Programming factors - language features that help explain programming complexity

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Programming factors - language features that help explain programming complexity

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ACM Annual Conference/Annual Meeting archive
Proceedings of the 1978 annual conference - Volume 2 table of contents

Pages: 554 - 560

Year of Publication: 1978

ISBN:0-89791-000-1

Authors

H. E. Dunsmore
J. D. Gannon

Sponsor

ACM: Association for Computing Machinery

Publisher

ACM New York, NY, USA

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Downloads (6 Weeks): 0, Downloads (12 Months): 18, Citation Count: 2

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ABSTRACT

Programming complexity (the amount of difficulty in constructing a program) may depend upon certain programming factors (choices of programming language features). Using program changes as a programming complexity measure, previous research has identified five potential programming factors. This paper suggests that subjects tend to use the same levels of these factors in two different programming languages supporting the conjecture that these factors are elements of individual programming style. It also describes five potential programming factors, and although each has intuitive appeal, only average procedure length was related to programming complexity.

REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

	1	Hubert Earl Dunsmore, The influence of programming factors on programming complexity., 1978
	2	Dunsmore, H. E. and Gannon, J. D. Experimental investigation of programming complexity, Proceedings of Sixteenth Annual Technical Symposium: Systems and Software, Washington, D.C. (June, 1977), 117-125.
	3	J. D. Gannon, An experimental evaluation of data type conventions, Communications of the ACM, v.20 n.8, p.584-595, Aug. 1977 [doi>10.1145/359763.359800]
	4	Knuth, D. E. An empirical study of FORTRAN programs, Software - Practice and Experience 1 (1971), 105-333.
	5	McCabe, T. J. A complexity measure, IEEE Transactions of Software Engineering 2,4 (December 1976), 308-320.
	6	Siegel, S. Nonparametric Statistics for the Behavioral Sciences, McGraw-Hill Book Co., New York, 1956.

CITED BY 2

	Gerrit E. DeYoung , Garry R. Kampen , James M. Topolski, Analyzer-generated and human-judged predictors of computer program readability, Proceedings of the 1982 conference on Human factors in computing systems, p.223-228, March 15-17, 1982, Gaithersburg, Maryland, United States
	Taiga Nakamura , Lorin Hochstein , Victor R. Basili, Identifying domain-specific defect classes using inspections and change history, Proceedings of the 2006 ACM/IEEE international symposium on International symposium on empirical software engineering, September 21-22, 2006, Rio de Janeiro, Brazil