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Résumé
Automated feedback and grading platforms can require substantial effort when encoding new programming exercises for first-year students. Such exercises are usually simple but require defining several test cases to ensure their functional correctness. This paper describes our initial effort to leverage automated test case generation for simple programming exercises. We rely on grey-box fuzzing and random combinations of method calls to test the students' solutions and compare their execution to the results produced by a reference implementation. We implemented our approach in a pro- totype, called SimPyTest, openly available on GitHub. We discuss its usage and possible future extensions.
langue originale | Anglais |
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titre | EASEAI 2022 - Proceedings of the 4th International Workshop on Education through Advanced Software Engineering and Artificial Intelligence, co-located with ESEC/FSE 2022 |
rédacteurs en chef | Andreea Vescan, Camelia Serban, Julie Henry, Upsorn Praphamontripong |
Lieu de publication | Singapore |
Editeur | ACM Press |
Pages | 33-36 |
Nombre de pages | 4 |
ISBN (Electronique) | 9781450394536 |
Les DOIs | |
Etat de la publication | Publié - 7 nov. 2022 |
Evénement | 4th International Workshop on Education through Advanced Software Engineering and Artificial Intelligence - Singapore, Singapour Durée: 18 nov. 2022 → 18 nov. 2022 Numéro de conférence: 4 https://easeai.github.io |
Série de publications
Nom | EASEAI 2022 - Proceedings of the 4th International Workshop on Education through Advanced Software Engineering and Artificial Intelligence, co-located with ESEC/FSE 2022 |
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Atelier de travail
Atelier de travail | 4th International Workshop on Education through Advanced Software Engineering and Artificial Intelligence |
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Titre abrégé | EASEAI '22 |
Pays/Territoire | Singapour |
La ville | Singapore |
période | 18/11/22 → 18/11/22 |
Adresse Internet |
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