@conference {apiace:2022:icws,
	title = {How Composable is the Web? An Empirical Study on OpenAPI Data model Compatibility},
	booktitle = {IEEE World Congress on Services (ICWS Symposium on Services for Machine Learning)},
	year = {2022},
	month = {July},
	publisher = {IEEE},
	organization = {IEEE},
	address = {Barcelona, Spain},
	abstract = {Composing Web APIs is a widely adopted practice by developers to speed up the development process of complex Web applications, mashups, and data processing pipelines. However, since most publicly available APIs are built independently of each other, developers often need to invest their efforts in solving incompatibility issues by writing ad-hoc glue code, adapters and message translation mappings. How likely are Web APIs to be directly composable?

The paper presents an empirical study to determine the potential composability of a large collection of 20,587 public Web APIs by verifying their schemas{\textquoteright} compatibility. We define three levels of data model elements compatibility -- considering matches between property names and/or data types -- which can be determined statically based on API descriptions conforming to the OpenAPI specification. The study research questions address: to which extent are Web APIs compatible; the average number of compatible endpoints within each API; the likelihood of finding two APIs with at least one pair of compatible endpoints. 

To perform the analysis we developed a compatibility checker tool which can statically determine API schema compatibility on the three levels and find matching pairs of API responses which can be directly forwarded as requests to the same or other APIs. We run the tool on a dataset of 751,390 request and response message schemas extracted from publicly available OpenAPI descriptions.

The results indicate a relatively high number of compatible APIs when matching their data models only on the level of their elements{\textquoteright} data type. However, this number gets lower narrowing the scope to only the ones handling data objects having identical properties name. The average likelihood of finding two compatible APIs with both matching property names and data types reaches 21\%. Also, the number of compatible endpoints within the same API is very low.},
	keywords = {API Analytics, empirical study, mashups, OpenAPI, Web APIs},
	author = {Souhaila Serbout and Cesare Pautasso and Uwe Zdun}
}
@conference {2021:europlop:api-fragments,
	title = {From OpenAPI Fragments to API Pattern Primitives and Design Smells},
	booktitle = {European Conference on Pattern Languages of Programs (EuroPLoP{\textquoteright}21)},
	year = {2021},
	month = {July},
	publisher = {ACM},
	organization = {ACM},
	address = {Virtual Kloster Irsee, Germany},
	abstract = {In the past few years, the OpenAPI Specification (OAS) has emerged as a standard description language for accurately modeling Web APIs.
Today, thousands of OpenAPI descriptions can be found by mining open source repositories. In this paper, we attempt to exploit these artifacts to extract commonly occurring building blocks used in Web API structures, in order to assist Web API designers in their modelling task. Our work is based on a fragmentation mechanism, that starts from  OpenAPI descriptions of Web APIs to extract their structures, then fragment these structures into smaller blocks. This approach enabled us to extract a large dataset of reoccurring fragments from a collection of 6619 API specifications.  
Such fragments have been found multiple times in the same or across different APIs. We have classified the most reoccurring fragments into four pattern primitives used to expose in the API access to collections of items.  We distinguish for each primitive variants from design smells. This classification is based on the specific combinations of operations associated with the collection items and on an in-depth analysis of their natural language labels and descriptions. The resulting pattern primitives are intended to support designers who would like to introduce one or more collections for a specific class of items in their HTTP-based API.},
	keywords = {API, API fragments, design smells, OpenAPI, patterns},
	doi = {10.1145/3489449.3489998},
	url = {https://zenodo.org/record/5727094$\#$.YZ97mFMo-0o},
	author = {Souhaila Serbout and Cesare Pautasso and Uwe Zdun and Olaf Zimmermann}
}
