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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The term 'automatic programming' has been initially used to describe early FORTRAN compilers. The present paper is organized into sections corresponding to each of the three components of the extended automati...
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The term 'automatic programming' has been initially used to describe early FORTRAN compilers. The present paper is organized into sections corresponding to each of the three components of the extended automatic programming problem, taking into account specification acquisition, interactive translation, and automatic compilation. The simple notion of an automatic compiler is incrementally elaborated into a paradigm for automated software development. The obtained paradigm, even without full automation, eliminates two fundamental flaws in the current paradigm. A description is provided of a wide variety of research which was undertaken in support of the new paradigm, giving attention to successes and failures. (G.R.)
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.
Domain knowledge is vital to an automatic programming system and to the interaction between domain knowledge and programming. The phi-nix project at Schlumberger-Doll Research has explored this issue in the context of...
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Domain knowledge is vital to an automatic programming system and to the interaction between domain knowledge and programming. The phi-nix project at Schlumberger-Doll Research has explored this issue in the context of 2 application domains related to oil well logging -- interpretation and tool software. The current key research issues in automatic programming are: 1. how domain knowledge should be represented for use by an automatic programming system, and 2. how domain knowledge and programming knowledge interact during the programming process. A framework is developed for domain-specific automatic programming that provides preliminary answers to these questions. Within this framework, programming is modeled in terms of formalization and implementation; each of these activities transforms descriptions of the program as it proceeds through intermediate states of development. The activities and transformations may be employed to characterize the interaction of programming knowledge and domain knowledge in an automatic programming system.
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.
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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In previous papers [Comput. Methods Appl. Mech. Eng. 132 (1996) 277-304, 259-276;154 (1998) 41-68], the authors have presented the main ideas, which have led to the creation of an environment for symbolic derivations ...
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In previous papers [Comput. Methods Appl. Mech. Eng. 132 (1996) 277-304, 259-276;154 (1998) 41-68], the authors have presented the main ideas, which have led to the creation of an environment for symbolic derivations of variational problems and automatic programming of finite elements codes. In these papers, only linear formulations were treated, e.g., Galerkin formulation for elastodynamics [Adv. Eng. Soft. 27 (1996) 3-10] or Galerkin least-squares (GLS) formulation of Stokes flow problem. In this paper, we wish to show a natural extension of symbolic derivation concepts to nonlinear formulations, using the general notion of directional derivative. The application to the numerical solution of Navier-Stokes equations is given. (C) 2001 Elsevier Science B.V. All rights reserved.
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.
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.
This paper proposes an automatic structural programming system. Genetic programming achieves success for automatic programming using the evolutionary process. However, the approach doesn't deal with the essential ...
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This paper proposes an automatic structural programming system. Genetic programming achieves success for automatic programming using the evolutionary process. However, the approach doesn't deal with the essential program concept in the sense of what is called a program in software science. It is useful that a program be structured by various sub-structures, i.e. subroutines, however, the above-mentioned approach treats a single program as one sequence. As a result of the above problem, there is a lack of reusability, flexibility, and a decreases in the possibility of use as a utilitarian programming system. In order to realize a structural programming system, this paper proposes a method which can generate a program constructed by subroutines, named formula, using the evolutionary process.
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