Verification of communicating data-driven web services

Deutsch, Alin; Sui, Liying; Vianu, Victor; Zhou, Dayou

doi:10.1145/1142351.1142364

Cited by 68 publications

(96 citation statements)

References 31 publications

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“…The modeling (and analysis) of the data manipulated by processes was studied in e.g. [12,20,21,22,26,28], but the processes studied there were not probabilistic; combining these two lines of research into a unified framework for probabilistic processes along with the data they manipulate. Additionally, we have discussed selection and projection queries, the latter with two particular aggregation functions (sum and max); in [1] the authors study aggregate queries for "monoid" aggregate functions (including sum, count, min, max) for Probabilistic XML.…”

Section: Resultsmentioning

confidence: 99%

On models and query languages for probabilistic processes

Deutch

Milo

2010

SIGMOD Rec.

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Probabilistic processes appear naturally in various contexts, with applications to Business Processes, XML data management and more. Many models for specifying and querying such processes exist in the literature; a main goal of research in this area is to design models that are expressive enough to capture real-life processes and analysis tasks, but at the same time allow for efficient query evaluation. We depict the model established in [13,16,17,18], and claim that it achieves a good balance between expressivity and query evaluation complexity. We compare and contrast the model with other common models for probabilistic processes, highlighting the different choices made in models design and their effect on expressivity and incurred complexity.

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Section: Resultsmentioning

confidence: 99%

On models and query languages for probabilistic processes

Deutch

Milo

2010

SIGMOD Rec.

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“…The business artifact model [26] has pioneered datadriven workflows, but formal studies have focused on the single-user scenario. Compositions of data-driven web services are studied in [15], focusing on automatic verification. Active XML [3] provides distributed datadriven workflows manipulating XML data.…”

Section: Related Workmentioning

confidence: 99%

Explanations and Transparency in Collaborative Workflows

Abiteboul

Bourhis

Vianu

2018

Proceedings of the 37th ACM SIGMOD-SIGACT-SIGAI Symposium on Principles of Database Systems

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We pursue an investigation of data-driven collaborative workflows. In the model, peers can access and update local data, causing side-e↵ects on other peers' data. In this paper, we study means of explaining to a peer her local view of a global run, both at runtime and statically. We consider the notion of "scenario for a given peer" that is a subrun observationally equivalent to the original run for that peer. Because such a scenario can sometimes di↵er significantly from what happens in the actual run, thus providing a misleading explanation, we introduce and study a faithfulness requirement that ensures closer adherence to the global run. We show that there is a unique minimal faithful scenario, that explains what is happening in the global run by extracting only the portion relevant to the peer.With regard to static explanations, we consider the problem of synthesizing, for each peer, a "view program" whose runs generate exactly the peer's observations of the global runs. Assuming some conditions desirable in their own right, namely transparency and boundedness, we show that such a view program exists and can be synthesized. As an added benefit, the view program rules provide provenance information for the updates observed by the peer.

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“…Analysis of non-weighted processes in the context of verification (rather than top-k analysis) was discussed in e.g. [9].…”

Section: Conclusion and Related Workmentioning

confidence: 99%

Optimal top-k query evaluation for weighted business processes

et al. 2010

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A Business Process (BP for short) consists of a set of activities that achieve some business goal when combined in a flow. Among all the (maybe infinitely many) possible execution flows of a BP, analysts are often interested in identifying flows that are "most important", according to some weight metric. This paper studies the following problem: given a specification of such a BP, a weighting function over BP execution flows, a query, and a number k, identify the k flows with the highest weight among those satisfying the query. We provide here, for the first time, a provably optimal algorithm for identifying the top-k weighted flows of a given BP, and use it for efficient top-k query evaluation.

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Verification of communicating data-driven web services

Cited by 68 publications

References 31 publications

On models and query languages for probabilistic processes

On models and query languages for probabilistic processes

Explanations and Transparency in Collaborative Workflows

Optimal top-k query evaluation for weighted business processes

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