Automatic tools for diagnosis and feedback in a project based learning course

In this paper, we present advanced diagnosis and feedback tools to improve student software quality. After several years of quantitative analysis of the relationship between the assigned grades and certain software features, we have been able to characterize high-quality assembly software. With these results, we have defined new learning objectives after an instructors´ consensus, and we have developed a set of automatic tools that help to supervise how well the objectives have been achieved and to feed this information back to the students along the course. We have successfully used these analysis tools in a new course, with a considerable improvement in software quality factors. In the 2003-2004 academic year, there were 54.7% more subroutines per program, with 48.7% fewer lines per subroutine and an increase of 43.6% in the use of the more complex addressing capabilities. This improvement in quality had a positive impact on students´ surveys