Skip navigation

Measuring the comprehensibility of Z specifications

Measuring the comprehensibility of Z specifications

Finney, Kate, Rennolls, Keith and Fedorec, Alex (1998) Measuring the comprehensibility of Z specifications. Journal of Systems and Software, 42 (1). pp. 3-15. ISSN 0164-1212 (doi:10.1016/S0164-1212(98)00003-X)

Full text not available from this repository.

Abstract

The effects of natural language comments, meaningful variable names, and structure on the comprehensibility of Z specifications are investigated through a designed experiment conducted with a range of undergraduate and post-graduate student subjects. The times taken on three assessment questions are analysed and related to the abilities of the students as indicated by their total score, with the result that stronger students need less time than weaker students to complete the assessment. Individual question scores, and total score, are then analysed and the influence of comments, naming, structure and level of student's class are determined. In the whole experimental group, only meaningful naming significantly enhances comprehension. In contrast, for those obtaining the best score of 3/3 the only significant factor is commenting. Finally, the subjects' ratings of the five specifications used in the study in terms of their perceived comprehensibility have been analysed. Comments, naming and structure are again found to be of importance in the group when analysed as a whole, but in the sub-group of best performing subjects only the comments had an effect on perceived comprehensibility.

Item Type: Article
Uncontrolled Keywords: comprehensibility, Z specifications, measurement
Subjects: Q Science > QA Mathematics
Pre-2014 Departments: School of Computing & Mathematical Sciences
School of Computing & Mathematical Sciences > Centre for Numerical Modelling & Process Analysis
School of Computing & Mathematical Sciences > Centre for Numerical Modelling & Process Analysis > Fire Safety Engineering Group
School of Computing & Mathematical Sciences > Computer & Computational Science Research Group
School of Computing & Mathematical Sciences > Department of Computer Science
School of Computing & Mathematical Sciences > Statistics & Operational Research Group
Related URLs:
Last Modified: 14 Oct 2016 08:59
Selected for GREAT 2016: None
Selected for GREAT 2017: None
Selected for GREAT 2018: None
URI: http://gala.gre.ac.uk/id/eprint/112

Actions (login required)

View Item View Item