Comparing Semantic Graph Representations of Source Code: The Case of Automatic Feedback on Programming Assignments

• Tipo: Artigo em Revista Científica Internacional
• Data: 2024

Autores

Paiva, JC (Autor) Outra; José Paulo Leal (Autor) FCUP; Figueira, A (Autor) FCUP

Revista

Título: Computer Science and Information Systems

Vol. 21

Páginas: 117-142

ISSN: 1820-0214

Editora: ComSIS Consortium

Indexação

ISI Web of Knowledge - 1 Citação

Scopus - 2 Citações

Outras Informações

ID Authenticus: P-00Z-ZPV

DOI: 10.2298/csis230615004p

Abstract (EN): Static source code analysis techniques are gaining relevance in automated assessment of programming assignments as they can provide less rigorous evaluation and more comprehensive and formative feedback. These techniques focus on source code aspects rather than requiring effective code execution. To this end, syntactic and semantic information encoded in textual data is typically represented internally as graphs, after parsing and other preprocessing stages. Static automated assessment techniques, therefore, draw inferences from intermediate representations to determine the correctness of a solution and derive feedback. Consequently, achieving the most effective semantic graph representation of source code for the specific task is critical, impacting both techniques' accuracy, outcome, and execution time. This paper aims to provide a thorough comparison of the most widespread semantic graph representations for the automated assessment of programming assignments, including usage examples, facets, and costs for each of these representations. A benchmark has been conducted to assess their cost using the Abstract Syntax Tree (AST) as a baseline. The results demonstrate that the Code Property Graph (CPG) is the most feature -rich representation, but also the largest and most space -consuming (about 33% more than AST).

Idioma: Inglês

Tipo (Avaliação Docente): Científica

Nº de páginas: 26