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https://doi.org/10.1145/364155...
Article . 2025 . Peer-reviewed
License: CC BY SA
Data sources: Crossref
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https://dx.doi.org/10.48550/ar...
Article . 2024
License: CC BY SA
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Evaluation of Systems Programming Exercises through Tailored Static Analysis

Authors: Roberto Natella;

Evaluation of Systems Programming Exercises through Tailored Static Analysis

Abstract

In large programming classes, it takes a significant effort from teachers to evaluate exercises and provide detailed feedback. In systems programming, test cases are not sufficient to assess exercises, since concurrency and resource management bugs are difficult to reproduce. This paper presents an experience report on static analysis for the automatic evaluation of systems programming exercises. We design systems programming assignments with static analysis rules that are tailored for each assignment, to provide detailed and accurate feedback. Our evaluation shows that static analysis can identify a significant number of erroneous submissions missed by test cases.

56th SIGCSE Technical Symposium on Computer Science Education (SIGCSE TS 2025)

Country
Italy
Related Organizations
Keywords

Software Engineering (cs.SE), FOS: Computer and information sciences, Computer Science - Computers and Society, Computer Science - Software Engineering, Computers and Society (cs.CY)

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
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