Completed Plants, Animals & Ecology Computing & AI

Evolving Program Improvement Collaborators

Summary

Original abstract (not yet simplified)

EPIC will automatically construct Evolutionary Program Improvement Collaborators (called Epi-Collaborators) that suggest code changes that improve software according to multiple functional and non-functional objectives. The Epi-Collaborator suggestions will include transplantation of code from a donor system to a host, grafting of entirely new features `grown' (evolved) by the Epi-Collaborator, and identification and optimisation of tuneable `deep' parameters (that were previously...

View original technical description
EPIC will automatically construct Evolutionary Program Improvement Collaborators (called Epi-Collaborators) that suggest code changes that improve software according to multiple functional and non-functional objectives. The Epi-Collaborator suggestions will include transplantation of code from a donor system to a host, grafting of entirely new features `grown' (evolved) by the Epi-Collaborator, and identification and optimisation of tuneable `deep' parameters (that were previously unexposed and therefore unexploited).A key feature of the EPIC approach is that all of these suggestions will be underpinned by automatically-constructed quantitative evidence that justifies, explains and documents improvements. EPIC aims to introduce a new way of developing software, as a collaboration between human and machine, exploiting the complementary strengths of each; the human has domain and contextual insights, while the machine has the ability to intelligently search large search spaces. The EPIC approach directly tackles the emergent challenges of multiplicity: optimising for multiple competing and conflicting objectives and platforms with multiple software versions.Keywords:Search Based Software Engineering (SBSE),Evolutionary Computing,Software Testing,Genetic Algorithms,Genetic Programming.

Related Research

Grants with similar aims, by meaning.

Evidence-based Practices Informing Computing (EPIC)
GGGP: Grow and Graft Genetic Programming
Graph Transformation and Evolutionary Computation
EVO-ENGINE: A directed evolution engine for engineering proteins and logic gates
Evolving the adjacent possible for engineering design

Original classification

H2020

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