When developing automatic quizzing systems and intelligent tutoring systems, significant effort has to be spent on developing the problem bank. Question and problem generation is a field of study concerning automating this routine work. The two most common methods of problem generation are constrained random generation and template-based generation, but each of them has disadvantages. In this work, we study a possibility of generating code-tracing learning problems from existing open-source code. We generated a set of learning problems and evaluated their distinctness from human-authored problems and readiness for usage in the learning process. Both teachers and students showed the rate of determining machine-generated problems only slightly above random guessing. Teachers strongly agreed with the problems' relevance and agreed with their suitability for the learning process. Automatic labeling to filter desired problems for the assignment includes used concepts, possible errors during solving, and difficulty estimates. The studied type of learning problem required little additional data to add to the code; our further work will concern problem types with more dynamic data to overcome this limitation.

When developing automated assessments and intelligent tutoring systems, a lot of routine effort goes into developing the bank of learning problems. Problem generation is the way to automate this process. In this paper, we present a method of generating expression-related problems for teaching introductory programming courses. The problems are generated from open-source software code which allows keeping learning problems similar to the production code the students should learn to analyze and write. Generated problems are automatically classified by their difficulties and the knowledge they need to solve, represented as sets of possible errors. This allows seamless integration with adaptive learning algorithms. The evaluation showed that the generated problems are indistinguishable from human-authored problems and suitable for use in the educational process.