Digital Technologies Research and Applications

Article

Programming Techniques for Considering m Desired Conditions from n Possible Conditions

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https://doi.org/10.54963/dtra.v1i2.81
Riyana, S., Homdoung, N., & Sasujit, K. (2022). Programming Techniques for Considering m Desired Conditions from n Possible Conditions. Digital Technologies Research and Applications, 1(2), 89–95. https://doi.org/10.54963/dtra.v1i2.81
Volume 1 Issue 2: September 2022
Copyright (c) 2022 The author(s)
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Authors

  • Surapon Riyana
    Maejo University, Sansai, Chiangmai, 50290, Thailand
  • Nigran Homdoung Maejo University, Sansai, Chiangmai, 50290, Thailand; School of Renewable Energy, Maejo University, Sansai, Chiangmai, 50290, Thailand
  • Kittikorn Sasujit Maejo University, Sansai, Chiangmai, 50290, Thailand; School of Renewable Energy, Maejo University, Sansai, Chiangmai, 50290, Thailand

The performance of computer programs (or the hardware that can be programmed such as IoTs, embedded computers, and PLCs) is generally based on the complexity of the particular program development technique. High complexity often uses more execution times and system resources. For this reason, the computer program is less computational complexity to be desired. The conditional statements tell computers what certain information is a major cause of computer program complexities, e.g., considering m desired conditions from n possible conditions. To achieve this aim in computer programs, the data combination is often utilized. However, it is high complexity. Moreover, they cannot give that one condition takes precedence over others. To rid these vulnerabilities of combined conditions, a simple programming technique for considering m desired conditions from n possible conditions is proposed in this work, which is based on the summation of the condition weights. It only has the complexity of search spaces and data constructions to be O(n) and each condition can be set to be different precedence from the others. Furthermore, the proposed technique is evaluated by extensive experiments. From the experimental results, they indicate that the proposed technique is more effective and efficient than the comparative technique.

Keywords:

Condition weights Weighted summations Data combinations Data considerations Programming techniques

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