2021/02/10 by Kai Presler-Marshall, Presler-Marshall, Kai, Sarah Heckman +3 · 1 citation
Computer Science · Decision Sciences · #Software Engineering Research #Software Testing and Debugging Techniques #Scientific Computing and Data Management
paper · pdf · doi:10.48550/arxiv.2102.05729
Computer science educators seek to understand the types of mistakes that students make when learning a new (programming) language so that they can help students avoid those mistakes in the future. While educators know what mistakes students regularly make in languages such as C and Python, students struggle with SQL and regularly make mistakes when working with it. We present an analysis of mistakes that students made when first working with SQL, classify the types of errors introduced, and provide suggestions on how to avoid them going forward. In addition, we present an automated tool, SQLRepair, that is capable of repairing errors introduced by undergraduate programmers when writing SQL queries. Our results show that students find repairs produced by our tool comparable in understandability to queries written by themselves or by other students, suggesting that SQL repair tools may be useful in an educational context. We also provide to the community a benchmark of SQL queries written by the students in our study that we used for evaluation of SQLRepair.