Avoiding state enumeration in dynamic checking of distributed programs
Bibliographic record
Abstract
Distributed programs are particularly vulnerable to software faults. Bugs in these programs are usually very hard to detect without automatic verification. The idea of checking an expected property in a given distributed program run (also referred to as runtime verification) has recently been attracting a great deal of attention for analyzing execution traces to ensure the reliability and dependability of distributed programs. Due to concurrency, the number of global states of a distributed program run tends to grow exponentially with respect to the number of program statements executed. As a result, checking the satisfaction of a property in a given distributed program run can incur significant overhead. This thesis introduces various ideas and exploits them to develop efficient dynamic property checking algorithms. These include the use of atom, introducing and exploiting the notion of serialization and finally proposing a methodology that exploits the concept of atoms and partial order semantics to specify and to check properties of distributed programs. The abstract specification of a distributed program can be mapped to the lower level implementation by labeling the code blocks that belong to the abstract functionalities of the program that are expected to be performed atomically. Each labeled code block is called an atom. Dynamically, an atom includes all the events that result from executing the selected statements from the corresponding code block. An efficient on-the-fly atomicity error detection algorithm has been developed. It is shown that if a run of a distributed program is atomic then the required properties can be checked on a reduced lattice, referred to as the atomic state lattice, which is significantly smaller than the original state lattice. Even with atomization, the number of global states can still grow exponentially in the number of atoms executed. However, when a number of processes has to maintain a property, we expect that each process will be, at some point in time, aware of the events of other processes that may affect the property. Consequently, it is not necessary to check the property in each state. Only synchronized states, where processes have already exchanged the information necessary to maintain the property, need to be considered. These states can be characterized by a synchronization predicate. Serialization of synchronized states is the minimal avenue for a set of processes to exchange the necessary information to maintain a property. Two efficient algorithms to check the satisfaction of a property in a distributed computation in cases where the synchronization predicate is conjunctive or disjunctive have been developed. Finally, a methodology based on the concept of atoms and a partially ordered multi-set (POMSET) model to specify and to check distributed programs properties has been proposed. The POMSET model promotes the separation of two different concerns in specifying and checking properties, namely, the ordering requirements and the computational requirements. A methodology to specify and to efficiently check the two requirements has been introduced.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.005 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".