The psychology of computer programming
The psychology of computer programming
Spelling correction in systems programs
Communications of the ACM
DITRAN—a compiler emphasizing diagnostics
Communications of the ACM
Compiler Construction for Digital Computers
Compiler Construction for Digital Computers
Error-proneness in programming
Error-proneness in programming
A study of errors, error-proneness, and error diagnosis of programming languages with special reference to cobol.
An expert system for Cobol program debugging
ACM SIGMIS Database
A bibliography on syntax error handling in context free languages
ACM SIGPLAN Notices
Improving the human factors aspect of database interactions
ACM Transactions on Database Systems (TODS)
ACM Computing Surveys (CSUR)
The economics of designing generalized software
Communications of the ACM
An implementation of structured walk-throughs in teaching Cobol programming
Communications of the ACM
An Approach to Designing Very Fast Approximate String Matching Algorithms
IEEE Transactions on Knowledge and Data Engineering
Toward an effective software reliability evaluation
ICSE '78 Proceedings of the 3rd international conference on Software engineering
SIGCSE '79 Proceedings of the tenth SIGCSE technical symposium on Computer science education
A survey of run-time and logic errors in a classroom environment
ACM SIGCUE Outlook
Neon: A Library for Language Usage Analysis
Software Language Engineering
On compiler error messages: what they say and what they mean
Advances in Human-Computer Interaction
A statistical analysis of syntax errors
Computer Languages
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This paper provides data on Cobol error frequency for correction of errors in student-oriented compilers, improvement of teaching, and changes in programming language. Cobol was studied because of economic importance, widespread usage, possible error-inducing design, and lack of research. The types of errors were identified in a pilot study; then, using the 132 error types found, 1,777 errors were classified in 1,400 runs of 73 Cobol students. Error density was high: 20 percent of the types contained 80 percent of the total frequency, which implies high potential effectiveness for software-based correction of Cobol. Surprisingly, only four high-frequency errors were error-prone, which implies minimal error inducing design. 80 percent of Cobol misspellings were classifiable in the four error categories of previous researchers, which implies that Cobol misspellings are correctable by existent algorithms. Reserved word usage was not error-prone, which implies minimal interference with usage of reserved words. Over 80 percent of error diagnosis was found to be inaccurate. Such feedback is not optimal for users, particularly for the learning user of Cobol.