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ACM International Conference on Management of Data

作者： Jin, Zhongjun Anderson, Michael R. Cafarella, Michael Jagadish, H., V Univ Michigan Ann Arbor MI 48109 USA

ISBN: (纸本)9781450341974

Advancements in new data analysis and visualization technologies have resulted in wide applicability of data-driven decision making. However, raw data from various sources must be wrangled into a suitable form before they are processed by the downstream data tools. People traditionally write data transformation programs to automate this process, and such work is cumbersome and tedious. We built a system called FOOFAH for helping the user easily synthesize a desired data transformation program. Our system minimizes the user's effort by only asking for a small illustrative example comprised of the raw input data and the target transformed output;FOOFAH then synthesizes a program that can perform the desired data transformation. This demonstration showcases how the user can apply FOOFAH to real-world data transformation tasks.

关键词： Data Transformation Program Synthesis programming by example A* algorithm Heuristic

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EAGER. programming repetitive tasks by example

EAGER. Programming repetitive tasks by example

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Human Factors in Computing Systems - CHI'91

作者： Cypher, Allen Advanced Technology Group Apple Computer Inc. Cupertino CA 95014 United States

ISBN: (纸本)0201512785

Eager is a programming by example system for the HyperCard environment. It constantly monitors the user's activities, and when it detects an iterative pattern, it writes a program to complete the iteration. programming by example systems create generalized programs from examples provided by the user. They are faced with the problem of how to display these abstract procedures. Eager utilizes a new interface technique, called anticipation, to show how it has generalized: when it detects a repetitive activity, it highlights menus and objects on the screen to indicate what it expects the user to do next. As users continue to perform their activity, they will notice that the objects they are about to select have already been highlighted by the system. When it becomes apparent that Eager knows how to perform the task correctly, they can tell Eager to complete the task for them. The use of anticipation allows Eager to interfere minimally with the users' normal activities. © 1991 ACM.

关键词： Adaptive systems Agents Demonstrational interfaces Intelligent interfaces Models of user performance Programmer assistants programming by example User programming

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Program synthesis algorithm based on context consistency heuristic

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INTERNATIONAL JOURNAL OF MACHINE LEARNING AND CYBERNETICS 2024年第2期15卷 559-571页

作者： Dou, Quansheng Pan, Hao Tang, Huanling Jiang, Ping Wang, Huixian Shandong Technol & Business Univ Coll Comp Sci & Technol 191 Binhai Middle Rd Yantai 264005 Shandong Peoples R China Shandong Technol & Business Univ Coll Informat & Elect Engn 191 Binhai Middle Rd Yantai 264005 Shandong Peoples R China Kashi Univ Sch Comp Sci & Technol 29 Xueyuan Rd Kashi 844006 Xinjiang Peoples R China

programming-by-example (PBE) is a program synthesis technique that automatically synthesizes computer programs from input-output (I/O) examples. There are many approaches to program synthesis, and one of the most commonly used solutions is to perform a search over the space of programs. In this paper, we present a novel program synthesis algorithm based on context consistency heuristic (PSACC) that differs from previous heuristic methods. We consider the input-output example as a state and develop a deep neural network-based predictor called DHFnet. DHFnet has the ability to map the current state to the first two instructions of the program which achieves the current state. By considering the current state and its subsequent state obtained by executing the corresponding instruction, we design a context consistency-based search algorithm. Our search algorithm enables a more reasonable and efficient selection of instructions in the program, by judging whether the instructions maintain the context consistency between the current state and its subsequent state. Furthermore, under the same experimental and testing environments, PSACC successfully enhances the success rate of program synthesis by 2-5%, and reduces the synthesis time compared to the baseline method. PSACC also exhibits better synthesis efficiency in terms of comprehensive performance compared to existing program synthesis methods.

关键词： Program synthesis Search algorithm programming by example Context consistency heuristic

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Neural Network Approach to Program Synthesis for Tabular Transformation by example

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IEEE ACCESS 2022年 10卷 24864-24876页

作者： Ujibashi, Yoshifumi Takasu, Atsuhiro Grad Univ Adv Studies SOKENDAI Dept Informat Hayama Kanagawa 2400193 Japan Fujitsu Ltd Nakahara Ku Kawasaki Kanagawa 2118588 Japan Natl Inst Informat Chiyoda Ku Tokyo 1018430 Japan

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.

关键词： Task analysis Transformers Data integration Training Decoding Licenses Domain specific languages Automatic programming beam search LSTM neural network programming by example program synthesis tabular data transformer

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Integrating user interface agents with conventional applications

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KNOWLEDGE-BASED SYSTEMS 1998年第1期11卷 15-23页

作者： Lieberman, H MIT Media Lab Cambridge MA 02139 USA

In most experiments with user interface agents to date, it has been necessary either to implement both the agent and the application from scratch, or to modify the code of an existing application to enable the necessary communication. Instead, we would like to be able to 'attach' an agent to an existing application, while requiring only a minimum of advance planning on the part of the application developer. Commercial applications an increasingly supporting the use of 'application programmers' interfaces' and scripting languages as means of achieving external control of applications. Are these mechanisms sufficient for software agents to achieve communication with applications? This paper reports some preliminary experiments in developing agent software that works with existing, unmodified commercial applications and agents that work across multiple applications. We describe a programming by example agent, ScriptAgent, that uses a scripting language, Applescript, to record example procedures that are generalized by the agent. Another approach is examinability, where the application grants to the agent the right to examine internal data structures. We present another kind of learning agent, Tatlin, that compares successive application states to infer interface operations. Finally, we discuss broader systems issues such as parallelism, interface sharing between agent and application, and access to objects. (C) 1998 Published by Elsevier Science B.V. All rights reserved.

关键词： agents scripting languages programming by example programming by demonstration machine learning user interface

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Data Formulator: AI-Powered Concept-Driven Visualization Authoring

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IEEE TRANSACTIONS ON VISUALIZATION AND COMPUTER GRAPHICS 2024年第1期30卷 1128-1138页

作者： Wang, Chenglong Thompson, John Lee, Bongshin Microsoft Res Redmond WA 98052 USA

With most modern visualization tools, authors need to transform their data into tidy formats to create visualizations they want. Because this requires experience with programming or separate data processing tools, data transformation remains a barrier in visualization authoring. To address this challenge, we present a new visualization paradigm, concept binding, that separates high-level visualization intents and low-level data transformation steps, leveraging an AI agent. We realize this paradigm in Data Formulator, an interactive visualization authoring tool. With Data Formulator, authors first define data concepts they plan to visualize using natural languages or examples, and then bind them to visual channels. Data Formulator then dispatches its AI-agent to automatically transform the input data to surface these concepts and generate desired visualizations. When presenting the results (transformed table and output visualizations) from the AI agent, Data Formulator provides feedback to help authors inspect and understand them. A user study with 10 participants shows that participants could learn and use Data Formulator to create visualizations that involve challenging data transformations, and presents interesting future research directions.

关键词： Data visualization Temperature distribution Urban areas Visualization Transforms Histograms Libraries AI visualization authoring data transformation programming by example natural language large language model

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SOUNDNESS AND COMPLETENESS OF A SYNTHESIS ALGORITHM BASED ON example COMPUTATIONS

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JOURNAL OF THE ACM 1985年第2期32卷 249-279页

作者： BAUER, MA Univ. of Western Ontario London Ont. Canada

The problem of synthesizing a procedure from example computations is examined. An algorithm for this task is presented, and its success is considered. To do this, a model of procedures and example computations is introduced, and the class of acceptable examples is defined. The synthesis algorithm is shown to be successful, with respect to the model of procedures and examples, from two perspectives. First, it is shown to be sound, that is, that the procedure synthesized from a set of examples produces the same result as the intended one on the inputs used to generate that set of examples. Second, it is shown to be complete, that is, that for any procedure in the class of procedures, there exists a finite set of examples such that the procedure synthesized behaves as the intended one on all inputs for which the intended one halts.

关键词： programming by example

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Customization of Web applications through an intelligent environment exploiting logical interface descriptions

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INTERACTING WITH COMPUTERS 2008年第1期20卷 29-47页

作者： Macias, Jose A. Paterno, Fablo ISTI CNR I-56124 Pisa Italy

Customization of Web-based applications is often considered a designer skill rather than an end-user need. However, there is an ongoing shift to end-user-centred technology, and even users with poor or no skill in Web-based languages may feel the need to customize Web applications according to their preferences. Although Web authoring environments have an increasing number of features, the challenge of providing end-users with the ability to easily customize entire Web applications still remains unsolved. In this paper, we propose an intelligent approach to customizing Web-based applications. Customizations rules are automatically inferred by the system from changes that users supply as examples. They remain as long-term knowledge that can be applied to support future interactions, thus minimizing the amount of authoring that end-users need to do for this purpose. In order to better understand the implications of the user's modifications, they are analysed using the logical descriptions of the corresponding Web pages. (C) 2007 Elsevier B.V. All rights reserved.

关键词： human-computer interaction end-user development intelligent user interfaces programming by example model-based user interfaces web-based nomadic applications

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Providing end-user facilities to simplify ontology-driven web application authoring

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INTERACTING WITH COMPUTERS 2007年第4期19卷 563-585页

作者： Macias, Jose A. Castells, Pablo Univ Autonoma Madrid Dept Ingn Informat Escuela Politecn Super Madrid 28059 Spain

Generally speaking, emerging web-based technologies are mostly intended for professional developers. They pay poor attention to users who have no programming abilities but need to customize software applications. At some point, such needs force end-users to act as designers in various aspects of software authoring and development. Every day, more new computing-related professionals attempt to create and modify existing applications in order to customize web-based artifacts that will help them carry out their daily tasks. In general they are domain experts rather than skilled software designers, and new authoring mechanisms are needed in order that they can accomplish their tasks properly. The work we present is an effort to supply end-users with easy mechanisms for authoring web-based applications. To complement this effort, we present a user study showing that it is possible to carry out a trade-off between expressiveness and ease of use in order to provide end-users with authoring facilities. (C) 2007 Elsevier B.V. All rights reserved.

关键词： human-computer interaction model-based user interfaces end-user development intelligent user interfaces programming by example semantic web

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Generalized planning as heuristic search: A new planning search-space that leverages pointers over objects

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ARTIFICIAL INTELLIGENCE 2024年 330卷

作者： Segovia-Aguas, Javier Jimenez, Sergio Jonsson, Anders Univ Pompeu Fabra Fabra Spain Univ Politecn Valencia Valencia Spain

Planning as heuristic search is one of the most successful approaches to classical planning but unfortunately, it does not trivially extend to Generalized Planning (GP);GP aims to compute algorithmic solutions that are valid for a set of classical planning instances from a given domain, even if these instances differ in their number of objects, the initial and goal configuration of these objects and hence, in the number (and possible values) of the state variables. State -space search, as it is implemented by heuristic planners, becomes then impractical for GP. In this paper we adapt the planning as heuristic search paradigm to the generalization requirements of GP, and present the first native heuristic search approach to GP. First, the paper introduces a new pointerbased solution space for GP that is independent of the number of classical planning instances in a GP problem and the size of those instances (i.e. the number of objects, state variables and their domain sizes). Second, the paper defines an upgraded version of our GP algorithm, called Best -First Generalized Planning (BFGP), that implements a best -first search in our pointer -based solution space for GP. Lastly, the paper defines a set of evaluation and heuristic functions for BFGP that assess the structural complexity of the candidate GP solutions, as well as their fitness to a given input set of classical planning instances. The computation of these evaluation and heuristic functions does not require grounding states or actions in advance. Therefore our GP as heuristic search approach can handle large sets of state variables with large numerical domains, e.g. integers.

关键词： Generalized planning Classical planning Heuristic search Planning and learning Domain-specific control knowledge Program synthesis programming by example

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