|Title||Periodic Task Mining in Embedded System Traces|
|Publication Type||Conference Paper|
|Year of Publication||2017|
|Authors||Iegorov, O., R. Torres, and S. Fischmeister|
|Conference Name||IEEE Real-Time and Embedded Technology and Applications Symposium (RTAS)|
|Conference Location||Pittsburgh, USA|
Modern systems are growing in complexity beyond deep comprehension of developers. Increasing difficulties of keeping software projects on schedule and increasing recall rates are symptoms of this development. Consequently, developers need new methods and tools to build embedded systems, such as tools that dynamically analyze systems and recover comprehensible specifications of particular aspects. In this paper, we address the problem of discovering temporal behavior of real-time systems by mining periodic task sets and their temporal characteristics from system execution traces. We leverage the periodic nature of real-time systems to achieve this goal in an automatic way.
Periodic Task Mining in Embedded System Traces