19,800 research outputs found
Investigating novice programming mistakes: educator beliefs vs. student data
Educators often form opinions on which programming mistakes novices make most often - for example, in Java: "they always confuse equality with assignment", or "they always call methods with the wrong types". These opinions are generally based solely on personal experience. We report a study to determine if programming educators form a consensus about which Java programming mistakes are the most common. We used the Blackbox data set to check whether the educators' opinions matched data from over 100,000 students - and checked whether this agreement was mediated by educators' experience. We found that educators formed only a weak consensus about which mistakes are most frequent, that their rankings bore only a moderate correspondence to the students in the Blackbox data, and that educators' experience had no effect on this level of agreement. These results raise questions about claims educators make regarding which errors students are most likely to commit
Evaluating Maintainability Prejudices with a Large-Scale Study of Open-Source Projects
Exaggeration or context changes can render maintainability experience into
prejudice. For example, JavaScript is often seen as least elegant language and
hence of lowest maintainability. Such prejudice should not guide decisions
without prior empirical validation. We formulated 10 hypotheses about
maintainability based on prejudices and test them in a large set of open-source
projects (6,897 GitHub repositories, 402 million lines, 5 programming
languages). We operationalize maintainability with five static analysis
metrics. We found that JavaScript code is not worse than other code, Java code
shows higher maintainability than C# code and C code has longer methods than
other code. The quality of interface documentation is better in Java code than
in other code. Code developed by teams is not of higher and large code bases
not of lower maintainability. Projects with high maintainability are not more
popular or more often forked. Overall, most hypotheses are not supported by
open-source data.Comment: 20 page
Meaningful Categorisation of Novice Programmer Errors
The frequency of different kinds of error made by students learning to write computer programs has long been of interest to researchers and educators. In the past, various studies investigated this topic, usually by recording and analysing compiler error messages, and producing tables of relative frequencies of specific errors diagnostics produced by the compiler. In this paper, we improve on such prior studies by investigating actual logical errors in student code, as opposed to diagnostic messages produced by the compiler. The actual errors reported here are more precise, more detailed and more accurate than the diagnostic produced automatically
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