Documenting APIs with examples: Lessons learned with the APIMiner platform

Montandon, João Eduardo; Borges, Hudson Silva; Felix, Daniel; Valente, M.

doi:10.1109/wcre.2013.6671315

Cited by 57 publications

(54 citation statements)

References 7 publications

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“…We also conducted a field study to evaluate the first implementation of APIMiner. We found a right-skewed distribution on the usage of the Android API, considering a dataset of 103 open-source Android systems (Montandon et al, 2013).…”

Section: Related Workmentioning

confidence: 91%

“…However, the examples do not have documentation purposes, because they are highly dependent on a particular development context. In contrast, systems such as APIMiner (Montandon et al, 2013) and eXoaDocs (Kim et al, 2013) generate a new JavaDoc instrumented with source code examples. However, they do not provide support for API usage patterns.…”

Section: Related Workmentioning

confidence: 99%

“…APIMiner (http://apiminer.org) is a tool that instruments JavaDocs with code examples, extracted from API clients (Montandon et al, 2013). As illustrated in Fig.…”

Section: Apiminermentioning

confidence: 99%

“…By clicking on these buttons, developers are presented with source code examples for the documented API methods. A detailed presentation of the algorithms used by APIMiner to extract, summarize, and rank examples is out of the scope of this paper and we refer the interested reader to our previous work (Montandon et al, 2013).…”

Section: Apiminermentioning

confidence: 99%

“…We consider an API usage pattern as set of API methods that are used together with a certain frequency (Robillard et al, 2013). We extend a tool, called APIMiner (Montandon et al, 2013), to mine usage patterns from a dataset of Android open-source applications. This tool also instruments the original API documents with information on the extracted usage patterns.…”

Section: Introductionmentioning

confidence: 99%

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Mining usage patterns for the Android API

Borges

Valente

2015

PeerJ Computer Science

Self Cite

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API methods are not used alone, but in groups and following patterns. However, despite being a key information for API users, most usage patterns are not described in official API documents. In this article, we report a study that evaluates the feasibility of automatically enriching API documents with information on usage patterns. For this purpose, we mine and analyze 1,952 usage patterns, from a set of 396 Android applications. As part of our findings, we report that the Android API has many undocumented and non-trivial usage patterns, which can be inferred using association rule mining algorithms. We also describe a field study where a version of the original Android documentation is instrumented with the extracted usage patterns. During 17 months, this documentation received 77,863 visits from professional Android developers.Subjects Software Engineering

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Section: Related Workmentioning

confidence: 91%

Section: Related Workmentioning

confidence: 99%

“…APIMiner (http://apiminer.org) is a tool that instruments JavaDocs with code examples, extracted from API clients (Montandon et al, 2013). As illustrated in Fig.…”

Section: Apiminermentioning

confidence: 99%

Section: Apiminermentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Mining usage patterns for the Android API

Borges

Valente

2015

PeerJ Computer Science

Self Cite

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Mining unit test cases to synthesize API usage examples

Ghafari

Rubinov

2017

J Software Evolu Process

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Software developers study and reuse existing source code to understand how to properly use application programming interfaces (APIs). However, manually finding sufficient and adequate code examples for a given API is a difficult and a time‐consuming activity. Existing approaches to find or generate examples assume availability of a reasonable set of client code that uses the API. This assumption does not hold for newly released API libraries, non‐widely used APIs, nor private ones. In this work we reuse the important information that is naturally present in test code to circumvent the lack of usage examples for an API when other sources of client code are not available. We propose an approach for automatically identifying the most representative API uses within each unit test case. We then develop an approach to synthesize API usage examples by extracting relevant statements representing the usage of such APIs. We compare the output of a prototype implementation of our approach to both human‐written examples and to a state‐of‐the‐art approach. The obtained results are encouraging; the examples automatically generated with our approach are superior to the state‐of‐the‐art approach and highly similar to the manually constructed examples.

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APISonar: Mining API usage examples

Hora

2020

Softw Pract Exp

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Developers spend a significant part of their time searching for code examples on the web. Often, they look for Application Programming Interface (API) usage examples, that is, how to use APIs provided by libraries and frameworks. For this purpose, several programming websites are available. Some programming websites provide manually created examples: unfortunately, as millions of APIs are available nowadays, they do not cover the majority of the APIs. To alleviate this limitation, other programming websites focus on automatically mining API usage examples from code repositories. To the best of our knowledge, however, these solutions are still very limited: they often present poor, duplicated, and similar API usage examples. In this article, we propose an approach, APISonar, to automatically mine API usage examples from code repositories. Our approach aims to overcome the limitations of current solutions: we focus on presenting readable and reusable API usage examples. We analyze millions of source files provided by 4486 software projects hosted on GitHub. Based on this data, we extract 11 million API usage examples about 1.5 million distinct APIs. We evaluate APISonar by assessing its quality and usage. We show that APISonar is a competitive solution, providing the best API examples in terms of readability and reusability, as compared with popular programming websites. Moreover, despite being a novel website, APISonar attracted a significant amount of users in a short period (3.7K users from 119 countries during 5 months). APISonar is available at www.apisonar.com.

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Documenting APIs with examples: Lessons learned with the APIMiner platform

Cited by 57 publications

References 7 publications

Mining usage patterns for the Android API

Mining usage patterns for the Android API

Mining unit test cases to synthesize API usage examples

APISonar: Mining API usage examples

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