Name
Abstract | ||
|---|---|---|
Tremendous amounts of execution data are collected during software execution. These data provide rich information for software runtime behavior comprehension. The unstructured execution data may be too complex, involving multiple interleaved components and so on. Applying existing process discovery techniques results in spaghetti-like models with no clear structure and no valuable information that... |
Year | DOI | Venue |
|---|---|---|
2021 | 10.1109/TASE.2020.3008897 | IEEE Transactions on Automation Science and Engineering |
Keywords | DocType | Volume |
Software systems,Data mining,Petri nets,Data models,Analytical models,Runtime | Journal | 18 |
Issue | ISSN | Citations |
4 | 1545-5955 | 0 |
PageRank | References | Authors |
0.34 | 0 | 1 |