International Journal of Computer Science & Network Security

International Journal of Computer Science & Network Security (국제컴퓨터통신보호논문지학회)
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Prioritization-Based Model for Effective Adoption of Mobile Refactoring Techniques

  • Received : 2021.12.05
  • Published : 2021.12.30
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Abstract

The paper introduces a model for evaluating and prioritizing mobile quality attributes and refactoring techniques through the examination of their effectiveness during the mobile application development process. The astonishing evolution of software and hardware has increased the demand for techniques and best practices to overcome the many challenges related to mobile devices, such as those concerning device storage, network bandwidth, and energy consumption. A number of studies have investigated the influence of refactoring, leading to the enhancement of mobile applications and the overcoming of code issues as well as hardware issues. Furthermore, rapid and continuous mobile developments make it necessary for teams to apply effective techniques to produce reliable mobile applications and reduce time to market. Thus, we investigated the influence of various refactoring techniques on mobile applications to understand their effectiveness in terms of quality attributes. First, we extracted the most important mobile refactoring techniques and a set of quality attributes from the literature. Then, mobile application developers from nine mobile application teams were recruited to evaluate and prioritize these quality attributes and refactoring techniques for their projects. A prioritization-based model is examined that integrates the lightweight multi-criteria decision making method, called the best-worst method, with the process of refactoring within mobile applications. The results prove the applicability and suitability of adopting the model for the mobile development process in order to expedite application production while using well-defined procedures to select the best refactoring techniques. Finally, a variety of quality attributes are shown to be influenced by the adoption of various refactoring techniques.

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References

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