[mimmuz]

1. what do you mean with "smallest" (number of state, number of characters, ...)?

2. to evaluate the solution quality on the training data is wrong. In order to mitigate the overfitting risk, the Regex Generator learns the regular expressions from half of the training examples and validates them on the other half of the examples. We also assessed our algorithm on 20 extraction tasks and evaluated the final solutions on unknown corpora (testing): the quality of final solutions is comparable to expert human solutions.

"Sophisticated" regex users don't need our tool: regex generator is intended for novice users or to demonstrate that we can automatically find solutions which are comparable with human ones.

Please note that defining an extraction task is always error prone, there may be errors in the task definition (understanding) or during the regex coding; smart and expert programmers make errors too, there may be corner cases they have not thought about. Sometimes, you need to get the job done--with a fair confidence--and improve it later. This is our view of the real world.

Most important thing: your criticisms are valid for all the problems of supervised machine learning. Do you really think taht driverless car, antispam filters, automatic transaltors and so on are useless only because they are trying to infer a model from partial data? I do not think so.