Categorization of object-oriented software metrics

Tahvildari, Ladan; Singh, Amar Pal

doi:10.1109/ccece.2000.849705

Cited by 10 publications

(6 citation statements)

References 8 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…The proposed selection of the OO metrics is classified according to four major metrics categories [28]: complexity metrics, coupling metrics, cohesion metrics, and inheritance metrics.…”

Section: Oo Metrics Suitementioning

confidence: 99%

Improving design quality using meta‐pattern transformations: a metric‐based approach

Tahvildari

Kontogiannis

2004

J. Softw. Maint. Evol.: Res. Pract.

View full text Add to dashboard Cite

Improving the design quality of large object-oriented systems during maintenance and evolution is widely regarded as a high-priority objective. Furthermore, for such systems that are subject to frequent modifications, detection and correction of design defects may easily become a very complex task that is even not tractable for manual handling. Therefore, the use of automatic or semi-automatic detection and correction techniques and tools can assist reengineering activities. This paper proposes a framework whereby object-oriented metrics can be used as indicators for automatically detecting situations for particular transformations to be applied in order to improve specific design quality characteristics. The process is based both on modeling the dependencies between design qualities and source code features, and on analyzing the impact that various transformations have on software metrics that quantify the design qualities being improved. He is also a Visiting Scientist with the Centre for Advanced Studies at the IBM Toronto Laboratory. He received his PhD degree from McGill University in 1996. Together with his research group, he investigates technologies to migrate legacy software to object-oriented and network-centric platforms. His specific topics of interest include techniques and tools for source code representation, quality preserving source code transformations, and techniques for the integration of Web services. He was the recipient of the

show abstract

“…The proposed selection of the OO metrics is classified according to four major metrics categories [28]: complexity metrics, coupling metrics, cohesion metrics, and inheritance metrics.…”

Section: Oo Metrics Suitementioning

confidence: 99%

Improving design quality using meta‐pattern transformations: a metric‐based approach

Tahvildari

Kontogiannis

2004

J. Softw. Maint. Evol.: Res. Pract.

View full text Add to dashboard Cite

show abstract

“…There is no single measure that captures all the features of an OO software product [2]. Based on this fact, we have proposed two simple and heuristically validated metrics to assess class inheritance hierarchy in terms of understandability and modifiability.…”

Section: Resultsmentioning

confidence: 99%

“…For about one decade, researchers have been discussing whether a separate set of OO software metrics is needed and what this set should include [2]. Initial proposals focused more towards extension of existing software metrics for procedure-oriented programming [3,4].…”

Section: Introductionmentioning

confidence: 99%

Metrics for maintainability of class inheritance hierarchies

Sheldon

Jerath

Chung

2002

J. Softw. Maint. Evol.: Res. Pract.

View full text Add to dashboard Cite

Since the proposal for the six object-oriented metrics by Chidamber and Kemerer (1994), several studies have been conducted to validate their metrics and have discovered some deficiencies. Consequently, many new metrics for object-oriented systems have been proposed. Among the various measurements of objectoriented characteristics, we focus on the metrics of class inheritance hierarchies in design and maintenance. As such, we propose two simple and heuristic metrics for the class inheritance hierarchy for the maintenance of object-oriented software.In this paper we investigate the work of Chidamber and Kemerer (1994) and Li (1998), and extend their work to apply specifically to the maintenance of a class inheritance hierarchy. In doing so, we suggest new metrics for understandability and modifiability of a class inheritance hierarchy. The main contribution here includes the various comparisons that we have made. We discuss the advantages over Chidamber and Kemerer's (1994) metrics and Henderson-Sellers's (1996) metrics in the context of maintaining class inheritance hierarchies. Figure 6(a): (1 + 1 + 2 + 2 + 4)/5 = 2 AM of Figure 6(a): 2 + (2/2 + 2/2 + 1/2)/5 = 2.5 AU of Figure 6(b): (1 + 2 + 2 + 2)/4 = 1.75 AM of Figure 6(b): 1.75 + (3/2)/4 = 2.13 The understandability and modifiability of Figure 6(b) is better than Figure 6(a) in our metrics. AU of

show abstract

“…cyclomatic complexity; McCabe and Watson, 1994). Of particular importance for HPC are more recently developed software metrics that seem more applicable to OO code (Tahvildari and Singh, 2000a). The measurement of many of those can be automated, but it is not always clear how well they predict programming effort.…”

Section: Productmentioning

confidence: 99%

A Framework for Measuring Supercomputer Productivity

Snir

Bader

2004

The International Journal of High Performance Computing Applica

View full text Add to dashboard Cite

We propose a framework for measuring the productivity of high performance computing (HPC) systems, based on common economic definitions of productivity and on utility theory. We discuss how these definitions can capture essential aspects of HPC systems, such as the importance of time-to-solution and the trade-off between programming time and execution time. Finally, we outline a research program that would lead to the definition of effective productivity metrics for HPC that fit within the proposed framework.

show abstract

Categorization of object-oriented software metrics

Cited by 10 publications

References 8 publications

Improving design quality using meta‐pattern transformations: a metric‐based approach

Improving design quality using meta‐pattern transformations: a metric‐based approach

Metrics for maintainability of class inheritance hierarchies

A Framework for Measuring Supercomputer Productivity

Contact Info

Product

Resources

About