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Process mining is a family of techniques in the field of process management that
support the analysis of business processes based on event
logs. During process mining, specialized data mining algorithms are
applied to event log data in order to identify trends, patterns and details
contained in event logs recorded by an information system.
https://en.wikipedia.org/wiki/Process_mining#Overview
strace is a diagnostic, debugging and instructional userspace utility for Linux. It is used to monitor and tamper with
interactions between processes and the Linux kernel, which include system calls, signal deliveries, and changes
of process state.
https://en.wikipedia.org/wiki/Strace
Microsoft Windows: Logger can monitor the actions of a user-mode target
application and record all of its API calls.
https://docs.microsoft.com/en-us/windows-hardware/drivers/debugger/logger-and-logviewer
MineIt
takes as input, the log files generated by strace or Logger and
transforms them to be compatible to the process mining paradigm and
tools, i.e. based expressed in terms of
Case Id, Activity, TimeStamp
https://github.com/rchateauneu/mineit
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Applies Process mining techniques in the field of process management and
analysis of business processes from execution logs and traces. Uses machine
learning for processes classification.
The term Process Mining is used in a broader setting to refer not only to
techniques for discovering process models, but also techniques for business
process conformance and performance analysis based on event logs.
It aims at analysing log files and execution traces to extract individual
tasks.
For this, it generates event logs based on case ID, activities, and
timestamps, to make them ready for classical process mining techniques.
This log generation is based on tasks classification with an AI engine. This
separates trivial technical tasks from business-oriented processing steps.