Automating process discovery through event-data analysis (1995) [52 citations — 4 self]
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@INPROCEEDINGS{Cook95automatingprocess,author = {Jonathan E. Cook and Er L. Wolf},
title = {Automating process discovery through event-data analysis},
booktitle = {Association for Computer Machinery},
year = {1995},
pages = {73--82},
publisher = {ACM Press}
}
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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. The barrier would be lowered by automating the creation of formal models. We are currently exploring techniques that can use basic event data captured from an on-going process to generate a formal model of process behavior. We term this kind of data analysis process discovery. This paper describes and illustrates three methods with which we have been experimenting: algorithmic grammar inference, Markov models, and neural networks.
Citations
| 256 | Inductive inference: theory and methods – Angluin, Smith - 1983 |
| 106 | Software process model evolution in the SPADE environment – Bandinelli, Fugetta, et al. - 1993 |
| 72 | Automated analysis of concurrent systems with the constrained expression toolset – Avrunin, Buy, et al. - 1991 |
| 32 | Scaling up rule-based development environments – Barghouti, Kaiser - 1991 |
