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
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...
Genetic improvement uses automated search to find improved versions of existing software. We present...
High order mutation analysis of a software engineering benchmark, including schema and local optima ...
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...
The search landscape is a common metaphor to describe the structure of computational search spaces. ...
Genetic Programming is an evolutionary computation technique which searches for those computer progr...
We sample the genetic programming tree search space and show it is smooth, since many mutations on m...
Automatic Programming has long been a sub-goal of Artificial Intelligence (AI). It is feasible in li...
Context: Search-based techniques have been applied to almost all areas in software engineering, espe...
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...
Genetic improvement uses automated search to find improved versions of existing software. We present...
High order mutation analysis of a software engineering benchmark, including schema and local optima ...
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...
The search landscape is a common metaphor to describe the structure of computational search spaces. ...
Genetic Programming is an evolutionary computation technique which searches for those computer progr...
We sample the genetic programming tree search space and show it is smooth, since many mutations on m...
Automatic Programming has long been a sub-goal of Artificial Intelligence (AI). It is feasible in li...
Context: Search-based techniques have been applied to almost all areas in software engineering, espe...
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...
Genetic improvement uses automated search to find improved versions of existing software. We present...