Transcript AVIO: Detecting Atomicity Violations via Access Interleaving Invariants ASPLOS’06

AVIO: Detecting Atomicity Violations
via Access Interleaving Invariants
Shan Lu, Joseph Tucek, Feng Qin and Yuanyuan Zhou @ UIUC
ASPLOS’06
Presented by Jie Xiao
March 17, 2008
Outline
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Motivation
AVIO solution
AVIO Implementations
Evaluation
Conclusions
Motivation
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Concurrency bugs – difficult to test and
diagnose
Increasing Concurrency bugs – SMT
and CMP encourage multi-threaded
programming
Previous work – not satisfying
Motivation
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Previous work (1) – data races
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Lamport’s Happens-before Algorithm
A data race bug is reported when two
conflicting memory access do not have a
strict happen-before relation.
Lockset Algorithm (Eraser)
Motivation
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Programmers want atomicity, not just
freedom from data races
Race-free does NOT ensure synchronization correctness!
Motivation
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A data race is not always a bug.
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Barriers
Flag synchronization
Previous work can’t differentiate benign
races from true bugs.
Previous work has a high false positive.
Motivation
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Previous work (2) – atomicity violations
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Requires programmers’ annotations
Time-consuming
Correctness ?
SVD: without programmers’ annotations
only detects a limited subset of atomicity
violation bugs.
AVIO solution
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AVIO: an invariant-based approach
Access-Interleaving (AI) Invariant
AVIO solution
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Two steps:
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Collect AI Invariants through training
Detect AI Invariants violation at run time
Analyze interleaving (Table 1)
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8 ways of interleaving
4 of them are violations: case 2, 3, 5, 6.
AVIO solution
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Case 2
AVIO
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Step two – Detection Algorithm
AVIO solution
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Step one – Extraction Algorithm
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Based on Detection Algorithm
In-house testing
Delete fake AI invariants
Run several times with the same input
AVIO Implementations
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AVIO-H
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Using existing invalidation-based cache
coherence protocol
AVIO Implementations
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AVIO-S
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Each thread has an access-table.
More accurate, slower, cheaper
Evaluation
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AVIO detects more atomicity violation bugs.
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AVIO doesn’t rely on synchronization primitives.
AVIO is based on interleaving analysis.
Evaluation
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AVIO has less false positives
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AVIO-S is more accurate than AVIO-H, because
AVIO-S can choose flexible granularity.
Evaluation
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AVIO has small overhead
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AVIO-S for in-house bug detection and
postmortem bug diagnosis.
AVIO-H for bug detection during production runs.
Conclusions
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AVIO is effective in detecting atomicity violations.
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Detect more atomicity violations than previous
approaches
Low false positive
The first approach using hardware support to detect
atomicity violation
AVIO-H has a low overhead
Doesn’t rely on programmers’ annotations