A Delta Debugger for ILP Query Execution

Because query execution is the most crucial part of Inductive Logic Programming (ILP) algorithms, a lot of effort is invested in developing faster execution mechanisms. These execution mechanisms typically have a low-level implementation, making them hard to debug. Moreover, other factors such as the complexity of the problems handled by ILP algorithms and size of the code base of ILP data mining systems make debugging at this level a very difficult job. In this work, we present the trace-based debugging approach currently used in the development of new execution mechanisms in hipP, the engine underlying the ACE Data Mining system. This debugger uses the delta debugging algorithm to automatically reduce the total time needed to expose bugs in ILP execution, thus making manual debugging step much lighter.Comment: Paper presented at the 16th Workshop on Logic-based Methods in Programming Environments (WLPE2006

Where Are My Intelligent Assistant's Mistakes? A Systematic Testing Approach

Intelligent assistants are handling increasingly critical tasks, but until now, end users have had no way to systematically assess where their assistants make mistakes. For some intelligent assistants, this is a serious problem: if the assistant is doing work that is important, such as assisting with qualitative research or monitoring an elderly parent’s safety, the user may pay a high cost for unnoticed mistakes. This paper addresses the problem with WYSIWYT/ML (What You See Is What You Test for Machine Learning), a human/computer partnership that enables end users to systematically test intelligent assistants. Our empirical evaluation shows that WYSIWYT/ML helped end users find assistants’ mistakes significantly more effectively than ad hoc testing. Not only did it allow users to assess an assistant’s work on an average of 117 predictions in only 10 minutes, it also scaled to a much larger data set, assessing an assistant’s work on 623 out of 1,448 predictions using only the users’ original 10 minutes’ testing effort