How to formulate specific how-to questions in software development?

Mingwei Liu, Xin Peng, Andrian Marcus, Christoph Treude, Jiazhan Xie, Huanjun Xu, Yanjun Yang
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引用次数: 9

Abstract

Developers often ask how-to questions using search engines, technical Q&A communities, and interactive Q&A systems to seek help for specific programming tasks. However, they often do not formulate the questions in a specific way, making it hard for the systems to return the best answers. We propose an approach (TaskKG4Q) that interactively helps developers formulate a programming related how-to question. TaskKG4Q is using a programming task knowledge graph (task KG in short) mined from Stack Overflow questions, which provides a hierarchical conceptual structure for tasks in terms of [actions], [objects], and [constraints]. An empirical evaluation of the intrinsic quality of the task KG revealed that 75.0% of the annotated questions in the task KG are correct. The comparison between TaskKG4Q and two baselines revealed that TaskKG4Q can help developers formulate more specific how-to questions. More so, an empirical study with novice programmers revealed that they write more effective questions for finding answers to their programming tasks on Stack Overflow.
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在软件开发中如何制定具体的“如何”问题?
开发人员经常使用搜索引擎、技术问答社区和交互式问答系统来询问如何解决问题,以寻求特定编程任务的帮助。然而,他们通常不会以特定的方式提出问题,这使得系统很难返回最佳答案。我们提出了一种方法(TaskKG4Q),它可以交互式地帮助开发人员制定与编程相关的如何操作问题。TaskKG4Q使用从Stack Overflow问题中挖掘的编程任务知识图(简称任务KG),它根据[动作],[对象]和[约束]为任务提供了分层概念结构。对任务KG内在质量的实证评估表明,任务KG中注释问题的正确率为75.0%。TaskKG4Q和两个基线之间的比较表明,TaskKG4Q可以帮助开发人员制定更具体的how-to问题。更重要的是,一项针对新手程序员的实证研究表明,他们在Stack Overflow上编写更有效的问题来寻找编程任务的答案。
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