Empirical study of eight LLMs finds overuse of popular libraries like NumPy in up to 45% of unnecessary cases and strong default preference for Python even when suboptimal.
On Designing Better Tools for Learning APIs
1 Pith paper cite this work. Polarity classification is still indexing.
abstract
Modern software development requires a large investment in learning application programming interfaces (APIs). Recent research found that the learning materials themselves are often inadequate: developers struggle to find answers beyond simple usage scenarios. Solving these problems requires a large investment in tool and search engine development. To understand where further investment would be most useful, we ran a study with 19 professional developers to understand what a solution might look like, free of technical constraints. In this paper, we report on design implications of tools for API learning, grounded in the reality of the professional developers themselves. The reoccurring themes in the participants' feedback were trustworthiness, confidentiality, information overload and the need for code examples as first-class documentation artifacts.
fields
cs.SE 1years
2025 1verdicts
UNVERDICTED 1representative citing papers
citing papers explorer
-
A Study of LLMs' Preferences for Libraries and Programming Languages
Empirical study of eight LLMs finds overuse of popular libraries like NumPy in up to 45% of unnecessary cases and strong default preference for Python even when suboptimal.