Automating Programming Assignment Marking with AST Analysis

assignment;clustering;machine learning;ast analysis;compiler;clang;llvm

Li, Sichuangadvisor:Lam, Patrick ; affiliation1:Faculty of Mathematics ; Lam, Patrick ;

University of Waterloo

关键词: Master Thesis;    clang;    llvm;    assignment;    clustering;    ast analysis;    machine learning;    compiler;   

Others  :  https://uwspace.uwaterloo.ca/bitstream/10012/14348/3/Li_SiChuang.pdf

瑞士|英语

来源: UWSPACE Waterloo Institutional Repository

【 摘 要 】

This thesis presents a novel approach to automatically mark programming assignments. We hypothesize that correct student solution ASTs will be more similar to reference solution ASTs than incorrect student solutions and that their similarities can be quantitatively measured. Our approach first preprocesses the ASTs before computing their tree edit distances. We then aggregate the student's set of edit distances from every reference solution into a final mark for the student. We have implemented our approach in our ClangAutoMarker tool. Our experiments demonstrate promising potential for reducing a human marker's workload but further refinements are needed before its accuracy can be suitable for a live classroom.