Do software engineers use autocompletion features differently than other developers?
| Autor: | Keheliya Gallaba, Rahul Amlekar, Shane McIntosh, Andres Felipe Rincon Gamboa |
|---|---|
| Rok vydání: | 2018 |
| Předmět: |
Autocomplete
Computer science business.industry Local variable 020207 software engineering Small sample 02 engineering and technology Workspace 01 natural sciences World Wide Web 010104 statistics & probability Software 0202 electrical engineering electronic engineering information engineering Code (cryptography) Feature (machine learning) 0101 mathematics Set (psychology) business |
| Zdroj: | MSR |
| DOI: | 10.1145/3196398.3196471 |
| Popis: | Autocomplete is a common workspace feature that is used to recommend code snippets as developers type in their IDEs. Users of autocomplete features no longer need to remember programming syntax and the names and details of the API methods that are needed to accomplish tasks. Moreover, autocompletion of code snippets may have an accelerating effect, lowering the number of keystrokes that are needed to type the code. However, like any tool, implicit tendencies of users may emerge. Knowledge of how developers in different roles use autocompletion features may help to guide future autocompletion development, research, and training material. In this paper, we set out to better understand how usage of autocompletion varies among software engineers and other developers (i.e., academic researchers, industry researchers, hobby programmers, and students). Analysis of autocompletion events in the Mining Software Repositories (MSR) challenge dataset reveals that: (1) rates of autocompletion usage among software engineers and other developers are not significantly different; and (2) although several non-negligible effect sizes of autocompletion targets (e.g., local variables, method names) are detected between the two groups, the rates at which these targets appear do not vary to a significant degree. These inconclusive results are likely due to the small sample size (n = 35); however, they do provide an interesting insight for future studies to build upon. |
| Databáze: | OpenAIRE |
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