Search results for "programming."
showing 10 items of 3035 documents
Some models of inductive syntactical synthesis from sample computations
2005
The paper is a survey of several models of inductive program synthesis from sample computations. Synthesis tools are basically syntactical: the synthesis is based on the detection of "regular" fragments related with "shuffled" arithmetical progressions. Input sample computations are supposed to be "representative": they have to "reflect" all loops occurring in the target program. Programs are synthesized in nontraditional form of "generalized" regular expressions having Cleene stars and unions for loops and CASE-like operators. However, if input samples are somehow "annotated" (we consider two different approaches), then loops can be synthesized in more traditional WHILE-form, where loop co…
Gradation of Fuzzy Preconcept Lattices
2021
Noticing certain limitations of concept lattices in the fuzzy context, especially in view of their practical applications, in this paper, we propose a more general approach based on what we call graded fuzzy preconcept lattices. We believe that this approach is more adequate for dealing with fuzzy information then the one based on fuzzy concept lattices. We consider two possible gradation methods of fuzzy preconcept lattice—an inner one, called D-gradation and an outer one, called M-gradation, study their properties, and illustrate by a series of examples, in particular, of practical nature.
Multiple SIP strategies and bottom-up adorning in logic query optimization
1990
Preprocessing methods called “readorning” and “bottom-up adorning” are introduced as means of enlarging the application domain of magic sets and related query optimization strategies for logic databases. Readorning tries to make possible the simultaneous use of multiple sideways information passing (sip) strategies defined for a rule, thus yielding an optimization effect that may not be achieved by any particular choice of sip strategies. Bottom-up adorning is used to make magic sets applicable to cases in which potential optimizations can be derived from bindings coming upwards from rule bodies to rule heads in bottom-up evaluation. These include the cases in which we know that some base r…
Recursive modeling for completed code generation
2009
Model-Driven Development is promising to software development because it can reduce the complexity and cost of developing large software systems. The basic idea is the use of different kinds of models during the software development process, transformations between them, and automatic code generation at the end of the development. But unlike the structural parts, fully-automated code generation from the behavior parts is still hard, if it works at all, restricted to specific application areas using a domain specific language, DSL.This paper proposes an approach to model the behavior parts of a system and to embed them into the structural models. The underlying idea is recursive refinements …
Challenges of Program Synthesis with Grammatical Evolution
2020
Program synthesis is an emerging research topic in the field of EC with the potential to improve real-world software development. Grammar-guided approaches like GE are suitable for program synthesis as they can express common programming languages with their required properties. This work uses common software metrics (lines of code, McCabe metric, size and depth of the abstract syntax tree) for an analysis of GE’s search behavior and the resulting problem structure. We find that GE is not able to solve program synthesis problems, where correct solutions have higher values of the McCabe metric (which means they require conditions or loops). Since small mutations of high-quality solutions str…
Diagrammatic approach to cellular automata and the emergence of form with inner structure
2018
We present a diagrammatic method to build up sophisticated cellular automata (CAs) as models of complex physical systems. The diagrams complement the mathematical approach to CA modeling, whose details are also presented here, and allow CAs in rule space to be classified according to their hierarchy of layers. Since the method is valid for any discrete operator and only depends on the alphabet size, the resulting conclusions, of general validity, apply to CAs in any dimension or order in time, arbitrary neighborhood ranges and topology. We provide several examples of the method, illustrating how it can be applied to the mathematical modeling of the emergence of order out of disorder. Specif…
Researching Conditional Probability Problem Solving
2014
The chapter is organized into two parts. In the first one, the main protagonist is the conditional probability problem. We show a theoretical study about conditional probability problems, identifying a particular family of problems we call ternary problems of conditional probability. We define the notions of Level, Category and Type of a problem in order to classify them into sub-families and in order to study them better. We also offer a tool we call trinomial graph that functions as a generative model for this family of problems. We show the syntax of the model that allows researchers and teachers to translate a problem in terms of the trinomial graphs language, and the consequences of th…
Multi-Dimensional motivic pattern extraction founded on adaptive redundancy filtering
2005
Abstract We present a computational model for discovering repeated patterns in symbolic representations of monodic music. Patterns are discovered through an incremental adaptive identification along a multi-dimensional parametric space. The difficulties of pattern discovery mainly come from combinatorial redundancies, that our model is able to control efficiently. A specificity relation is defined between pattern descriptions, unifying suffix and inclusion relations and enabling a filtering of redundant descriptions. Combinatorial proliferation caused by successive repetitions of patterns is managed using cyclic patterns. The modelling of these redundancy control mechanisms enables an autom…
Representations for evolutionary algorithms
2015
Successful and efficient use of evolutionary algorithms (EA) depends on the choice of the genotype, the problem representation (mapping from genotype to phenotype) and on the choice of search operators that are applied to the genotypes. These choices cannot be made independently of each other. The question whether a certain representation leads to better performing EAs than an alternative representation can only be answered when the operators applied are taken into consideration. The reverse is also true: deciding between alternative operators is only meaningful for a given representation. In EA practice one can distinguish two complementary approaches. The first approach uses indirect repr…
High Locality Representations for Automated Programming
2011
We study the locality of the genotype-phenotype mapping used in grammatical evolution (GE). GE is a variant of genetic programming that can evolve complete programs in an arbitrary language using a variable-length binary string. In contrast to standard GP, which applies search operators directly to phenotypes, GE uses an additional mapping and applies search operators to binary genotypes. Therefore, there is a large semantic gap between genotypes (binary strings) and phenotypes (programs or expressions). The case study shows that the mapping used in GE has low locality leading to low performance of standard mutation operators. The study at hand is an example of how basic design principles o…