Abstract—Recently, evolutionary computing is gaining more
interest from software engineering community for using it to
solve various types of related problems. The software metrics
selection problem is among the problems implemented using
this technique. For the problem to be implemented using this
method, the initial process called representation should be
established. Currently, the conversion of the problem into
binary representation is done using human experts. However,
experts’ opinions in categorizing the defect and non-defect
prone classes into bits are always questionable due to human
weakness. This paper presents metrics thresholds encoding
algorithm as an alternative to replace human experts in
developing problem representation. Algorithm was tested to
metric selection problem using Genetic Algorithm and the
results obtained are promising.
Index Terms—Genetic algorithm, software metrics, software
metrics thresholds, evolutionary computation, and
representation.
Abubakar D. Bakar, Abu Bakar Md. Sultan, Hazura Zulzalil, and Jamilah
Din are with the System Department, Faculty of Computer Science and
Information Technology, University Putra Malaysia, 43400 Serdang,
Selangor, Malaysia (e-mail: abakar@upm.edu.my).
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Cite: Abubakar D. Bakar, Abu Bakar Md. Sultan, Hazura Zulzalil, and Jamilah Din, "Metric’s Thresholds for Encoding Evolutionary Computing Representation in Software Engineering Problem," Lecture Notes on Software Engineering vol. 3, no. 1, pp. 22-25, 2015.