Gina R. Bai, Joshua Kayani, and Kathryn T. Stolee. 2020. How Graduate Computing Students Search When Using an Unfamiliar Programming Language. In Proceedings of the 28th International Conference on Program Comprehension (ICPC ‘20). ACM, New York, NY, USA, 160–171. https://doi.org/10.1145/3387904.3389274
Developers and computing students are usually expected to master multiple programming languages. To learn a new language, developers often turn to online search to find information and code examples. However, insights on how learners perform code search when working with an unfamiliar language are lacking. Understanding how learners search and the challenges they encounter when using an unfamiliar language can motivate future tools and techniques to better support subsequent language learners.
Research on code search behavior typically involves monitoring developers during search activities through logs or in situ surveys. We conducted a study on how computing students search for code in an unfamiliar programming language with 18 graduate students working on VBA tasks in a lab environment. Our surveys explicitly asked about search success and query reformulation to gather reliable data on those metrics. By analyzing the combination of search logs and survey responses, we found that students typically search to explore APIs or find example code. Approximately 50% of queries that precede clicks on documentation or tutorials successfully solved the problem. Students frequently borrowed terms from languages with which they are familiar when searching for examples in an unfamiliar language, but term borrowing did not impede search success. Edit distances between reformulated queries and non-reformulated queries were nearly the same. These results have implications for code search research, especially on reformulation, and for research on supporting programmers when learning a new language.