Stress-testing algorithms: generating new test instances to elicit insights

  • Smith-Miles, Kate, (Primary Chief Investigator (PCI))

Project: Research

Project Description

This project develops a new paradigm in algorithm testing: creating novel test instances and tools to elicit insights into algorithm strengths and weaknesses. Such advances are urgently needed to support good research practice in academia, and to avoid disasters when deploying algorithms in practice. Extending our recent work in algorithm testing for combinatorial optimisation - described as 'ground-breaking' - this project tackles the challenges needed to generalise the paradigm to other fields: machine learning, forecasting, software testing, and other branches of optimisation. An online repository of test instances and tools will provide a valuable resource to improve research practice and support new insights into algorithm performance.
StatusActive
Effective start/end date8/12/1431/12/19

Funding

  • Australian Research Council (ARC): AUD752,770.00
  • Australian Research Council (ARC): AUD849,602.00
  • Australian Research Council (ARC): AUD924,380.00
  • Australian Research Council (ARC): AUD203,248.00
  • Australian Research Council (ARC): AUD100,000.00
  • Monash University