A Static Analysis Tool in CS1: Student Usage and Perceptions of PythonTA

Static analysis tools help programmers write better code. In computer science education, such tools can help students identify common style and coding errors, and lead students to fixing them. However, static analysis tools should be deployed in the classroom with care, so that all students—especially novice programmers—are empowered to act on the feedback they receive from these tools. For the past several years, our department has been integrating PythonTA, an educational static analysis tool, into a large CS1 course to provide students regular formative feedback and as part of the grading of programming assignments. This paper reports on a study of over 800 students conducted in the September 2022 offering of this course. Using both quantitative and qualitative methods, we investigate how students used PythonTA and their perceptions of its helpfulness. Overall, students across all levels of prior programming experience report that this static analysis tool was helpful. Though students with prior experience reported being more confident using the tool than novice programmers, this gap in confidence shrank over the semester. A thematic analysis of student comments on PythonTA found that many students appreciated the tool for improving the quality of their code and their own programming habits, but others responded more negatively, including mentioning frustration or confusion caused by PythonTA’s error messages. We discuss our findings and provide recommendations for educators considering the adoption of static analysis tools in their classrooms.