International Journal on Science and Technology

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Continual-Learning Test Suites for Self-Evolving Software Systems

Author(s) Timothy Adepitan
Country Nigeria
Abstract Self-evolving software system is a paradigm shift in the way that autonomous applications are built, especially in fields such as robotics, self-driving vehicles and intelligent agents that must adapt to changing environments. These systems operate by learning continuously and being able to improve their performance through experiences and accumulated data. However, the dynamism of such systems presents major challenges for testing and evaluation, because the approaches were developed for static systems in mind and cannot take into account the current adaptation. This paper proposes the development of continual-learning test suites that are designed with the purpose of evaluating the self-evolving software systems. These test suites guarantee that systems are constantly being tested for their performance, safety and robustness as they adapt. This paper overviews the existing methodologies and discusses the need for dynamic test suites, and provides a framework for their design and implementation. By addressing the unique challenges of self-evolving systems, continual learning test suites are aimed at providing a practical and reliable way of testing dynamic and learning-based systems in real world applications.
Keywords Continual Learning, Self-Evolving Systems, Test Suites, Autonomous Systems, Software Testing, Machine Learning, Dynamic Environments, Robustness.
Field Engineering
Published In Volume 14, Issue 1, January-March 2023
Published On 2023-02-08
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