computed, you can have multiple changesets "introducing" the same file revision. For example, in the changeset graph below, changeset 2 and 3 both change a file -to- and -from- the same content. o 3: content = new | | o 2: content = new |/ o 1: content = old In such cases, the file revision is create once, when 2 is added, and just reused for 3. So the file change in '3' (from "old" to "new)" has no linkrev pointing to it). We'll call this situation "linkrev-shadowing". As the linkrev is used for optimization purposes when walking a file history, the linkrev-shadowing results in an unexpected jump to another branch during such a walk.. This leads to multiple bugs with log, annotate and rename detection. One element to fix such bugs is to ensure that walking the file history sticks on the same topology as the changeset's history. For this purpose, we extend the logic in 'basefilectx.parents' so that it always defines the proper changeset to associate the parent file revision with. This "proper" changeset has to be an ancestor of the changeset associated with the child file revision. This logic is performed in the '_adjustlinkrev' function. This function is given the starting changeset and all the information regarding the parent file revision. If the linkrev for the file revision is an ancestor of the starting changeset, the linkrev is valid and will be used. If it is not, we detected a topological jump caused by linkrev shadowing, we are going to walk the ancestors of the starting changeset until we find one setting the file to the revision we are trying to create. The performance impact appears acceptable: - We are walking the changelog once for each filelog traversal (as there should be no overlap between searches), - changelog traversal itself is fairly cheap, compared to what is likely going to be perform on the result on the filelog traversal, - We only touch the manifest for ancestors touching the file, And such changesets are likely to be the one introducing the file. (except in pathological cases involving merge), - We use manifest diff instead of full manifest unpacking to check manifest content, so it does not involve applying multiple diffs in most case. - linkrev shadowing is not the common case. Tests for fixed issues in log, annotate and rename detection have been added. But this changeset does not solve all problems. It fixes -ancestry- computation, but if the linkrev-shadowed changesets is the starting one, we'll still get things wrong. We'll have to fix the bootstrapping of such operations in a later changeset. Also, the usage of `hg log FILE` without --follow still has issues with linkrev pointing to hidden changesets, because it relies on the `filelog` revset which implement its own traversal logic that is still to be fixed. Thanks goes to: - Matt Mackall: for nudging me in the right direction - Julien Cristau and RĂ©mi Cardona: for keep telling me linkrev bug were an evolution show stopper for 3 years. - Durham Goode: for finding a new linkrev issue every few weeks - Mads Kiilerich: for that last rename bug who raise this topic over my anoyance limit.
author Pierre-Yves David <pierre-yves.david@fb.com>
date Tue, 23 Dec 2014 15:30:38 -0800
parents f710644e1ce9
children 4056fdf71aff
line wrap: on
line source

from mercurial import ancestor, commands, hg, ui, util
from mercurial.node import nullrev
import binascii, getopt, math, os, random, sys, time

def buildgraph(rng, nodes=100, rootprob=0.05, mergeprob=0.2, prevprob=0.7):
    '''nodes: total number of nodes in the graph
    rootprob: probability that a new node (not 0) will be a root
    mergeprob: probability that, excluding a root a node will be a merge
    prevprob: probability that p1 will be the previous node

    return value is a graph represented as an adjacency list.
    '''
    graph = [None] * nodes
    for i in xrange(nodes):
        if i == 0 or rng.random() < rootprob:
            graph[i] = [nullrev]
        elif i == 1:
            graph[i] = [0]
        elif rng.random() < mergeprob:
            if i == 2 or rng.random() < prevprob:
                # p1 is prev
                p1 = i - 1
            else:
                p1 = rng.randrange(i - 1)
            p2 = rng.choice(range(0, p1) + range(p1 + 1, i))
            graph[i] = [p1, p2]
        elif rng.random() < prevprob:
            graph[i] = [i - 1]
        else:
            graph[i] = [rng.randrange(i - 1)]

    return graph

def buildancestorsets(graph):
    ancs = [None] * len(graph)
    for i in xrange(len(graph)):
        ancs[i] = set([i])
        if graph[i] == [nullrev]:
            continue
        for p in graph[i]:
            ancs[i].update(ancs[p])
    return ancs

class naiveincrementalmissingancestors(object):
    def __init__(self, ancs, bases):
        self.ancs = ancs
        self.bases = set(bases)
    def addbases(self, newbases):
        self.bases.update(newbases)
    def removeancestorsfrom(self, revs):
        for base in self.bases:
            if base != nullrev:
                revs.difference_update(self.ancs[base])
        revs.discard(nullrev)
    def missingancestors(self, revs):
        res = set()
        for rev in revs:
            if rev != nullrev:
                res.update(self.ancs[rev])
        for base in self.bases:
            if base != nullrev:
                res.difference_update(self.ancs[base])
        return sorted(res)

def test_missingancestors(seed, rng):
    # empirically observed to take around 1 second
    graphcount = 100
    testcount = 10
    inccount = 10
    nerrs = [0]
    # the default mu and sigma give us a nice distribution of mostly
    # single-digit counts (including 0) with some higher ones
    def lognormrandom(mu, sigma):
        return int(math.floor(rng.lognormvariate(mu, sigma)))

    def samplerevs(nodes, mu=1.1, sigma=0.8):
        count = min(lognormrandom(mu, sigma), len(nodes))
        return rng.sample(nodes, count)

    def err(seed, graph, bases, seq, output, expected):
        if nerrs[0] == 0:
            print >> sys.stderr, 'seed:', hex(seed)[:-1]
        if gerrs[0] == 0:
            print >> sys.stderr, 'graph:', graph
        print >> sys.stderr, '* bases:', bases
        print >> sys.stderr, '* seq: ', seq
        print >> sys.stderr, '*  output:  ', output
        print >> sys.stderr, '*  expected:', expected
        nerrs[0] += 1
        gerrs[0] += 1

    for g in xrange(graphcount):
        graph = buildgraph(rng)
        ancs = buildancestorsets(graph)
        gerrs = [0]
        for _ in xrange(testcount):
            # start from nullrev to include it as a possibility
            graphnodes = range(nullrev, len(graph))
            bases = samplerevs(graphnodes)

            # fast algorithm
            inc = ancestor.incrementalmissingancestors(graph.__getitem__, bases)
            # reference slow algorithm
            naiveinc = naiveincrementalmissingancestors(ancs, bases)
            seq = []
            revs = []
            for _ in xrange(inccount):
                if rng.random() < 0.2:
                    newbases = samplerevs(graphnodes)
                    seq.append(('addbases', newbases))
                    inc.addbases(newbases)
                    naiveinc.addbases(newbases)
                if rng.random() < 0.4:
                    # larger set so that there are more revs to remove from
                    revs = samplerevs(graphnodes, mu=1.5)
                    seq.append(('removeancestorsfrom', revs))
                    hrevs = set(revs)
                    rrevs = set(revs)
                    inc.removeancestorsfrom(hrevs)
                    naiveinc.removeancestorsfrom(rrevs)
                    if hrevs != rrevs:
                        err(seed, graph, bases, seq, sorted(hrevs),
                            sorted(rrevs))
                else:
                    revs = samplerevs(graphnodes)
                    seq.append(('missingancestors', revs))
                    h = inc.missingancestors(revs)
                    r = naiveinc.missingancestors(revs)
                    if h != r:
                        err(seed, graph, bases, seq, h, r)

# graph is a dict of child->parent adjacency lists for this graph:
# o  13
# |
# | o  12
# | |
# | | o    11
# | | |\
# | | | | o  10
# | | | | |
# | o---+ |  9
# | | | | |
# o | | | |  8
#  / / / /
# | | o |  7
# | | | |
# o---+ |  6
#  / / /
# | | o  5
# | |/
# | o  4
# | |
# o |  3
# | |
# | o  2
# |/
# o  1
# |
# o  0

graph = {0: [-1], 1: [0], 2: [1], 3: [1], 4: [2], 5: [4], 6: [4],
         7: [4], 8: [-1], 9: [6, 7], 10: [5], 11: [3, 7], 12: [9],
         13: [8]}

def genlazyancestors(revs, stoprev=0, inclusive=False):
    print ("%% lazy ancestor set for %s, stoprev = %s, inclusive = %s" %
           (revs, stoprev, inclusive))
    return ancestor.lazyancestors(graph.get, revs, stoprev=stoprev,
                                  inclusive=inclusive)

def printlazyancestors(s, l):
    print 'membership: %r' % [n for n in l if n in s]
    print 'iteration:  %r' % list(s)

def test_lazyancestors():
    # Empty revs
    s = genlazyancestors([])
    printlazyancestors(s, [3, 0, -1])

    # Standard example
    s = genlazyancestors([11, 13])
    printlazyancestors(s, [11, 13, 7, 9, 8, 3, 6, 4, 1, -1, 0])

    # Standard with ancestry in the initial set (1 is ancestor of 3)
    s = genlazyancestors([1, 3])
    printlazyancestors(s, [1, -1, 0])

    # Including revs
    s = genlazyancestors([11, 13], inclusive=True)
    printlazyancestors(s, [11, 13, 7, 9, 8, 3, 6, 4, 1, -1, 0])

    # Test with stoprev
    s = genlazyancestors([11, 13], stoprev=6)
    printlazyancestors(s, [11, 13, 7, 9, 8, 3, 6, 4, 1, -1, 0])
    s = genlazyancestors([11, 13], stoprev=6, inclusive=True)
    printlazyancestors(s, [11, 13, 7, 9, 8, 3, 6, 4, 1, -1, 0])


# The C gca algorithm requires a real repo. These are textual descriptions of
# DAGs that have been known to be problematic.
dagtests = [
    '+2*2*2/*3/2',
    '+3*3/*2*2/*4*4/*4/2*4/2*2',
]
def test_gca():
    u = ui.ui()
    for i, dag in enumerate(dagtests):
        repo = hg.repository(u, 'gca%d' % i, create=1)
        cl = repo.changelog
        if not util.safehasattr(cl.index, 'ancestors'):
            # C version not available
            return

        commands.debugbuilddag(u, repo, dag)
        # Compare the results of the Python and C versions. This does not
        # include choosing a winner when more than one gca exists -- we make
        # sure both return exactly the same set of gcas.
        for a in cl:
            for b in cl:
                cgcas = sorted(cl.index.ancestors(a, b))
                pygcas = sorted(ancestor.ancestors(cl.parentrevs, a, b))
                if cgcas != pygcas:
                    print "test_gca: for dag %s, gcas for %d, %d:" % (dag, a, b)
                    print "  C returned:      %s" % cgcas
                    print "  Python returned: %s" % pygcas

def main():
    seed = None
    opts, args = getopt.getopt(sys.argv[1:], 's:', ['seed='])
    for o, a in opts:
        if o in ('-s', '--seed'):
            seed = long(a, base=0) # accepts base 10 or 16 strings

    if seed is None:
        try:
            seed = long(binascii.hexlify(os.urandom(16)), 16)
        except AttributeError:
            seed = long(time.time() * 1000)

    rng = random.Random(seed)
    test_missingancestors(seed, rng)
    test_lazyancestors()
    test_gca()

if __name__ == '__main__':
    main()