Once a programmer knows one language, they can leverage concepts and knowledge already learned, and easily pick up another programming language. But is that always the case? To understand if programmers have difficulty learning additional programming languages, we conducted an empirical study of Stack Overflow questions across 18 different programming languages. We hypothesized that previous knowledge could potentially interfere with learning a new programming language. From our inspection of 450 Stack Overflow questions, we found 276 instances of interference that occurred due to faulty assumptions originating from knowledge about a different language. To understand why these difficulties occurred, we conducted semi-structured interviews with 16 professional programmers. The interviews revealed that programmers make failed attempts to relate a new programming language with what they already know. Our findings inform design implications for technical authors, toolsmiths, and language designers, such as designing documentation and automated tools that reduce interference, anticipating uncommon language transitions during language design, and welcoming programmers not just into a language, but its entire ecosystem.
Nischal Shrestha North Carolina State University
Colton Botta North Carolina State University
Tue 6 Oct
| 10:50 - 12:30: Paper Presentations - Cognition at TBD4 |
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| 10:50 - 11:10 Talk |
A Tale from the Trenches: Cognitive Biases and Software Development Technical Souti Chattopadhyay Graduate Student , Nicholas Nelson Oregon State University , Audrey Au Oregon State University , Natalia Morales Oregon State University , Christopher Sanchez Oregon State University , Rahul Pandita Phase Change Software , Anita Sarma Oregon State University |
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| 11:10 - 11:30 Talk |
Recognizing Developers' Emotions while Programming Technical Daniela Girardi University of Bari , Nicole Novielli University of Bari , Davide Fucci Blekinge Institute of Technology , Filippo Lanubile University of Bari |
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| 11:30 - 11:50 Talk |
Neurological Divide: An fMRI Study of Prose and Code Writing Technical Ryan Krueger University of Michigan , Yu Huang University of Michigan , Xinyu Liu University of Michigan , Tyler Santander University of California at Santa Barbara , Westley Weimer University of Michigan, USA , Kevin Leach University of Michigan |
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| 11:50 - 12:10 Talk |
Assessing Practitioner Beliefs SEIP Shrikanth N C North Carolina State University , Tim Menzies North Carolina State University |
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| 12:10 - 12:30 Talk |
Here We Go Again: Why Is It Difficult for Developers to Learn Another Programming Language? Technical Nischal Shrestha North Carolina State University , Colton Botta North Carolina State University , Titus Barik Microsoft , Chris Parnin North Carolina State University |
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Google软件测试之道
James A. Whittaker、Jason Arbon、Jeff Carollo / 黄利、李中杰、薛明 / 人民邮电出版社 / 2013-10 / 59.00元
每天，google都要测试和发布数百万个源文件、亿万行的代码。数以亿计的构建动作会触发几百万次的自动化测试，并在好几十万个浏览器实例上执行。面对这些看似不可能完成的任务，谷歌是如何测试的呢？ 《google软件测试之道》从内部视角告诉你这个世界上知名的互联网公司是如何应对21世纪软件测试的独特挑战的。《google软件测试之道》抓住了google做测试的本质，抓住了google测试这个时代最......一起来看看 《Google软件测试之道》 这本书的介绍吧!
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正则表达式在线测试
正则表达式在线测试