A Genetic Framework Model For Self-Adaptive Software
This work addresses a specific challenge in self-adaptive software for researchers, but it is incremental as it builds on existing bio-inspired approaches.
The paper tackled the problem of self-adaptive software by proposing a framework that integrates both external behavior and genetic material, addressing a gap in bio-inspired research, but it is limited to predicted events with non-predicted events remaining a challenge.
Lots of bio-inspired research works have been conducted in self-adaptive software. They have focused on the external behavior of biological entities without their genetic material that causes this behavior and constitutes the challenge this work dealt with. This paper propose a framework integrating both the external behavior and the genetics material. This framework is limited to predicted events. the non-predicted events are still a challenge.