Faster possibility detection by combining two approaches

Stoller, Scott D.; Schneider, Fred B.

doi:10.1007/bfb0022156

Cited by 21 publications

(22 citation statements)

References 11 publications

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“…Further, a predicate is said to be k-local if it depends on variables of at most k processes [SS95]. For example, suppose x i is an integer variable on process p i for each i ∈ [1 .…”

Section: Global Predicatementioning

confidence: 99%

“…However, if the predicate is not regular, then the slice produced will only be an approximate one. To compute the slice for a k-local predicate, which is not regular, we use the technique developed by Stoller and Schneider [SS95]. For a given computation, their technique can be used to transform a k-local predicate into a predicate in k-DNF (disjunctive normal form) with at most m k−1 clauses, where m is the maximum number of events on a process.…”

Section: Computing the Slice For K-local Predicate For Constant Kmentioning

confidence: 99%

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Techniques and applications of computation slicing

Mittal

Garg

2005

Distrib. Comput.

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Writing correct distributed programs is hard. In spite of extensive testing and debugging, software faults persist even in commercial grade software. Many distributed systems, especially those employed in safety-critical environments, should be able to operate properly even in the presence of software faults. Monitoring the execution of a distributed system, and, on detecting a fault, initiating the appropriate corrective action is an important way to tolerate such faults. This gives rise to the predicate detection problem which requires finding a consistent cut of a given computation exists that satisfies a given global predicate, if it exists.Detecting a predicate in a computation is, however, an NP-complete problem in general. In order to ameliorate the associated combinatorial explosion problem, we introduce the notion of computation slice. Formally, the slice of a computation with respect to a predicate is a (sub)computation with the least number of consistent cuts that contains all consistent cuts of the computation satisfying the predicate. Intuitively, slice is a concise representation of those consistent cuts of a computation that satisfy a certain condition. To detect a predicate, rather than searching the state-space of the computation, it is much more efficient to search the statespace of the slice.We prove that the slice exists and is uniquely defined for all predicates. We present efficient algorithms for computing the slice for several useful classes of predicates. We establish that the problem of computing the slice for an arbitrary predicate is NP-complete in general. We develop efficient heuristic algorithms for computing an approximate slice for such predicates for which computing the slice is otherwise provably intractable. Our experimental results demonstrate that slicing can lead to an exponential improvement over existing techniques for predicate detection in terms of time and space.

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“…Further, a predicate is said to be k-local if it depends on variables of at most k processes [SS95]. For example, suppose x i is an integer variable on process p i for each i ∈ [1 .…”

Section: Global Predicatementioning

confidence: 99%

Section: Computing the Slice For K-local Predicate For Constant Kmentioning

confidence: 99%

Techniques and applications of computation slicing

Mittal

Garg

2005

Distrib. Comput.

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“…Lemma 2 which allows queues to be pruned correctly is implemented in the algorithm at P 0 . The algorithm deletes interval X as soon as R(X, Y ) ∈ S(r i,j ) (lines [13][14][15][16][17].…”

Section: Lemma 2 If the Relationship R(x Y ) Between Intervalsmentioning

confidence: 99%

“…4 and Tab. 2 (13) if (R(X, Y ) ∈ S(ri,j)) then (14) newU pdatedQueues = {i} ∪ newU pdatedQueues (15) if (R(Y, X) ∈ S(rj,i)) then (16) newU pdatedQueues = {j} ∪ newU pdatedQueues (17) Delete heads of all Q k where k ∈ newU pdatedQueues (18) updatedQueues = newU pdatedQueues (19) if (all queues are non-empty) then (20) solution found. Heads of queues identify intervals that form the solution.…”

Section: Theorem 4 Algorithm F Ine Rel Has the Following Complexitiementioning

confidence: 99%

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Global Predicate Detection under Fine-Grained Modalities

Chandra

Kshemkalyani

2003

Advances in Computing Science – ASIAN 2003. Progamming Languages and Distributed Computation Programming Languages and Distribu

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Abstract. Predicate detection is an important problem in distributed systems. Based on the temporal interactions of intervals, there exists a rich class of modalities under which global predicates can be specified. For a conjunctive predicate φ, we show how to detect the traditional P ossibly(φ) and Def initely(φ) modalities along with the added information of the exact interaction type between each pair of intervals (one interval at each process). The polynomial time, space, and message complexities of the proposed on-line detection algorithms to detect Possibly and Definitely in terms of the fine-grained interaction types per pair of processes, are the same as those of the earlier on-line algorithms that can detect only whether the Possibly and Definitely modalities hold.

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Computation Slicing: Techniques and Theory

Mittal

Garg

2001

Lecture Notes in Computer Science

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Abstract. We generalize the notion of slice introduced in our earlier paper [6]. A slice of a distributed computation with respect to a global predicate is the smallest computation that contains all consistent cuts of the original computation that satisfy the predicate. We prove that slice exists for all global predicates. We also establish that it is, in general, NP-complete to compute the slice. An optimal algorithm to compute slices for special cases of predicates is provided. Further, we present an efficient algorithm to graft two slices, that is, given two slices, either compute the smallest slice that contains all consistent cuts that are common to both slices or compute the smallest slice that contains all consistent cuts that belong to at least one of the slices. We give application of slicing in general and grafting in particular to global property evaluation of distributed programs. Finally, we show that the results pertaining to consistent global checkpoints [14,18] can be derived as special cases of computation slicing.

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Faster possibility detection by combining two approaches

Cited by 21 publications

References 11 publications

Techniques and applications of computation slicing

Techniques and applications of computation slicing

Global Predicate Detection under Fine-Grained Modalities

Computation Slicing: Techniques and Theory

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