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In addition to their vital role in professional software development,Application Programming Interfaces (APIs) are now increasingly used bynon-professional programmers, including end users, scientists and experts fromother domains. Therefore, good APIs must meet old and new user requirements.Most of the re-search on API evaluation and design derives from user-centered,cognitive perspectives on human-computer interaction. As an alternative, wepresent a lower-threshold variant of a previously proposed semiotic APIevaluation tool. We illustrate the procedures and power of this variant, calledAPI Signification Inspection (API-SI), with Keras, a Deep Learning API. Theillustration also shows how the method can complement and fertilize APIusability studies. Additionally, API-SI is packaged as an introductory semiotictool that API designers and researchers can use to evaluate the communicationof design intent and product rationale to other programmers through implicitand explicit signs thereof, encountered in the API structure, behavior anddocumentation.

The Case for API Communicability Evaluation: Introducing API-SI with Examples from Keras