Measurement of object-oriented software spatial complexity

Chhabra, Jitender Kumar; Aggarwal, K. K.; Singh, Yogesh

doi:10.1016/j.infsof.2004.01.001

Cited by 21 publications

(20 citation statements)

References 33 publications

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“…For example, reference [20] introduces a computation method for structured program complexity based on entropy evaluation of random single-value response functions and characteristic software functions. Based on class and object, reference [21] introduces two kinds of object-oriented measurement methods of software space complexity.…”

Section: Measurement Of Object-oriented Programmentioning

confidence: 99%

Research and Measurement of Software Complexity Based on Wuli, Shili, Renli (WSR) and Information Entropy

Jiang

2015

Entropy

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Abstract:Complexity is an important factor throughout the software life cycle. It is increasingly difficult to guarantee software quality, cost and development progress with the increase in complexity. Excessive complexity is one of the main reasons for the failure of software projects, so effective recognition, measurement and control of complexity becomes the key of project management. At first, this paper analyzes the current research situation of software complexity systematically and points out existing problems in current research. Then, it proposes a WSR framework of software complexity, which divides the complexity of software into three levels of Wuli (WL), Shili (SL) and Renli (RL), so that the staff in different roles may have a better understanding of complexity. Man is the main source of complexity, but the current research focuses on WL complexity, and the research of RL complexity is extremely scarce, so this paper emphasizes the research of RL complexity of software projects. This paper not only analyzes the composing factors of RL complexity, but also provides the definition of RL complexity. Moreover, it puts forward a quantitative measurement method of the complexity of personnel organization hierarchy and the complexity of personnel communication information based on information entropy first and analyzes and validates the scientificity and rationality of this measurement method through a large number of cases.

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Section: Measurement Of Object-oriented Programmentioning

confidence: 99%

Research and Measurement of Software Complexity Based on Wuli, Shili, Renli (WSR) and Information Entropy

Jiang

2015

Entropy

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“…Douce et al [7] and Chhabra et al [5] have proposed measures for the measurement of comprehensibility of object-oriented programs in terms of spatial complexity. But, all these spatial complexity measures were formulated by keeping C++ language in mind and still, there are no spatial complexity measures available, which can be directly applicable to Java programs.…”

Section: Spatial Complexity Measures For Java Programsmentioning

confidence: 99%

“…But, all these spatial complexity measures were formulated by keeping C++ language in mind and still, there are no spatial complexity measures available, which can be directly applicable to Java programs. This paper tries to extend spatial complexity measures proposed in [5] by defining spatial complexity measures especially for Java programs. Although C++ and Java both are object-oriented languages, still in many aspects Java programs completely differ from C++ programs e.g.…”

Section: Spatial Complexity Measures For Java Programsmentioning

confidence: 99%

“…Thus, spatial complexity of Java class is defined in terms ofspatial complexity of attributes and spatial complexity of methods. Next two sub-sections present the spatial complexity measure for attributes (which is similar to TCASC metric proposed in [5]) and spatial complexity measure for methods of Java class, which is defined as per Java environment.…”

Section: Spatial Complexity Of Java Classmentioning

confidence: 99%

“…If it is not there, then he looks for its definition in some other class present in some other file. Thus, the distance for that particular usage of the attribute is calculated as sum of distance of first usage of the attribute from top of the current file and distance of definition of the attribute from the top of the file containing definition [5]. In this way, by taking spatial complexities of all attributes of a class into consideration, Average spatial complexity of class attribute can be defined as:…”

Section: Spatial Complexity Of Java Classmentioning

confidence: 99%

See 2 more Smart Citations

Towards Spatial Complexity Measures for Comprehension of Java Programs

Chhabra

Gupta

2006

2006 International Conference on Advanced Computing and Communications

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The software comprehension is an important activity that influences a variety of software engineering tasks. Software comprehension is required when a software engineer maintains, reuses, and reengineers software systems. In order to understand a program, we need to look at human factors involved in the comprehension process. Program comprehension is a complex cognitive skill, which requires understanding of spatial orientations of the program entities. These spatial orientations of the program entities give rise to the spatial complexity of program. Various spatial complexity measures have been proposed to characterize the difficulty of understanding programs. This paper tries to extend these measures especially for the comprehension of Java programs. This paper identifies two spatial complexity measures for Java programs, which are based on classes and objects. The proposed measures have been applied to 10 different software projects developed using Java and the results obtained, have been used to draw a number of conclusions.

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Evaluation of Code and Data Spatial Complexity Measures

Chhabra

Gupta

2009

Communications in Computer and Information Science

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Measurement of object-oriented software spatial complexity

Cited by 21 publications

References 33 publications

Research and Measurement of Software Complexity Based on Wuli, Shili, Renli (WSR) and Information Entropy

Research and Measurement of Software Complexity Based on Wuli, Shili, Renli (WSR) and Information Entropy

Towards Spatial Complexity Measures for Comprehension of Java Programs

Evaluation of Code and Data Spatial Complexity Measures

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