automatic programming assessment has recently become an important method in assisting lecturers and instructors of programming courses to automatically mark and grade students' programming exercises as well as to ...
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automatic programming consists not only of an automatic compiler, but also some means of acquiring the high-level specification to be compiled, some means of determining that it is the intended specification, and some...
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automatic programming consists not only of an automatic compiler, but also some means of acquiring the high-level specification to be compiled, some means of determining that it is the intended specification, and some (interactive) means of translating this high-level specification into a lower-level one which can be automatically compiled.
Recently, automatic programming approaches have attracted great deal of interest aiming to utilize search techniques to find out optimal programs in various problems. Genetic programming is the most commonly explored ...
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Recently, automatic programming approaches have attracted great deal of interest aiming to utilize search techniques to find out optimal programs in various problems. Genetic programming is the most commonly explored automatic programming technique which uses genetic algorithm to evolve and discover programs with the tree structure. Herein, we focus on a new gravitational search algorithm (GSA)-based technique to create computer programs, automatically. This method is called gravitational search programming (GSP). Using GSA, the approach of generating the tree structure and insertion of internal nodes has been explained in detail. The GSP has been employed to the symbolic regression (SR) and the problem of feature construction (FC) that are widely used as a mathematical expression fitting to a given set of data points, and a data preprocessing technique for classification, respectively. The proficiency of the proposed algorithm has been evaluated and compared with the well-known automatic programming algorithms as well as C4.5 decision tree classifier. The results have been obtained over ten typical functions and 13 diverse datasets. The obtained results prove the effectiveness of the proposed method in achieving improved accuracy values in comparison to those of competing algorithms.
Online platforms to learn programming are very popular nowadays. These platforms must automatically assess codes submitted by the learners and must provide good quality feedbacks in order to support their learning. Cl...
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作者：
SCHMITT, MINRIA
Domaine de Voluceau-Rocquencourt BP 105 78153 Le Chesnay Cedex France
This paper presents an automatic programming system within the mathematical morphological framework. After structuring the set of the morphological transformations,we show how we can automatically choose the component...
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This paper presents an automatic programming system within the mathematical morphological framework. After structuring the set of the morphological transformations,we show how we can automatically choose the components of the high-level primitives and their chaining by means of geometric reasoning. Im Rahmen der mathematischen Morphologie wird ein automatisches Programmierungs System dargestellt. Nachdem wir die Menge der Transformationen der mathematischen Morphologie strukturiert haben, zeigen wir wie die Komponenten der höheren Primitiven gewählt wurden, und wie sie dann in einer geometrischen Gedankenführung aneinander verknüpft werden. Nous présentons ici un système de programmation automatique qui prend pour cadre la Morphologie Mathématique. Après avoir structuré l'ensemble des transformations morphologiques, nous montrons comment choisir automatiquement les primitives d'ordre supérieur et comment les chaîner par un raisonnement de type géométrique.
In a computational medical model, diagnosis is the classification of disease status in the terms of abnormal or positive, normal or negative or intermediate stages. Different Machine learning techniques such as artifi...
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In a computational medical model, diagnosis is the classification of disease status in the terms of abnormal or positive, normal or negative or intermediate stages. Different Machine learning techniques such as artificial neural networks (ANNs) are extensively and successfully used in disease diagnosis. However, there is no single classifier that can solve all classification problems. Selecting an optimal classifier for a problem is difficult, and it has become a relevant subject in the area. This paper focuses on grammar-based automatic programming (GAP) to build optimized discriminant functions for medical data classification in any arbitrary language. These techniques have an implicit power of automatic feature selection and feature extraction. This work carries out an in-depth investigation of the use of different GAP algorithms in the medical data classification problem. The objective is to identify the benefits and limitations of algorithms of this nature in the current problem. Classical classifiers were also considered for comparison purposes. Fourteen medical data sets were used in the experiments, and seven performance measures such as accuracy, sensitivity, specificity, precision, geometric-mean, F-measure, and false-positive rate are used to evaluate the performance of the produced classifier. The multiple criteria decision analysis (MCDA) demonstrates that GAP approaches are able to produce suitable classifiers for a given problem, and the GS performs better than other classical classifiers in medical data classification.
Domain knowledge is crucial to an automatic programming system and the interaction between domain knowledge and programming at the current time. The NIX project at Schlumberger-Doll Research has been investigating thi...
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Domain knowledge is crucial to an automatic programming system and the interaction between domain knowledge and programming at the current time. The NIX project at Schlumberger-Doll Research has been investigating this issue in the context of two application domains related to oil well logging. Based on these experiments we have developed a framework for domain-specific automatic programming. Within the framework, programming is modeled in terms of two activities, formalization and implementation, each of which transforms descriptions of the program as it proceeds through intermediate states of development. The activities and transformations may be used to characterize the interaction of programming knowledge and domain knowledge in an automatic programming system.
Since the 1970s the goal of generating programs in an automatic way (i.e., automatic programming) has been sought. A user would just define what he expects from the program (i.e., the requirements), and it should be a...
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Since the 1970s the goal of generating programs in an automatic way (i.e., automatic programming) has been sought. A user would just define what he expects from the program (i.e., the requirements), and it should be automatically generated by the computer without the help of any programmer. Unfortunately, this task is much harder than expected. Although transformation methods are usually employed to address this problem, they cannot be employed if the gap between the specification and the actual implementation is too wide. In this paper we introduce a novel conceptual framework for evolving programs from their specification. We Use genetic programming to evolve the programs, and at the same time we exploit the specification to co-evolve sets of unit tests. Programs are rewarded by how many tests they do not fail, whereas the unit tests are rewarded by how many programs they make to fail. We present and analyse seven different problems on which this novel technique is successfully applied. (C) 2009 Elsevier Inc. All rights reserved.
automatic programming is a branch of artificial intelligence that presents each solution as a mathematical formula based on heuristic mechanisms. In this study, artificial bee colony expression programming (ABCEP) is ...
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automatic programming is a branch of artificial intelligence that presents each solution as a mathematical formula based on heuristic mechanisms. In this study, artificial bee colony expression programming (ABCEP) is presented, which is combined simultaneously with expression programming. By using expression sharing to generate new solutions, the proposed method can minimize certain deficiencies of artificial bee colony programming, such as weak convergence and high locality. A total number of 15 real-world regression benchmark functions was used to evaluate the performance of the proposed model. For comparison purposes, successful run percentage, mean best cost, convergence performance, and run time of ABCEP were compared to those of other tested automatic programming algorithms, including artificial bee colony programming, gene expression programming, genetic programming, and quick artificial bee colony programming. A Wilcoxon signed-rank test was also done to compare the behavior of the algorithms. Additionally, the accuracy of all algorithms was then evaluated using three real-world practical benchmarks. The results indicate that the predictions generated by ABCEP are better than those obtained by other control algorithms based on successful runs, mean fitness values, and convergence rate. (C) 2020 Elsevier Inc. All rights reserved.
Geometric information is important for automatic programming of arc welding robot. Complete geometric models of robotic arc welding are established in this paper. In the geometric model of weld seam, an equation with ...
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Geometric information is important for automatic programming of arc welding robot. Complete geometric models of robotic arc welding are established in this paper. In the geometric model of weld seam, an equation with seam length as its parameter is introduced to represent any weld seam. The method to determine discrete programming points on a weld seam is presented. In the geometric model of weld workpiece, three class primitives and CSG tree are used to describe weld workpiece. Detailed data structure is presented. In pose transformation of torch, world frame, torch frame and active frame are defined, and transformation between frames is presented. Based on these geometric models, an automatic programming software package for robotic arc welding, RAWCAD, is developed. Experiments show that the geometric models are practical and reliable.
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