Live API documentation

Subramanian, Siddharth; Inozemtseva, Laura; Holmes, Reid

doi:10.1145/2568225.2568313

Cited by 221 publications

(154 citation statements)

References 16 publications

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“…Identifying the most significantly discussed APIs in energy related posts can help API designers identify problematic APIs and uncover and rectify the underlying usability issues associated with them. Approach: We used a static analysis tool called Baker [9] to find the fully qualified names of Java classes and types (hereafter referred to as APIs) used in code snippets. Only results containing a single API (Baker returns several suggestions if it cannot be certain) were considered as this allows for a high precision of 0.98 while still having a recall of 0.83.…”

Section: Rq 3 Which Apis Are Significantly Discussed In the Energymentioning

confidence: 99%

Going Green: An Exploratory Analysis of Energy-Related Questions

Malik

Zhao

Godfrey

2015

2015 IEEE/ACM 12th Working Conference on Mining Software Repositories

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-The popularity of smartphones -small computers that run on battery power -has exploded in the last decade. Unsurprisingly, power consumption is an overarching concern for mobile app developers, who are anxious to learn about powerrelated problems that are encountered by others. In this paper, we present an empirical study exploring the characteristics of energy-related questions posed in StackOverflow, issues faced by the developers, and the most significantly discussed APIs. We extracted a sample of 5009 StackOverflow questions, and manually analyzed 1000 posts of Android-related energy questions. Our study shows that developers are most concerned about energy-related issues that concern improper implementations, sensor, and radio utilization.

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Section: Rq 3 Which Apis Are Significantly Discussed In the Energymentioning

confidence: 99%

Going Green: An Exploratory Analysis of Energy-Related Questions

Malik

Zhao

Godfrey

2015

2015 IEEE/ACM 12th Working Conference on Mining Software Repositories

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“…Their evaluation results showed that the approach provides code examples with high precision and boosts programmer productivity. In a similar effort, Subramanian et al [34] introduced Baker, an iterative, deductive method for linking source code examples to API documentation. In contrast to these tools, SISE links natural language sentences from Stack Overflow to API documentation.…”

Section: Improving Api Documentationmentioning

confidence: 99%

Augmenting API documentation with insights from stack overflow

Treude

Robillard

2016

Proceedings of the 38th International Conference on Software Engineering

235

113

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Software developers need access to different kinds of information which is often dispersed among different documentation sources, such as API documentation or Stack Overflow. We present an approach to automatically augment API documentation with "insight sentences" from Stack Overflowsentences that are related to a particular API type and that provide insight not contained in the API documentation of that type. Based on a development set of 1,574 sentences, we compare the performance of two state-of-the-art summarization techniques as well as a pattern-based approach for insight sentence extraction. We then present SISE, a novel machine learning based approach that uses as features the sentences themselves, their formatting, their question, their answer, and their authors as well as part-of-speech tags and the similarity of a sentence to the corresponding API documentation. With SISE, we were able to achieve a precision of 0.64 and a coverage of 0.7 on the development set. In a comparative study with eight software developers, we found that SISE resulted in the highest number of sentences that were considered to add useful information not found in the API documentation. These results indicate that taking into account the meta data available on Stack Overflow as well as part-of-speech tags can significantly improve unsupervised extraction approaches when applied to Stack Overflow data.

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“…Enclosing class names of methods in snippets are often ambiguous [13] (i.e., method name qualification). For example, Subramanian et al [42] found that there are unqualified method name getId() more than 27,000 times in their oracle containing 1.6 million types (i.e., classes and method-/field signatures) whereas partially qualified name Node.getId() can be identified only few times. Thus, recovering unqualified names can improve the accuracy of code search.…”

Section: Answersmentioning

confidence: 99%

Augmenting and structuring user queries to support efficient free-form code search

Sirres

Bissyandé

Kim

et al. 2018

Proceedings of the 40th International Conference on Software Engineering

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Source code terms such as method names and variable types are often different from conceptual words mentioned in a search query. This vocabulary mismatch problem can make code search inefficient. In this paper, we present COde voCABUlary (CoCaBu), an approach to resolving the vocabulary mismatch problem when dealing with free-form code search queries. Our approach leverages common developer questions and the associated expert answers to augment user queries with the relevant, but missing, structural code entities in order to improve the performance of matching relevant code examples within large code repositories. To instantiate this approach, we build GitSearch, a code search engine, on top of GitHub and Stack Overflow Q&A data. We evaluate GitSearch in several dimensions to demonstrate that (1) its code search results are correct with respect to user-accepted answers; (2) the results are qualitatively better than those of existing Internet-scale code search engines; (3) our engine is competitive against web search engines, such as Google, in helping users complete solve programming tasks; and (4) GitSearch provides code examples that are acceptable or interesting to the community as answers for Stack Overflow questions.

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Live API documentation

Cited by 221 publications

References 16 publications

Going Green: An Exploratory Analysis of Energy-Related Questions

Going Green: An Exploratory Analysis of Energy-Related Questions

Augmenting API documentation with insights from stack overflow

Augmenting and structuring user queries to support efficient free-form code search

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