Challenges in Relational Learning for Real-Time Systems Applications

Research output: Chapter in Book/Report/Conference proceedingConference contribution


The problem of determining the Worse Case Execution Time (WCET) of a piece of code is a fundamental one in the Real Time Systems community. Existing methods either try to gain this information by analysis of the program code or by running extensive timing analyses. This paper presents a new approach to the problem based on using Machine Learning in the form of ILP to infer program properties based on sample executions of the code. Additionally, significant improvements in the range of functions learnable and the time taken for learning can be made by the application of more advanced ILP techniques.

Original languageEnglish
Title of host publicationINDUCTIVE LOGIC PROGRAMMING, ILP 2008
EditorsF Zelezny, N Lavrac
Place of PublicationBERLIN
Number of pages17
Volume5194 LNAI
ISBN (Print)978-3-540-85927-7
Publication statusPublished - 2008
Event18th International Conference on Inductive Logic Programming - Prague
Duration: 10 Sep 200812 Sep 2008


Conference18th International Conference on Inductive Logic Programming


  • Worst Case Execution Time (WCET)
  • Inductive Logic Programming (ILP)
  • Lazy Learning
  • Symmetry
  • Efficiency

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