Since the dawn of programming, several developments in programming language design and programming methodology have been hailed as the end of the profession of programmer;they have all proven to be exaggerated rumors,...
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Since the dawn of programming, several developments in programming language design and programming methodology have been hailed as the end of the profession of programmer;they have all proven to be exaggerated rumors, to echo the words attributed to Mark Twain. In this short paper, we ponder the question of whether the emergence of large language models finally realizes these prophecies? Also, we discuss why even if this prophecy is finally realized, it does not change the job of the researcher in programming.
Decision tables for real time process control logically present the solution to a problem and directly replace flowcharts. A decision table is a self-contained description of the solution to a complex decision problem...
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Decision tables for real time process control logically present the solution to a problem and directly replace flowcharts. A decision table is a self-contained description of the solution to a complex decision problem. It presents all pertinent variables, the rules for combining possible conditions, and actions desired. The power of a decision table is that format and programming are independent of the problem, and it is thereby possible to automate much of the manpower required to design, program, test, and document solutions to complex control problems.
Aimed at the question that goal programming is lack of modeling support and the automatic generation of model during the process of modeling, this paper systematically researches the modeling question of goal programm...
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ISBN:
(纸本)9781424412945
Aimed at the question that goal programming is lack of modeling support and the automatic generation of model during the process of modeling, this paper systematically researches the modeling question of goal programming using knowledge engineering, machine learning and such theories, and proposes the theoretical system of "practical questions - knowledgeable information model - knowledgeable mathematical model knowledgeable solution model". The study opens up the method of a knowledge-based model to solve goal programming questions. The research makes the application of goal programming step forward to the intelligent direction.
Features a computer program for integrated-circuit layout designing. Specifications of a cell layout design knowledge-based system called Talib; Functions of an automatic cell layout system; Types of task- specific kn...
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Features a computer program for integrated-circuit layout designing. Specifications of a cell layout design knowledge-based system called Talib; Functions of an automatic cell layout system; Types of task- specific knowledge of the Talib system.
The term software CAD suggests a design paradigm and supporting environment centering around wiring-diagram-like graphical representations of software structures which serve as a framework for both human reasoning and...
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The term software CAD suggests a design paradigm and supporting environment centering around wiring-diagram-like graphical representations of software structures which serve as a framework for both human reasoning and automated tools for analysis and code generation. The term revolutionary highlights the fact that adopting the approach in industry would have exactly that effect on the state of the practice. This paper has its roots in a research project at Carleton University, which developed an experimental software CAD environment called the Carleton embedded system design environment (CAEDE), oriented toward embedded systems and Ada, to provide a demonstration of the concept and to serve as a research testbed. The major contribution of CAEDE presented in this paper is a demonstration of a visual paradigm which combines semantic depth and syntactic shallowness, relative to Ada, in a manner that makes it possible for the embedded system designer to work in terms of abstract machines while still 'thinking Ada.' A secondary contribution is the identification of Prolog as a promising approach for supporting tool development in an environment which supports the visual paradigm. We also describe experimental tools for temporal analysis, performance analysis, and the generation of skeleton Ada code; however, details are left for future papers. [ABSTRACT FROM AUTHOR]
Currently, most robot programming is done either by manual programming or using a teach pendant as part of the ''teach-by-showing'' method. Both of these methods have been found to have several drawbac...
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Currently, most robot programming is done either by manual programming or using a teach pendant as part of the ''teach-by-showing'' method. Both of these methods have been found to have several drawbacks. We are developing a novel method with which to program a robot: the assembly-plan-from-observation (APO) method. The APO method aims to build a system that has the capability of observing a human performing an assembly task, understanding the task based on the observation, and subsequently generating a robot program to achieve the same task. This paper focuses on the task recognition module (TRM), the main component of a complete APO system. The TRM recognizes object configurations before and after an assembly task, detects a configuration transition, and infers the assembly task that causes such a configuration transition. We assume that each assembly task aims to achieve a face contact relation between an object that has just been manipulated and stationary environmental objects. We prepare abstract task models that associate transitions of face contact relations with assembly tasks that achieve such transitions. Next, we implement TRM in order to verify two issues: 1) that such a contact transition can be recovered from the output of the object recognizer, and 2) that given these relation transitions, it is possible to use the abstract task models to effect the generation of robot motion commands;the execution of these commands will culminate in a repetition on the original assembly task.
Prolog program synthesis can be made more efficient by using schemata which capture similarities in previously-seen programs. Such schemata narrow the search involved in the synthesis of a new program. We define a gen...
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Prolog program synthesis can be made more efficient by using schemata which capture similarities in previously-seen programs. Such schemata narrow the search involved in the synthesis of a new program. We define a generalization operator for forming schemata from programs and a downward refinement operator for constructing programs from schemata. These operators define schema-hierarchy graphs which can be used to aid in the synthesis of new programs. Algorithms are presented for efficiently obtaining least generalizations of schemata, for adding new schemata to a schema-hierarchy graph, and for using schemata to construct new programs. (C) 1998 Elsevier Science B.V.
Data transformation is a laborious and time-consuming task for analysts. programming by example (PBE) is a technique that can simplify this difficult task for data analysts by automatically generating programs for dat...
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Data transformation is a laborious and time-consuming task for analysts. programming by example (PBE) is a technique that can simplify this difficult task for data analysts by automatically generating programs for data transformation. Most of the previously proposed PBE methods are based on search algorithms, but recent improvements in machine learning (ML) have led to its application in PBE research. For example, RobustFill was proposed as an ML-based PBE method for string transformation by using long short-term memory (LSTM) as the sequential encoder-decoder model. However, an ML-based PBE method has not been developed for tabular transformations, which are used frequently in data analysis. Thus, in the present study, we propose an ML-based PBE method for tabular transformations. First, we consider the features of tabular transformations, which are more complex and data intensive than string transformations, and propose a new ML-based PBE method using the state-of-the-art Transformer sequential encoder-decoder model. To our knowledge, this is the first ML-based PBE method for tabular transformations. We also propose two decoding methods comprising multistep beam search and program validation-beam search, which are optimized for program generation, and thus generate correct programs with higher accuracy. Our evaluation results demonstrated that the Transformer-based PBE model performed much better than LSTM-based PBE when applied to tabular transformations. Furthermore, the Transformer-based model with the proposed decoding method performed better than the conventional PBE model using the search-based method.
Metaheuristics are an effective and diverse class of optimization algorithms: a means of obtaining solutions of acceptable quality for otherwise intractable problems. The selection, construction, and configuration of ...
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Metaheuristics are an effective and diverse class of optimization algorithms: a means of obtaining solutions of acceptable quality for otherwise intractable problems. The selection, construction, and configuration of a metaheuristic for a given problem has historically been a manually intensive process based on experience, experimentation, and reasoning by metaphor. More recently, there has been interest in automating the process of algorithm configuration. In this article, we identify shared state as an inhibitor of progress for such automation. To solve this problem, we introduce the Automated Open-Closed Principle (AOCP), which stipulates design requirements for unintrusive reuse of algorithm frameworks and automated assembly of algorithms from an extensible palette of components. We demonstrate how the AOCP enables a greater degree of automation than previously possible via an example implementation.
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