The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.
Discovering models of software processes from event-based data
Open accessAbstract
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.
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Valiant, L. G. (1984) · Communications of the ACM · doi:10.1145/1968.1972 · Cited by 3,279
The KDD process for extracting useful knowledge from volumes of data
Fayyad, U., Piatetsky-Shapiro, G., & Smyth, P. (1996) · Communications of the ACM · doi:10.1145/240455.240464 · Cited by 1,934
Cited by
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Ernst, M. D., Cockrell, J., Griswold, W. G., & Notkin, D. (2001) · IEEE Transactions on Software Engineering · doi:10.1109/32.908957 · Cited by 1,050
Code completion with statistical language models
Raychev, V., Vechev, M., & Yahav, E. (2014) · Proceedings of the 35th ACM SIGPLAN Conference on Programming Language Design and Implementation · doi:10.1145/2594291.2594321 · Cited by 555
Genetic process mining: an experimental evaluation
de Medeiros, A. K. A., Weijters, A. J. M. M., & van der Aalst, W. M. P. (2007) · Data Mining and Knowledge Discovery · doi:10.1007/s10618-006-0061-7 · Cited by 490
Inferring extended finite state machine models from software executions
Walkinshaw, N., Taylor, R., & Derrick, J. (2016) · Empirical Software Engineering · doi:10.1007/s10664-015-9367-7 · Cited by 127
Survey on Models and Techniques for Root-Cause Analysis
Solé, M., Muntés-Mulero, V., Rana, A. I., & Estrada, G. (2017) · arXiv · doi:10.48550/arxiv.1701.08546 · Cited by 74
Metadata
- Authors
- Cook, J. E., & Wolf, A. L.
- Venue
- ACM Transactions on Software Engineering and Methodology
- Published
- 1998-07
- Volume
- 7
- Issue
- 3
- Pages
- 215-249
- ISSN
- 1049-331X (ISSN-L)
- 1557-7392
- OpenAlex
- W2004865374
- Cited by
- 870
- References
- 2
- FWCI
- 27.54
- Type
- journal article
- Language
- en
- Open access
- bronze
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- Cook, J. E., & Wolf, A. L. (1998). Discovering models of software processes from event-based data. ACM Transactions on Software Engineering and Methodology. https://doi.org/10.1145/287000.287001
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
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