Automatic categorization of questions from Q&amp;A sites

Campos, Eduardo Cunha; Maia, Marcelo de Almeida

doi:10.1145/2554850.2555117

Cited by 10 publications

(4 citation statements)

References 5 publications

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“…To verify the feasibility of constructing automatic classifiers for these categories of question, we performed experimentation with different classification mechanisms [30]. Based on the analysis of the most important features in that work, we constructed for this work a rule-based binary classifier to automatically filter only how-to-do-it questions from the others.…”

Section: Selection Of Threads With How-to-do-it Questionmentioning

confidence: 99%

Bootstrapping cookbooks for APIs from crowd knowledge on Stack Overflow

Souza

Campos

Madeiral

et al. 2019

Information and Software Technology

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Context: Well established libraries typically have API documentation. However, they frequently lack examples and explanations, possibly making difficult their effective reuse. Stack Overflow is a question-and-answer website oriented to issues related to software development. Despite the increasing adoption of Stack Overflow, the information related to a particular topic (e.g., an API) is spread across the website. Thus, Stack Overflow still lacks organization of the crowd knowledge available on it.Objective: Our target goal is to address the problem of the poor quality documentation for APIs by providing an alternative artifact to document them based on the crowd knowledge available on Stack Overflow, called crowd cookbook. A cookbook is a recipe-oriented book, and we refer to our cookbook as crowd cookbook since it contains content generated by a crowd. The cookbooks are meant to be used through an exploration process, i.e. browsing.Method: In this paper, we present a semi-automatic approach that organizes the crowd knowledge available on Stack Overflow to build cookbooks for APIs. We have generated cookbooks for three APIs widely used by the software development community: SWT, LINQ and QT. We have also defined desired properties that crowd cookbooks must meet, and we conducted an evaluation of the cookbooks against these properties with human subjects.Results: The results showed that the cookbooks built using our approach, in general, meet those properties. As a highlight, most of the recipes were considered appropriate to be in the cookbooks and have self-contained information.Conclusions: We concluded that our approach is capable to produce adequate cookbooks automatically, which can be as useful as manually produced cookbooks. This opens an opportunity for API designers to enrich existent cookbooks with the different points of view from the crowd, or even to generate initial versions of new cookbooks.

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Section: Selection Of Threads With How-to-do-it Questionmentioning

confidence: 99%

Bootstrapping cookbooks for APIs from crowd knowledge on Stack Overflow

Souza

Campos

Madeiral

et al. 2019

Information and Software Technology

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“…Campos and de Almeida Maia (2014) carried out a thorough evaluation of different classification algorithms to identify the best one which can classify questions efficiently from SO. The classification algorithms used are as follows: Naive Bayes (NB), Multilayer Perceptron, SVM, K-Nearest Neighbors (K-NN), J4.8 DT, and Random Forests.…”

Section: Mining So For Software Developmentmentioning

confidence: 99%

A survey on mining stack overflow: question and answering (Q&A) community

Ahmad

Feng

Shi

et al. 2018

DTA

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Purpose Software developers extensively use stack overflow (SO) for knowledge sharing on software development. Thus, software engineering researchers have started mining the structured/unstructured data present in certain software repositories including the Q&A software developer community SO, with the aim to improve software development. The purpose of this paper is show that how academics/practitioners can get benefit from the valuable user-generated content shared on various online social networks, specifically from Q&A community SO for software development. Design/methodology/approach A comprehensive literature review was conducted and 166 research papers on SO were categorized about software development from the inception of SO till June 2016. Findings Most of the studies revolve around a limited number of software development tasks; approximately 70 percent of the papers used millions of posts data, applied basic machine learning methods, and conducted investigations semi-automatically and quantitative studies. Thus, future research should focus on the overcoming existing identified challenges and gaps. Practical implications The work on SO is classified into two main categories; “SO design and usage” and “SO content applications.” These categories not only give insights to Q&A forum providers about the shortcomings in design and usage of such forums but also provide ways to overcome them in future. It also enables software developers to exploit such forums for the identified under-utilized tasks of software development. Originality/value The study is the first of its kind to explore the work on SO about software development and makes an original contribution by presenting a comprehensive review, design/usage shortcomings of Q&A sites, and future research challenges.

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“…We could not reuse the classifier built by Souza et al [7] and Campos et al [14], as this classifier does not address debug-corrective questions. Also the classifier built by Campos and Maia [15] does not focus only on how-to-doit and debug-corrective.…”

Section: Automatic Classification Of Questionsmentioning

confidence: 99%

Redocumenting APIs with crowd knowledge: a coverage analysis based on question types

et al. 2016

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Background: Software libraries and frameworks play an important role in software system development. The appropriate usage of their functionalities/components through their APIs, however, is a challenge for developers. Usually, API documentation, when it exists, is insufficient to assist them in their programming tasks. There are few API documentation writers for the many potential readers, resulting in the lack of explanations and examples concerning different scenarios and perspectives. The interaction of developers on the Web, on the other hand, generates content concerning APIs from different perspectives, which can be used to document APIs, also known as crowd documentation. Methods: In this paper, we present a study regarding the knowledge generated by the crowd on the Stack Overflow question-and-answer website. Our main goal is to understand how the crowd can contribute for API documentation on two programming tasks: how to implement a scenario using an API (how-to-do-it), and how to fix domain-independent bugs in an existing code where there was a misunderstanding regarding the usage of an API (debug-corrective). We classified questions available on Stack Overflow by the main concerns of askers, and we used those classified as how-to-do-it and debug-corrective to analyze the coverage of API elements on the discussions related to such questions. Our cases included the well-known and popular Swing and Android APIs. Results: Our main findings showed that the crowd provides more content for debug-corrective tasks than for how-to-do-it tasks, regardless of the API. Android API elements are more discussed by the crowd compared to Swing. Moreover, we observed that some API elements are frequently mentioned together in discussions, and that there is a strong association between API coverage on Stack Overflow and its usage in real software systems. Conclusions: Crowd documentation may not be a complete substitute for official documentation because of its partial coverage, especially for how-to-do-it tasks. However, it can still significantly enhance the existent documentation, especially for the most commonly used API elements, providing code samples and explanations on a large variety of usage nuances. Finally, taking advantage of the high coverage for debug-corrective tasks, a new kind of debugging assistant may be conceived.

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Automatic categorization of questions from Q&A sites

Cited by 10 publications

References 5 publications

Bootstrapping cookbooks for APIs from crowd knowledge on Stack Overflow

Bootstrapping cookbooks for APIs from crowd knowledge on Stack Overflow

A survey on mining stack overflow: question and answering (Q&A) community

Redocumenting APIs with crowd knowledge: a coverage analysis based on question types

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