Model checking of workflow schemas

Karamanolis, Christos; Giannakopoulou, Dimitra; Magee, Jeff; Wheater, SM

doi:10.1109/edoc.2000.882357

Cited by 42 publications

(28 citation statements)

References 13 publications

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“…Detecting and repairing errors at run time, when the workflow is deployed, is very expensive and time consuming. Therefore, a critical challenge in workflow modeling lies in the design-time verification of workflow models [1,5,6,11,15,19,24,32,33,36].…”

Section: Introductionmentioning

confidence: 99%

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An integer programming based approach for verification and diagnosis of workflows

Eshuis

Kumar

2010

Data & Knowledge Engineering

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Workflow analysis is indispensable to capture modeling errors in workflow designs. While several workflow analysis approaches have been defined previously, these approaches do not give precise feedback, thus making it hard for a designer to pinpoint the exact cause of modeling errors. In this paper we introduce a novel approach for analyzing and diagnosing workflows based on integer programming (IP). Each workflow model is translated into a set of IP constraints. Faulty control flow connectors can be easily detected using the approach by relaxing the corresponding constraints. We have implemented this diagnosis approach in a tool called DiagFlow which reads and diagnoses XPDL models using an existing open source IP solver as a backend. We show that the diagnosis approach is correct and illustrate it with realistic examples. Moreover, the approach is flexible and can be extended to handle a variety of new constraints, as well as to support new workflow patterns. Results of testing on large process models show that DiagFlow outperforms a state of the art tool like Woflan in terms of the solution time.

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Section: Introductionmentioning

confidence: 99%

“…Several authors have recognized this problem, and, starting with Sadiq and Orlowska [33], have defined approaches for analyzing workflow models [1,5,6,11,15,19,24,32,36]. The approaches typically detect two types of errors [33].…”

Section: Introductionmentioning

confidence: 99%

An integer programming based approach for verification and diagnosis of workflows

Eshuis

Kumar

2010

Data & Knowledge Engineering

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“…Even Dynamic DLs [13], which are capable of modeling transition systems with states corresponding to DL knowledge bases, are not flexible enough to express rich constraints on the data level. Some other verification formalisms, of a more suitable, data-oriented flavor, have been proposed for verification of data-driven systems [14], knowledge base programs [15], or workflow schemas [16]. However, the central motivation behind their design is to enable representation of all permissable data-altering operations over a fixed data language, with the aim of studying general properties of programs composed of such operations.…”

Section: Related Workmentioning

confidence: 99%

Formal Verification of Data Provenance Records

Klarman¹,

Schlobach²,

Serafini

2012

The Semantic Web – ISWC 2012

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Abstract. Data provenance is the history of derivation of a data artifact from its original sources. As the real-life provenance records can likely cover thousands of data items and derivation steps, one of the pressing challenges becomes development of formal frameworks for their automated verification.In this paper, we consider data expressed in standard Semantic Web ontology languages, such as OWL, and define a novel verification formalism called provenance specification logic, building on dynamic logic. We validate our proposal by modeling the test queries presented in The First Provenance Challenge, and conclude that the logic core of such queries can be successfully captured in our formalism.

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“…Specifically, model checking has been applied to models for software process [28], requirements [9], architecture [21,22], detailed design [1,25], and implementation [26,12,24].…”

Section: Formal Security Architecturesmentioning

confidence: 99%