Process mining is a growing and promising study area focused on understanding processes
and to help capture the more significant findings during real execution rather than, those …

Over the last decade, process mining emerged as a new research field that focuses on the
analysis of processes using event data. Classical data mining techniques such as …

In recent years, data science emerged as a new and important discipline. It can be viewed
as an amalgamation of classical disciplines like statistics, data mining, databases, and …

We address the problem of synthesizing code completions for programs using APIs. Given a
program with holes, we synthesize completions for holes with the most likely sequences of …

Process mining Page 1 76 CoMMuniCAtionS oF thE ACM | AuguST 2012 | vOL. 55 | NO. 8
contributed articles Doi:10.1145/2240236.2240257 Using real event data to X-ray business …

Contemporary workflow management systems are driven by explicit process models, ie, a
completely specified workflow design is required in order to enact a given workflow process …

Business Process Management (BPM) research resulted in a plethora of methods,
techniques, and tools to support the design, enactment, management, and analysis of …

Process Mining is a technique for extracting process models from execution logs. This is
particularly useful in situations where people have an idealized view of reality. Real-life …

Under the umbrella of buzzwords such as “Business Activity Monitoring”(BAM) and
“Business Process Intelligence”(BPI) both academic (eg, EMiT, Little Thumb, InWoLvE …

Daikon is an implementation of dynamic detection of likely invariants; that is, the Daikon
invariant detector reports likely program invariants. An invariant is a property that holds at a …