Measuring commercial PL/I programs using Halstead's criteria

Elshoff, James L.

doi:10.1145/956003.956006

Cited by 41 publications

(9 citation statements)

References 5 publications

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“…Whether or not these as.iumptiotis are reasonable, experiments show that L yields a close estimate of the Program Level, L (Bulut 1974, Elshoff 1976, Halstead 1977, and Ottenstein 1981.…”

Section: Critical Analysismentioning

confidence: 96%

“…The coefficient of correlation shows that a strong relationship exists between the Implementation Length and the Estimated Length. In fact, Elshoff (1976) used the Estimated Length equation to calculate the length of 154 PL/l programs. He then compared the Estimated Length with the Implementation Length and found correlations higher than 0.97 between the two measures, giving strong support to the assumption that this equation can be used to estimate the actual length.…”

Section: Estimated Lengthmentioning

confidence: 99%

“…The average correlation coefficient was 0.968 (significant at the 0.001 level) between the Estimated Length and the Implementation Length. Elshoff (1976) tested the length estimator on 154 programs. The correlation between actual and estimated lengths was 0.985 for structured programs and 0.976 for nonstructured programs, further validating this metric.…”

Section: Empirical Evidencementioning

confidence: 99%

“…SQM RELATIONSHIP.-Maintainability TOOLS: LOGISCOPE, Verilog USA Inc., Alexandria, VA PC-Metric, SET Laboratories, Inc., Mulino, OR F " RENCES: Albrecht and Gaffney 1983;Arthur 1983;Bulut 1974;Carver 1986;Coulter 1983;Elshoff 1976;Fitzsimmons 1978;Funrami 1976;Gordon 1976Halstead 1972Halstead , 1977Halstead , 1979Halstead and Zislis 1973;jones 1978;Kafura and Reddy 1987;Lassez 1981;Li and Cheung 1987;; Shen, Conte, and Dunsmore…”

Section: Critical Analysismentioning

confidence: 99%

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Software Quality Metrics

Pries¹,

Quigley²

2008

Project Management of Complex and Embedded Systems

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“…Whether or not these as.iumptiotis are reasonable, experiments show that L yields a close estimate of the Program Level, L (Bulut 1974, Elshoff 1976, Halstead 1977, and Ottenstein 1981.…”

Section: Critical Analysismentioning

confidence: 96%

Section: Estimated Lengthmentioning

confidence: 99%

Section: Empirical Evidencementioning

confidence: 99%

Section: Critical Analysismentioning

confidence: 99%

See 2 more Smart Citations

Software Quality Metrics

Pries¹,

Quigley²

2008

Project Management of Complex and Embedded Systems

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“…The theory of software science has grown to include quantitative measures of program level, language level, algorithm purity, program clarity, the effect of modularization, programming effort, and programming time. Preliminary tests of the theory have shown very high correlations between the software science metrics and such measures as the number of bugs in programs (Funami and Halstead [10]; Cornell and Halstead [8]), programming time (Gordon and Halstead [12]), and quality of programs (Elshoff [9]; Halstead [16]; Bulut and Halstead [5]; Gordon [11]). …”

Section: Kolence's Theory Of Software Physicsmentioning

confidence: 99%

A Review and Evaluation of Software Science

1978

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During recent years, there have been many attempts to define and measure the "complexity" of a computer program. Maurme Halstead has developed a theory that gives objective measures of software complexity. Various studms and experiments have shown that the theory's predictmns of the number of bugs in programs and of the time required to implement a program are amazingly accurate. It is a promising theory worthy of much more probing scientific investigation.This paper reviews the theory, called "software science," and the evidence supporting it. A bmef description of a related theory, called "software physics," is included.

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Software Development Metrics

Reynolds

2002

Encyclopedia of Software Engineering

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Software development metrics are the means by which software engineers assess and predict aspects of those processes, resources, and products that are relevant to the software engineering activity. Metrics serve as the compass that guides the discipline in the search for efficient and effective solutions to complex problems. Future progress in the discipline will be closely tied to the ability of these metrics to provide accurate and timely information to those software engineers navigating the problem‐solving seas. In this article, the notion of a software metric and its formulation for use in a problem‐solving situation are presented. A description of the basic categories of software metrics based on the entities of the software development process that they measure is given. Metrics that have been proposed for each phase of the software development process using this classification are surveyed.

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Measuring commercial PL/I programs using Halstead's criteria

Cited by 41 publications

References 5 publications

Software Quality Metrics

Software Quality Metrics

A Review and Evaluation of Software Science

Software Development Metrics

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