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“Exploration and exploitation are the two cornerstones of problem solving by search.” For more than a decade, Eiben and Schippers' advocacy for balancing between these two antagonistic cornerstones still greatly influences the research directions of evolutionary algorithms (EAs) [1998]. This article revisits nearly 100 existing works and surveys(More)
Many domain-specific languages, that try to bring feasible alternatives for existing solutions while simplifying programming work, have come up in recent years. Although, these little languages seem to be easy to use, there is an open issue whether they bring advantages in comparison to the application libraries, which are the most commonly used(More)
The paper discusses context-free grammar (CFG) inference using genetic-programming with application to inducing grammars from programs written in simple domain-specific languages. Grammar-specific heuristic operators and non-random construction of the initial population are proposed to achieve this task. Suitability of the approach is shown by small(More)
Extracting grammar from programs attracts researchers from several fields such as software engineering, pattern recognition, computational linguistic and natural language acquisition. So far, only regular grammar induction has been successful, while purposeful context-free grammar induction is still elusive. We discuss the search space of context-free(More)
Grammar metrics have been introduced to measure the quality and the complexity of the formal grammars. The aim of this paper is to explore the meaning of these notions and to experiment, on several grammars of domain specific languages and of general-purpose languages, existing grammar metrics together with the new metrics that are based on grammar LR(More)
While grammar inference is used in areas like natural language acquisition, syntactic pattern recognition, etc., its application to the programming language problem domain has been limited. We propose a new application area for grammar induction which intends to make domain-specific language development easier and finds a second application in renovation(More)
The null hypothesis significance testing (NHST) is of utmost importance for comparing evolutionary algorithms as the performance of one algorithm over another can be scientifically proven. However, NHST is often misused, improperly applied and misinterpreted. In order to avoid the pitfalls of NHST usage this paper proposes a new method, a Chess Rating(More)