Journal ArticleDOI
Discovering models of software processes from event-based data
Jonathan Cook,Alexander L. Wolf +1 more
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TLDR
In this article, the authors describe a Markov method for process discovery, as well as two additional methods that are adopted from other domains and augmented for their purposes, and compare the methods and discuss their application in an industrial case study.Abstract:
Many software process methods and tools presuppose the existence of a formal model of a process. Unfortunately, developing a formal model for an on-going, complex process can be difficult, costly, and error prone. This presents a practical barrier to the adoption of process technologies, which would be lowered by automated assistance in creating formal models. To this end, we have developed a data analysis technique that we term process discovery. Under this technique, data describing process events are first captured from an on-going process and then used to generate a formal model of the behavior of that process. In this article we describe a Markov method that we developed specifically for process discovery, as well as describe two additional methods that we adopted from other domains and augmented for our purposes. The three methods range from the purely algorithmic to the purely statistical. We compare the methods and discuss their application in an industrial case study.read more
Citations
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Journal ArticleDOI
Workflow mining: discovering process models from event logs
TL;DR: A new algorithm is presented to extract a process model from a so-called "workflow log" containing information about the workflow process as it is actually being executed and represent it in terms of a Petri net.
Proceedings ArticleDOI
Dynamically discovering likely program invariants to support program evolution
TL;DR: This paper describes techniques for dynamically discovering invariants, along with an instrumenter and an inference engine that embody these techniques, and reports on the application of the engine to two sets of target programs.
Journal ArticleDOI
Workflow mining: a survey of issues and approaches
W.M.P. van der Aalst,B. F. van Dongen,Joachim Herbst,Laura Maruster,G. Schimm,A.J.M.M. Weijters +5 more
TL;DR: This paper introduces the concept of workflow mining and presents a common format for workflow logs, and discusses the most challenging problems and present some of the workflow mining approaches available today.
Journal ArticleDOI
The Daikon system for dynamic detection of likely invariants
Michael D. Ernst,Jeff H. Perkins,Philip J. Guo,Stephen McCamant,Carlos Pacheco,Matthew S. Tschantz,Chen Xiao +6 more
TL;DR: Daikon is an implementation of dynamic detection of likely invariants; that is, the Daikon invariant detector reports likely program invariants, a property that holds at a certain point or points in a program.
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