High order mutation analysis of a software engineering benchmark, including schema and local optima networks, suggests program improvements may not be as hard to find as is often assumed. (1) Bit-wise genetic building blocks are not deceptive and can lead to all global optima. (2) There are many neutral networks, plateaux and local optima, nevertheless in most cases near the human written C source code there are hill climbing routes including neutral moves to solutions
Search Based Software Engineering techniques are emerging as important tools for software maintenanc...
Context: Search-based techniques have been applied to almost all areas in software engineering, espe...
We re-examine the central motivation behind Genetic Improvement Programming (GIP), and argue that t...
High order mutation analysis of a software engineering benchmark, including schema and local optima ...
Local optima networks are a compact representation of the global structure of a search space. They c...
Trying all hopeful high order mutations to source code shows none of the first order schema of trian...
Genetic improvement uses automated search to improve existing software. It has been successfully use...
Genetic Improvement (GI) uses automated search to improve existing software. Most GI work has focuse...
Genetic Improvement (GI) uses automated search to improve existing software. Most GI work has focuse...
Automatic Programming has long been a sub-goal of Artificial Intelligence (AI). It is feasible in li...
The search landscape is a common metaphor to describe the structure of computational search spaces. ...
We sample the genetic programming tree search space and show it is smooth, since many mutations on m...
Genetic Programming is an evolutionary computation technique which searches for those computer progr...
Genetic improvement uses automated search to find improved versions of existing software. We present...
Trying all simple changes (first order mutations) to executed source code shows software engineering...
Search Based Software Engineering techniques are emerging as important tools for software maintenanc...
Context: Search-based techniques have been applied to almost all areas in software engineering, espe...
We re-examine the central motivation behind Genetic Improvement Programming (GIP), and argue that t...
High order mutation analysis of a software engineering benchmark, including schema and local optima ...
Local optima networks are a compact representation of the global structure of a search space. They c...
Trying all hopeful high order mutations to source code shows none of the first order schema of trian...
Genetic improvement uses automated search to improve existing software. It has been successfully use...
Genetic Improvement (GI) uses automated search to improve existing software. Most GI work has focuse...
Genetic Improvement (GI) uses automated search to improve existing software. Most GI work has focuse...
Automatic Programming has long been a sub-goal of Artificial Intelligence (AI). It is feasible in li...
The search landscape is a common metaphor to describe the structure of computational search spaces. ...
We sample the genetic programming tree search space and show it is smooth, since many mutations on m...
Genetic Programming is an evolutionary computation technique which searches for those computer progr...
Genetic improvement uses automated search to find improved versions of existing software. We present...
Trying all simple changes (first order mutations) to executed source code shows software engineering...
Search Based Software Engineering techniques are emerging as important tools for software maintenanc...
Context: Search-based techniques have been applied to almost all areas in software engineering, espe...
We re-examine the central motivation behind Genetic Improvement Programming (GIP), and argue that t...