%0 Journal Article
	%A Benjapol Auprasert and  Yachai Limpiyakorn
	%D 2008
	%J International Journal of Computer and Systems Engineering
	%B World Academy of Science, Engineering and Technology
	%I Open Science Index 21, 2008
	%T Underlying Cognitive Complexity Measure Computation with Combinatorial Rules
	%U https://publications.waset.org/pdf/11564
	%V 21
	%X Measuring the complexity of software has been an
insoluble problem in software engineering. Complexity measures can
be used to predict critical information about testability, reliability,
and maintainability of software systems from automatic analysis of
the source code. During the past few years, many complexity
measures have been invented based on the emerging Cognitive
Informatics discipline. These software complexity measures,
including cognitive functional size, lend themselves to the approach
of the total cognitive weights of basic control structures such as loops
and branches. This paper shows that the current existing calculation
method can generate different results that are algebraically
equivalence. However, analysis of the combinatorial meanings of this
calculation method shows significant flaw of the measure, which also
explains why it does not satisfy Weyuker's properties. Based on the
findings, improvement directions, such as measures fusion, and
cumulative variable counting scheme are suggested to enhance the
effectiveness of cognitive complexity measures.
	%P 3026 - 3031