How Dynamic Features Affect API Usages? An Empirical Study of API Misuses in Python Programs

Incorrect usages of Application Programming Interfaces (APIs) may lead to unexpected problems during the software development process. Although there have been many attempts to address API-misuse issues, most of them are mainly for static languages. In contrast, API misuses in dynamic languages are rarely covered, mostly due to challenges about dynamic features. In this paper, we develop the first-ever comprehensive study of API misuses for Python programs. To accomplish this, we manually analyze 79,096 commits of six popular open-source Python projects on GitHub to collect true-positive cases. Based on the validation, we develop a classification of Python API Misuses, called PAM, and a dataset, PAMBench, containing 670 validated real-world API-misuse cases in popular Python programs. For each API-misuse case, we explore its root cause, symptom, program issue and repair method. Specifically, we pay attention to the effect of dynamic features on API usages in Python. The systematic study on PAMBench shows that, most importantly, dynamic features, especially type dynamics, have a non-negligible impact on API usages in Python, mainly related to incorrect assumptions about the type, callable state, attribute and existence of caller object, method call itself, passed argument(s) and return value during an API invocation. Our root-cause analysis reveals the importance of correct design, implementation, annotation, checking and recording about the types and states of all parts of API method calls during Python program development. Finally, we present possible solutions for more secure, reliable and maintainable API usages in Python.