Research on Automatic Scoring Methods for Programs Based on Program Understanding

Ya Ning Wang; Lan Nan Xiao

doi:10.4028/www.scientific.net/AMM.513-517.2054

Paper Titles

Predicting Project Effort Intelligently in early Stages by Applying Genetic Algorithms with Neural Networks
p.2035

Building a Multi-Agent System for Emergency Logistics Collaborative Decision
p.2041

Research on Fast Community Detection Algorithm in Microblog
p.2045

Application of the IOT Technology in the Intelligent Management of University Multimedia Classrooms
p.2050

Research on Automatic Scoring Methods for Programs Based on Program Understanding
p.2054

A Framework for Detecting Weighted Communities in the International Trade Network
p.2059

Adaptive Transmission Control Based on QoE Measurement of Invalid Data Rate
p.2063

Evaluation of Literature Reading Value Based on User Interests Mining
p.2068

Methods in Requirements Elicitation for Application System of Nuclear Power Enterprise
p.2073

HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 513-517Research on Automatic Scoring Methods for Programs...

Research on Automatic Scoring Methods for Programs Based on Program Understanding

Abstract:

This paper discusses three general automatic scoring algorithms including software quality metric algorithm, dynamic testing algorithm and static analysis algorithm based on program understanding, analyzes and designs their rationality, practicality and maneuverability. Therefore, a new automatic scoring strategy which combines dynamic testing and pattern matching based on program understanding is proposed. This method focuses on the accurate expressions on program algorithm and semantic points in student program, enhances the performance of the automatic scoring system and matches the idea of manual scoring better.

You might also be interested in these eBooks

View Preview

Info:

Periodical:

Applied Mechanics and Materials (Volumes 513-517)

Pages:

2054-2058

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.513-517.2054

Citation:

Cite this paper

Online since:

February 2014

Authors:

Ya Ning Wang*, Lan Nan Xiao

Keywords:

Abstract Syntax Tree, Automatic Scoring of Programs, Dynamic Testing, Key Points Matching, Structure Matching

Export:

RIS, BibTeX

Price:

Permissions CCC:

Request Permissions

Permissions PLS:

Request Permissions

Сopyright:

Citation:

* - Corresponding Author

References

[1] Ala-Mutka K. A survey of automatic assessment approaches for programming assignments[J]. Computer Science Education, 2005, 16(2): 83-102.

DOI: 10.1080/08993400500150747

Google Scholar

[2] Mengel S A, Ulans J. Using Verilog LOGISCOPE to analyze student programs[C]/Proc of the 28th Annual Frontiers in Education Conf. Piscataway, NJ: IEEE, 1998: 1213-1218.

DOI: 10.1109/fie.1998.738617

Google Scholar

[3] Morris D S. Automatic grading of student's programming assignments: An interactive process and suit of programs[C]/Proc of the 33rd ASEE/IEEE Frontiers in Education Conf . Piscataway, NJ: IEEE, 2003: 1-6.

DOI: 10.1109/fie.2003.1265998

Google Scholar

[4] Ma Pei-jun, Wang Tian-tian, Su Xiao-hong. Automatic Grading of Student Programs Based on Program Understanding. Journal of Computer Research and Development, 2009, 46(7): 1136-1142 (In Chinese).

Google Scholar

[5] Livadas P E, Johnson T. An optimal algorithm for the construction of the system dependence graph[J]. Information sciences Applications, 2000, 125(1/2/3/4): 99-131.

DOI: 10.1016/s0020-0255(99)00030-4

Google Scholar