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  1. Dec 04, 2018
  2. Nov 18, 2018
  3. Nov 10, 2018
  4. Nov 18, 2018
    • Yuya Nishihara's avatar
      loggingutil: add basic logger backends · 96be0eca
      Yuya Nishihara authored
      These classes will be used in command server. They are similar to
      the blackboxlogger, but it can't be factored out since the blackbox is so
      tightly coupled with a repo object.
      96be0eca
  5. Dec 04, 2018
  6. Nov 20, 2018
  7. Dec 04, 2018
  8. Oct 28, 2018
    • Yuya Nishihara's avatar
      rust: fix possible out-of-bounds read through index_get_parents() · 884321cd
      Yuya Nishihara authored
      index_get_parents() is an internal function, which doesn't check if the
      specified rev is valid. If rustlazyancestors() were instantiated with an
      invalid stoprev, it would access to invalid memory region.
      
      This is NOT a security fix as there's no Python code triggering the bug,
      but included in this series to not give a notion about the memory issue
      fixed by the previous patch.
      884321cd
  9. Nov 01, 2018
  10. Nov 29, 2018
    • Georges Racinet's avatar
      rust: peek_mut optim for lazy ancestors · e13ab4ac
      Georges Racinet authored
      This is one of the two optimizations that are also
      present in the Python code: replacing pairs of pop/push
      on the BinaryHeap by single updates, hence having it
      under the hood maintain its consistency (sift) only once.
      
      On Mozilla central, the measured gain (see details below)
      is around 7%.
      
      Creating the PeekMut object by calling peek_mut() right away
      instead of peek() first is less efficient (gain is only 4%, stats
      not included).
      Our interpretation is that its creation has a cost which is vasted
      in the cases where it ends by droping the value (Peekmut::pop()
      just does self.heap.pop() anyway). On the other hand, the immutable
      peek() is very fast: it's just taking a reference in the
      underlying vector.
      
      The Python version still has another optimization:
      if parent(current) == current-1, then the heap doesn't need
      to maintain its consistency, since we already know that
      it's bigger than all the others in the heap.
      Rust's BinaryHeap doesn't allow us to mutate its biggest
      element with no housekeeping, but we tried it anyway, with a
      copy of the BinaryHeap implementation with a dedicaded added
      method: it's not worth the technical debt in our opinion
      (we measured only a further 1.6% improvement).
      One possible explanation would be that the sift is really fast
      anyway in that case, whereas it's not in the case of Python,
      because it's at least partly done in slow Python code.
      Still it's possible that replacing BinaryHeap by something more
      dedicated to discrete ordered types could be faster.
      
      Measurements on mozilla-central:
      
      Three runs of 'hg perfancestors' on the parent changeset:
      
      Moyenne des médianes: 0.100587
      ! wall 0.100062 comb 0.100000 user 0.100000 sys 0.000000 (best of 98)
      ! wall 0.135804 comb 0.130000 user 0.130000 sys 0.000000 (max of 98)
      ! wall 0.102864 comb 0.102755 user 0.099286 sys 0.003469 (avg of 98)
      ! wall 0.101486 comb 0.110000 user 0.110000 sys 0.000000 (median of 98)
      
      ! wall 0.096804 comb 0.090000 user 0.090000 sys 0.000000 (best of 100)
      ! wall 0.132235 comb 0.130000 user 0.120000 sys 0.010000 (max of 100)
      ! wall 0.100258 comb 0.100300 user 0.096000 sys 0.004300 (avg of 100)
      ! wall 0.098384 comb 0.100000 user 0.100000 sys 0.000000 (median of 100)
      
      ! wall 0.099925 comb 0.100000 user 0.100000 sys 0.000000 (best of 98)
      ! wall 0.133518 comb 0.140000 user 0.130000 sys 0.010000 (max of 98)
      ! wall 0.102381 comb 0.102449 user 0.098265 sys 0.004184 (avg of 98)
      ! wall 0.101891 comb 0.090000 user 0.090000 sys 0.000000 (median of 98)
      
      Mean of the medians: 0.100587
      
      On the present changeset:
      
      ! wall 0.091344 comb 0.090000 user 0.090000 sys 0.000000 (best of 100)
      ! wall 0.122728 comb 0.120000 user 0.110000 sys 0.010000 (max of 100)
      ! wall 0.093268 comb 0.093300 user 0.089300 sys 0.004000 (avg of 100)
      ! wall 0.092567 comb 0.100000 user 0.090000 sys 0.010000 (median of 100)
      
      ! wall 0.093294 comb 0.080000 user 0.080000 sys 0.000000 (best of 100)
      ! wall 0.144887 comb 0.150000 user 0.140000 sys 0.010000 (max of 100)
      ! wall 0.097708 comb 0.097700 user 0.093400 sys 0.004300 (avg of 100)
      ! wall 0.094980 comb 0.100000 user 0.090000 sys 0.010000 (median of 100)
      
      ! wall 0.091262 comb 0.090000 user 0.080000 sys 0.010000 (best of 100)
      ! wall 0.123772 comb 0.130000 user 0.120000 sys 0.010000 (max of 100)
      ! wall 0.093188 comb 0.093200 user 0.089300 sys 0.003900 (avg of 100)
      ! wall 0.092364 comb 0.100000 user 0.090000 sys 0.010000 (median of 100)
      
      Mean of the medians is 0.0933
      
      Differential Revision: https://phab.mercurial-scm.org/D5358
      e13ab4ac
  11. Dec 03, 2018
  12. Nov 13, 2018
  13. Dec 04, 2018
  14. Dec 03, 2018
  15. Nov 28, 2018
  16. Dec 03, 2018
  17. Dec 04, 2018
  18. Nov 18, 2018
  19. Nov 17, 2018
  20. Nov 20, 2018
  21. Nov 15, 2018
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