A Knowledge-Based Approach to Program Understanding

Abd-El-Hafiz, Salwa K.

doi:10.1007/978-1-4615-2279-9

Cited by 8 publications

(2 citation statements)

References 55 publications

(133 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…It has also been applied to imperative programming languages such as Pascal [1], [14], [26] and C [9]. The source-to-specification approach is consistent with the research on program understanding [3], [23]. An essential step in the approach is to understand the student program by matching it with code templates that are attached with corresponding specifications [14], [17], or matching it with specifications called goal structures [1], [2], schemata [7], plans [9], assertions [24], or processes [26].…”

Section: Introductionmentioning

confidence: 87%

“…Research into the automatic diagnosis of student programs can involve many different fields including intelligent programming tutoring systems, automatic program assessment [25], automatic program understanding [3], [23], program representation [19], and program semantics. Due to the difficulty of the problem of automatic diagnosis of student programs, existing approaches to the automatic diagnosis of student programs are unable to satisfy the above requirements due to various difficulties discussed below.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Transformation-based diagnosis of student programs for programming tutoring systems

Xu¹,

Chee

2003

IIEEE Trans. Software Eng.

View full text Add to dashboard Cite

A robust technology that automates the diagnosis of students' programs is essential for programming tutoring systems. Such technology should be able to determine whether programs coded by a student are correct. If a student's program is incorrect, the system should be able to pinpoint errors in the program as well as explain and correct the errors. Due to the difficulty of this problem, no existing system performs this task entirely satisfactorily, and this problem still hampers the development of programming tutoring systems. This paper describes a transformation-based approach to automate the diagnosis of students' programs for programming tutoring systems. Improved control-flow analysis and data-flow analysis are used in program analysis. Automatic diagnosis of student programs is achieved by comparing the student program with a specimen program at the semantic level after both are standardized. The approach was implemented and tested on 525 real student programs for nine different programming tasks. Test results show that the method satisfies the requirements stated above. Compared to other existing approaches to automatic diagnosis of student programs, the approach developed here is more rigorous and safer in identifying student programming errors. It is also simpler to make use of in practice. Only specimen programs are needed for the diagnosis of student programs. The techniques of program standardization and program comparison developed here may also be useful for research in the fields of program understanding and software maintenance.

show abstract