API governance support through the structural analysis of REST APIs

Haupt, Florian; Leymann, Frank; Vukojevic-Haupt, Karolina

doi:10.1007/s00450-017-0384-1

Cited by 15 publications

(7 citation statements)

References 13 publications

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“…Many works tried to statically extract structural characteristics and functional properties of APIs from their textual descriptions (both informal or formal documentation). Similar to our approach, in [8], the authors performed a structural analysis over 286 real-world publicly available API specifications (retrieved from apis.guru). The authors defined a set of quantitative metrics related to the resources and the HTTP methods supported by the API and identified the challenge of extracting recurring API fragments.…”

Section: Structural Analysis Of Web Apismentioning

confidence: 99%

“…M et al [12] extracted some metrics such as type of Web API, input parameters, output formats, invocation details and if the API has complementary documentation. While [8], and [12] focused more on metrics extraction and providing static results about the sample under study, the authors of [13] performed an in-depth analysis in order to detect five REST design patterns and eight anti-patterns. To do so, they defined and implemented detection heuristics.…”

Section: Structural Analysis Of Web Apismentioning

confidence: 99%

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From OpenAPI Fragments to API Pattern Primitives and Design Smells

Serbout

Pautasso

Zdun

et al. 2021

26th European Conference on Pattern Languages of Programs

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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. CCS CONCEPTS• Software and its engineering → Patterns; Designing software.

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Section: Structural Analysis Of Web Apismentioning

confidence: 99%

Section: Structural Analysis Of Web Apismentioning

confidence: 99%

From OpenAPI Fragments to API Pattern Primitives and Design Smells

Serbout

Pautasso

Zdun

et al. 2021

26th European Conference on Pattern Languages of Programs

View full text Add to dashboard Cite

show abstract

“…One unifying factor with all the challenges identified in the previous section is that they are all related, to a certain degree, to the governance of the provided APIs and data. API governance is defined as "a task mainly applied inside an organization, typically aiming at achieving a certain harmonization of APIs in terms of their non-functional properties, best-practices-support, documentation quality or rule compliance in general" [15]. In [16], API governance is seen encompassing a wide range of activities "starting with the API proposal all the way to its adoption, through requirements gathering, build and deploy, and operations during general availability".…”

Section: A Need For Governance Modelsmentioning

confidence: 99%

Challenges and Governance Solutions for Data Science Services based on Open Data and APIs

Joutsenlahti¹,

Lehtonen²,

Raatikainen³

et al. 2021

Preprint

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Increasingly common open data and open application programming interfaces (APIs) together with the progress of data science -such as artificial intelligence (AI) and especially machine learning (ML) -create opportunities to build novel services by combining data from different sources. In this experience report, we describe our firsthand experiences on open data and in the domain of marine traffic in Finland and Sweden and identified technological opportunities for novel services. We enumerate five challenges that we have encountered with the application of open data: relevant data, historical data, licensing, runtime quality, and API evolution. These challenges affect both business model and technical implementation. We discuss how these challenges could be alleviated by better governance practices for provided open APIs and data.

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“…With respect to input formats, we implemented Parsers for OpenAPI, RAML, and WADL, since these are among the most popular ones based on GitHub stars, Google search hits, and StackOverflow posts [15]. Moreover, most of them offer a convenient tool ecosystem that we can use in our Parser implementations.…”

Section: The Rama Approachmentioning

confidence: 99%

“…While we tried to make it applicable to a wide range of RESTful services by supporting the three formats OpenAPI, RAML, and WADL, there are still other used formats for which we currently do not have a parser, e.g. API Blueprint 15 . Similarly, there are many more proposed service-based metrics we could have implemented in the RAMA CLI.…”

Section: Limitations and Threats To Validitymentioning

confidence: 99%

Collecting Service-Based Maintainability Metrics from RESTful API Descriptions: Static Analysis and Threshold Derivation

Bogner,

Wagner,

Zimmermann

2020

Preprint

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While many maintainability metrics have been explicitly designed for service-based systems, tool-supported approaches to automatically collect these metrics are lacking. Especially in the context of microservices, decentralization and technological heterogeneity may pose challenges for static analysis. We therefore propose the modular and extensible RAMA approach (RESTful API Metric Analyzer) to calculate such metrics from machine-readable interface descriptions of RESTful services. We also provide prototypical tool support, the RAMA CLI, which currently parses the formats OpenAPI, RAML, and WADL and calculates 10 structural service-based metrics proposed in scientific literature. To make RAMA measurement results more actionable, we additionally designed a repeatable benchmark for quartile-based threshold ranges (green, yellow, orange, red). In an exemplary run, we derived thresholds for all RAMA CLI metrics from the interface descriptions of 1,737 publicly available RESTful APIs. Researchers and practitioners can use RAMA to evaluate the maintainability of RESTful services or to support the empirical evaluation of new service interface metrics.

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API governance support through the structural analysis of REST APIs

Cited by 15 publications

References 13 publications

From OpenAPI Fragments to API Pattern Primitives and Design Smells

From OpenAPI Fragments to API Pattern Primitives and Design Smells

Challenges and Governance Solutions for Data Science Services based on Open Data and APIs

Collecting Service-Based Maintainability Metrics from RESTful API Descriptions: Static Analysis and Threshold Derivation

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