Property-based Software Engineering Measurement
| dc.contributor.author | Briand, Lionel | en_US |
| dc.contributor.author | Morasca, Sandro | en_US |
| dc.contributor.author | R., Victor Basili | en_US |
| dc.date.accessioned | 2004-05-31T11:40:58Z | |
| dc.date.available | 2004-05-31T11:40:58Z | |
| dc.date.created | 1995-10 | en_US |
| dc.date.issued | 1998-10-15 | en_US |
| dc.description.abstract | Little theory exists in the field of software system measurement. Concepts such as complexity, coupling, cohesion or even size are very often subject to interpretation and appear to have inconsistent definitions in the literature. As a consequence, there is little guidance provided to the analyst attempting to define proper measures for specific problems. Many controversies in the literature are simply misunderstandings and stem from the fact that some people talk about different measurement concepts under the same label (complexity is the most common case). There is a need to define unambiguously the most important measurement concepts used in the measurement of software products. One way of doing so is to define precisely what mathematical properties characterize these concepts, regardless of the specific software artifacts to which these concepts are applied. Such a mathematical framework could generate a consensus in the software engineering community and provide a means for better communication among researchers, better guidelines for analysts, and better evaluation methods for commercial static analyzers for practitioners. In this paper, we propose a mathematical framework which is generic, because it is not specific to any particular software artifact, and rigorous, because it is based on precise mathematical concepts. This framework defines several important measurement concepts (size, length, complexity, cohesion, coupling). It does not intend to be complete or fully objective; other frameworks could have been proposed and different choices could have been made. However, we believe that the formalisms and properties we introduce are convenient and intuitive. In addition, we have reviewed the literature on this subject and compared it with our work. This framework contributes constructively to a firmer theoretical ground of software measurement. (Also cross-referenced as UMIACS-TR-94-119) | en_US |
| dc.format.extent | 275812 bytes | |
| dc.format.mimetype | application/postscript | |
| dc.identifier.uri | http://hdl.handle.net/1903/19 | |
| dc.language.iso | en_US | |
| dc.relation.isAvailableAt | Digital Repository at the University of Maryland | en_US |
| dc.relation.isAvailableAt | University of Maryland (College Park, Md.) | en_US |
| dc.relation.isAvailableAt | Tech Reports in Computer Science and Engineering | en_US |
| dc.relation.isAvailableAt | UMIACS Technical Reports | en_US |
| dc.relation.ispartofseries | UM Computer Science Department; CS-TR-3368 | en_US |
| dc.relation.ispartofseries | UMIACS; UMIACS-TR-94-119 | en_US |
| dc.title | Property-based Software Engineering Measurement | en_US |
| dc.type | Technical Report | en_US |