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The latter is done, by comparing their descriptions (or explanations) with our concurrency bug classification (given in Section 3.1).
Based on the severity classification given in Section 3.3, "Blocker" group defined for categorizing the bugs with highest priority, thus we extract the bugs tagged as "Blocker" from our concurrency and non-concurrency bugs' data sets.
Since all unreproducible reported bugs did not have sufficient and detailed discussions thus we could not continue further and map their descriptions (or explanation) with our concurrency bug classification.
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This happens due to our pessimistic concurrency model, in which an operation only completes inside a transaction if it is ensured that it would be committed in the future (contrary to the optimistic concurrency model [24]), and to maintain the Isolation property.
Our proposed concurrency-aware mapping technique can reduce the extra buffer size utilization up to 4.2 times and the execution time degradation up to 2.6 times.
This criterion shows that even if it does not satisfy maximal concurrency, our snap-stabilizing fair algorithm still allows a high level of concurrency.
In contrast, based on our main objective we focus on a more narrow type of bugs by limiting our study scope to concurrency bugs, but provide a broader analysis (comparing concurrency and non-concurrency bugs) taking into consideration several types of these bugs.
Our analysis on unreproducible concurrency bugs illustrates that only 513 of reported bugs (∼4%) were unreproducible.
Our findings shed light on concurrency bugs and could thereby influence future design and development of concurrent software, their debugging and testing, as well as related tools.
In the prediction stage, we do not use concurrency yet in our current prototype.
Instead of proposing yet another completely new real-time concurrency control protocol, our objective is to design an efficient integrated concurrency control method based on existing techniques.
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