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| Autori principali: | , , |
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| Natura: | Preprint |
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2024
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| Accesso online: | https://arxiv.org/abs/2410.18989 |
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| _version_ | 1866910666549362688 |
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| author | Naude, Etienne Denny, Paul Luxton-Reilly, Andrew |
| author_facet | Naude, Etienne Denny, Paul Luxton-Reilly, Andrew |
| contents | Producing high-quality code is essential as it makes a codebase more maintainable, reducing the cost and effort associated with a project. However, students learning to program are often given short, automatically graded programming tasks that they do not need to alter or maintain in the future. This can lead to poor-quality code that, although it may pass the test cases associated with the problem, contains anti-patterns - commonly occurring but ineffective or counterproductive programming patterns. This study investigates anti-patterns relating to conditional statements in code submissions made by students in an introductory Python course. Our primary motivation is to understand the prevalence and types of anti-patterns that occur in novice code. We analyzed 41,032 Python code submissions from 398 first-year students, using the open-source "qChecker" tool to identify 15 specific anti-patterns related to conditional statements. Our findings reveal that the most common anti-patterns are "if/else return bool", "confusing else", and "nested if", with "if/else return bool" and "confusing else" alone constituting nearly 60% of the total anti-patterns observed. These anti-patterns were prevalent across various lab exercises, suggesting a need for targeted educational interventions. Our main contribution includes a detailed analysis of anti-patterns in student code, and recommendations for improving coding practices in computing education contexts. The submissions we analyse were also collected prior to the emergence of generative AI tools, providing a snapshot of the issues present in student code before the availability of AI tool support. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2410_18989 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Anti-patterns in Students' Conditional Statements Naude, Etienne Denny, Paul Luxton-Reilly, Andrew Computers and Society Software Engineering Producing high-quality code is essential as it makes a codebase more maintainable, reducing the cost and effort associated with a project. However, students learning to program are often given short, automatically graded programming tasks that they do not need to alter or maintain in the future. This can lead to poor-quality code that, although it may pass the test cases associated with the problem, contains anti-patterns - commonly occurring but ineffective or counterproductive programming patterns. This study investigates anti-patterns relating to conditional statements in code submissions made by students in an introductory Python course. Our primary motivation is to understand the prevalence and types of anti-patterns that occur in novice code. We analyzed 41,032 Python code submissions from 398 first-year students, using the open-source "qChecker" tool to identify 15 specific anti-patterns related to conditional statements. Our findings reveal that the most common anti-patterns are "if/else return bool", "confusing else", and "nested if", with "if/else return bool" and "confusing else" alone constituting nearly 60% of the total anti-patterns observed. These anti-patterns were prevalent across various lab exercises, suggesting a need for targeted educational interventions. Our main contribution includes a detailed analysis of anti-patterns in student code, and recommendations for improving coding practices in computing education contexts. The submissions we analyse were also collected prior to the emergence of generative AI tools, providing a snapshot of the issues present in student code before the availability of AI tool support. |
| title | Anti-patterns in Students' Conditional Statements |
| topic | Computers and Society Software Engineering |
| url | https://arxiv.org/abs/2410.18989 |