What information about code snippets is available in different software-related documents? An exploratory study

Chatterjee, Preetha; Nishi, Manziba Akanda; Damevski, Kostadin; Augustine, Vinay; Pollock, Lori; Kraft, Nicholas A.

doi:10.1109/saner.2017.7884638

Cited by 19 publications

(12 citation statements)

References 8 publications

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“…(3) The study is not written in English; (4) the study was not peer-reviewed; (5) the study is not accessible in full-text; (6) the study is a duplicate of another study; (7) the study is about mining code, patterns of usage or code recommendation for purposes other than the improvement of API documentation. A total of 4,006 papers was obtained as the result of the search.…”

Section: Selection Criteriamentioning

confidence: 99%

“…They also resort to several resources that document APIs. Examples of such resources include Community Question-Answering (CQAs) such as SO 1 , API descriptions [7], code examples [8], among other resources. Yet, the problems of searching and finding API-related knowledge that satisfies the needs of developers are still open and they are far from being completely solved.…”

Section: Introductionmentioning

confidence: 99%

“…Works along this dimension focus on the problems of lack of API usage examples [11], missing descriptions in API documentation [12] and insufficiency of usage patterns [13]. Other studies include the factors affecting the usability of APIs [14] and code snippets in software-related documentation (including APIs) [7]. Further topics of interest in the literature include the production [15,16,17,18,19], problems/issues [20,21,22,23] and enrichment [12,13,24,25,26] of API learning resources.…”

Section: Introductionmentioning

confidence: 99%

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Scout-bot: Leveraging API Community Knowledge for Exploration and Discovery of API Learning Resources

Ajam

Rodríguez

Benatallah

2021

CLEIej

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Application Programming Interface (API) is a core technology that facilitates developers’ productivity by enabling the reuse of software components. Understanding APIs and gaining knowledge about their usage are therefore fundamental needs for developers. Here, API documentation plays a pivotal role in enabling developers to take full advantage of the benefits brought by APIs. The quality of API documentation has therefore become an important concern given the celerity and dynamics at which APIs are now being made available to users. This article aims at exploring existing research in the area of API documentation in order to identify the associated quality dimensions addressed by the literature. The research is carried out as a systematic mapping study where 103 research papers selected from the literature were reviewed and a total of 5 core quality dimensions were identified and analyzed. By focusing on the two most relevant quality dimensions (understandability and completeness), this article presents an approach to enable API users to explore, discover and learn about APIs through API topic issues discussed in Stack Overflow (SO). We demonstrate the feasibility of our approach through Scout-bot, our tool for exploration and discovery of API topic issues.

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Section: Selection Criteriamentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Scout-bot: Leveraging API Community Knowledge for Exploration and Discovery of API Learning Resources

Ajam

Rodríguez

Benatallah

2021

CLEIej

View full text Add to dashboard Cite

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“…This can severely hamper the API comprehension and the quality of the software built on top of it. To address defective API documents, developers try to infer the correct or required knowledge from the source code of the API itself or by searching source code descriptions reported in external artifacts (e.g., StackOverflow) [10], [11], [12], [13]. For instance, some developers, while discussing the use of popular APIs of Facebook, PHP, or JavaScript, state that: "...the functionality was there, but the only way to find out how to accomplish something was to dig through Stack Overflow" [14].…”

Section: Introductionmentioning

confidence: 99%

Automatic Detection and Repair Recommendation of Directive Defects in Java API Documentation

Zhou

Wang

Yan

et al. 2020

IIEEE Trans. Software Eng.

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Application Programming Interfaces (APIs) represent key tools for software developers to build complex software systems. However, several studies have revealed that even major API providers tend to have incomplete or inconsistent API documentation. This can severely hamper the API comprehension and, as a consequence, the quality of the software built on them. In this paper, we propose DRONE (Detect and Repair of dOcumentatioN dEfects), a framework to automatically detect and repair defects from API documents by leveraging techniques from program analysis, natural language processing, and constraint solving. Specifically, we target at the directives of API documents, which are related to parameter constraints and exception handling declarations. Furthermore, in presence of defects, we also provide a prototypical repair recommendation system. We evaluate our approach on parts of the well-documented APIs of JDK 1.8 APIs (including javaFX) and Android 7.0 (level 24). Across the two empirical studies, our approach can detect API defects with an average F-measure of 79.9%, 71.7%, and 81.4%, respectively. The API repairing capability has also been evaluated on the generated recommendations in a further experiment. User judgments indicate that the constraint information is addressed correctly and concisely in the rendered directives.

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“…Software developers use various online resources like blogs, API documentation, mailing lists, tutorials, Q&A forums, and e‐books so that they can quickly learn new skills and techniques, expand knowledge which they have already obtained, or refresh their memory by remembering something they forgot . They perform more than 20 software development‐related Web searches every day .…”

Section: Introductionmentioning

confidence: 99%

Automatically identifying valid API versions for software development tutorials on the Web

Nishi

Damevski

2019

J Software Evolu Process

Self Cite

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Online tutorials are a valuable source of community‐created information used by numerous developers to learn new APIs and techniques. Once written, tutorials are rarely actively curated and can become dated over time. Tutorials often reference APIs that change rapidly, and deprecated classes, methods, and fields can render tutorials inapplicable to newer releases of the API. Newer tutorials may not be compatible with older APIs that are still in use. In this paper, we first empirically study the tutorial versioning problem, confirming its presence in popular tutorials on the Web. We subsequently propose a technique, based on similar techniques in the literature, for automatically detecting the applicable API version ranges of tutorials, given access to the official API documentation they reference. The proposed technique identifies each API mention in a tutorial and maps the mention to the corresponding API element in the official documentation. The version of the tutorial is determined by combining the version ranges of all of the constituent API mentions. Our technique's precision varies from 61% to 89% and recall varies from 42% to 84% based on different levels of granularity of API mentions and different problem constraints. We observe API methods are the most challenging to accurately disambiguate due to method overloading. As the API mentions in tutorials are often redundant, and each mention of a specific API element commonly occurs several times in a tutorial, the distance of the predicted version range from the true version range is low: 3.61 on average for the tutorials in our sample.

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What information about code snippets is available in different software-related documents? An exploratory study

Cited by 19 publications

References 8 publications

Scout-bot: Leveraging API Community Knowledge for Exploration and Discovery of API Learning Resources

Scout-bot: Leveraging API Community Knowledge for Exploration and Discovery of API Learning Resources

Automatic Detection and Repair Recommendation of Directive Defects in Java API Documentation

Automatically identifying valid API versions for software development tutorials on the Web

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