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ACM TRANSACTIONS ON SOFTWARE ENGINEERING AND METHODOLOGY 2024年第1期33卷 1-36页

作者： Wu, Jiarong Wei, Lili Jiang, Yanyan Cheung, Shing-Chi Ren, Luyao Xu, Chang Hong Kong Univ Sci & Technol Dept Comp Sci & Engn Kowloon Clear Water Bay Hong Kong Peoples R China McGill Univ Dept Elect & Comp Engn McConnell Engn Bldg3480 Univ St Montreal PQ H3A 0E9 Canada Nanjing Univ State Key Lab Novel Software Technol Xianlin Campus163 Xianlin Rd Nanjing 210023 Jiangsu Peoples R China Nanjing Univ Dept Comp Sci & Technol Xianlin Campus163 Xianlin Rd Nanjing 210023 Jiangsu Peoples R China Peking Univ Key Lab High Confidence Software Technol Minist EducDept Comp Sci & TechnolEECS 5 Yiheyuan Rd Beijing 100871 Peoples R China

programming by example (PBE) is an emerging programming paradigm that automatically synthesizes programs specified by user-provided input-output examples. Despite the convenience for end-users, implementing PBE tools often requires strong expertise in programming language and synthesis algorithms. Such a level of knowledge is uncommon among software developers. It greatly limits the broad adoption of PBE by the industry. To facilitate the adoption of PBE techniques, we propose a PBE framework called BEE, which leverages an "entity-action" model based on relational tables to ease PBE development for a wide but restrained range of domains. Implementing PBE tools with Bee only requires adapting domain-specific data entities and user actions to tables, with no need to design a domain-specific language or an efficient synthesis algorithm. The synthesis algorithm of Bee exploits bidirectional searching and constraint-solving techniques to address the challenge of value computation nested in table transformation. We evaluated Bee's effectiveness on 64 PBE tasks from three different domains and usability with a human study of 12 participants. Evaluation results show that Bee is easier to learn and use than the state-of-the-art PBE framework, and the bidirectional algorithm achieves comparable performance to domain-specifically optimized synthesizers.

关键词： Program synthesis programming by example

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programming by example: The human face of AI

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AI & Society 1992年第2期6卷 166-180页

作者： Witten, Ian H. MacDonald, Bruce A. Maulsby, David L. Heise, Rosanna Computer Science University of Calgary Calgary T2N 1N4 Canada

It is argued that "human-centredness" will be an important characteristic of systems that learn tasks from human users, as the difficulties in inductive inference rule out learning without human assistance. The aim of "programming by example" is to create systems that learn how to perform tasks from their human users by being shown examples of what is to be done. Just as the user creates a learning environment for the system, so the system provides a teaching opportunity for the user, and emphasis is placed as much on facilitating successful teaching as on incorporating techniques of machine learning. If systems can "learn" repetitive tasks, their users will have the power to decide for themselves which parts of their jobs should be automated, and teach the system how to do them - reducing their dependence on intermediaries such as system designers and programmers. This paper presents principles for programming by example derived from experience in creating four prototype learners: for technical drawing, text editing, office tasks, and robot assembly. A teaching metaphor (a) enables the user to demonstrate a task by performing it manually, (b) helps to explain the learner's limited capabilities in terms of a persona, and (c) allows users to attribute intentionality. Tasks are represented procedurally, and augmented with constraints. Suitable mechanisms for attention focusing are necessary in order to control inductive search. Hidden features of a task should be made explicit so that the learner need not embark on the huge search entailed by hypothesizing missing steps. © 1992 Springer-Verlag.

关键词： Attention focusing Instructible systems Intentional stance Machine learning programming by example Teaching metaphor

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FlashFill⁺⁺: Scaling programming by example by Cutting to the Chase

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PROCEEDINGS OF THE ACM ON programming LANGUAGES-PACMPL 2023年第POPL期7卷 952-981页

作者： Cambronero, Jose Gulwani, Sumit Le, Vu Perelman, Daniel Radhakrishna, Arjun Simon, Clint Tiwari, Ashish Microsoft Redmond WA 98052 USA

programming-by-examples (PBE) involves synthesizing an intended program from a small set of user-provided input-output examples. A key PBE strategy has been to restrict the search to a carefully designed small domain-specific language (DSL) with effectively-invertible (EI) operators at the top and effectively-enumerable (EE) operators at the bottom. This facilitates an effective combination of top-down synthesis strategy (which backpropagates outputs over various paths in the DSL using inverse functions) with a bottom-up synthesis strategy (which propagates inputs over various paths in the DSL). We address the problem of scaling synthesis to large DSLs with several non-EI/EE operators. This is motivated by the need to support a richer class of transformations and the need for readable code generation. We propose a novel solution strategy that relies on propagating fewer values and over fewer paths. Our first key idea is that of cut functions that prune the set of values being propagated by using knowledge of the sub-DSL on the other side. Cuts can be designed to preserve completeness of synthesis;however, DSL designers may use incomplete cuts to have finer control over the kind of programs synthesized. In either case, cuts make search feasible for non-EI/EE operators and effcient for deep DSLs. Our second key idea is that of guarded DSLs that allow a precedence on DSL operators, which dynamically controls exploration of various paths in the DSL. This makes search efficient over grammars with large fanouts without losing recall. It also makes ranking simpler yet more effective in learning an intended program from very few examples. Both cuts and precedence provide a mechanism to the DSL designer to restrict search to a reasonable, and possibly incomplete, space of programs. Using cuts and gDSLs, we have built FlashFill(++), an industrial-strength PBE engine for performing rich string transformations, including datetime and number manipulations. The FlashFill(++) gDSL

关键词： programming by example domain-specific languages string transformations

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Semantic programming by example with Pre-trained Models

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PROCEEDINGS OF THE ACM ON programming LANGUAGES-PACMPL 2021年第OOPSLA期5卷 1–25页

作者： Verbruggen, Gust Le, Vu Gulwani, Sumit Katholieke Univ Leuven Dept Comp Sci Leuven Belgium Microsoft One Microsoft Way Redmond WA 98052 USA

The ability to learn programs from few examples is a powerful technology with disruptive applications in many domains, as it allows users to automate repetitive tasks in an intuitive way. Existing frameworks on inductive synthesis only perform syntactic manipulations, where they rely on the syntactic structure of the given examples and not their meaning. Any semantic manipulations, such as transforming dates, have to be manually encoded by the designer of the inductive programming framework. Recent advances in large language models have shown these models to be very adept at performing semantic transformations of its input by simply providing a few examples of the task at hand. When it comes to syntactic transformations, however, these models are limited in their expressive power. In this paper, we propose a novel framework for integrating inductive synthesis with few-shot learning language models to combine the strength of these two popular technologies. In particular, the inductive synthesis is tasked with breaking down the problem in smaller subproblems, among which those that cannot be solved syntactically are passed to the language model. We formalize three semantic operators that can be integrated with inductive synthesizers. To minimize invoking expensive semantic operators during learning, we introduce a novel deferred query execution algorithm that considers the operators to be oracles during learning. We evaluate our approach in the domain of string transformations: the combination methodology can automate tasks that cannot be handled using either technologies by themselves. Finally, we demonstrate the generality of our approach via a case study in the domain of string profiling.

关键词： program synthesis programming by example language models

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Governing Open Vocabulary Data Leaks U sing an Edge LLM through programming by example

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PROCEEDINGS OF THE ACM ON INTERACTIVE MOBILE WEARABLE AND UBIQUITOUS TECHNOLOGIES-IMWUT 2024年第4期8卷 1-31页

作者： Li, Qiyu Wen, Jinhe Jin, Haojian Univ Calif San Diego La Jolla CA 92093 USA

A major concern with integrating large language model (LLM) services (e.g., ChatGPT) into workplaces is that employees may inadvertently leak sensitive information through their prompts. Since user prompts can involve arbitrary vocabularies, conventional data leak mitigation solutions, such as string-matching-based filtering, often fall short. We present GPTWall, a privacy firewall that helps internal admins create and manage policies to mitigate data leaks in prompts sent to external LLM services. GPTWall's key innovations are (1) introducing a lightweight LLM running on the edge to obfuscate target information in prompts and restore the information after receiving responses, and (2) helping admins author fine-grained disclosure policies through programming by example. We evaluated GPTWall with 12 participants and found that they could create an average of 17.7 policies within 30 minutes, achieving an increase of 29% in precision and 22% in recall over the state-of-the-art data de-identification tool.

关键词： data leak programming by example edge computing large language model

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Guiding Dynamic Programing via Structural Probability for Accelerating programming by example

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PROCEEDINGS OF THE ACM ON programming LANGUAGES-PACMPL 2020年第OOPSLA期4卷 1–29页

作者： Ji, Ruyi Sun, Yican Xiong, Yingfei Hu, Zhenjiang Peking Univ Key Lab High Confidence Software Technol Minist Educ Dept Comp Sci & TechnolEECS Beijing Peoples R China

programming by example (PBE) is an important subproblem of program synthesis, and PBE techniques have been applied to many domains. Though many techniques for accelerating PBE systems have been explored, the scalability remains one of the main challenges: There is still a gap between the performances of state-of-the-art synthesizers and the industrial requirement. To further speed up solving PBE tasks, in this paper, we propose a novel PBE framework MaxPlash. MaxPlash uses a model based on structural probability, named topdown prediction models, to guide a search based on dynamic programming, such that the search will focus on subproblems that form probable programs, and avoid improbable programs. Our evaluation shows that MaxFlash achieves x4.107 - x2080 speed-ups against state-of-the-art solvers on 244 real-world tasks.

关键词： programming by example Dynamic programming Probabilistic Model

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User Interaction Models for Disambiguation in programming by example 15

User Interaction Models for Disambiguation in Programming by...

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28th Annual ACM Symposium on User Interface Software and Technology (UIST)

作者： Mayer, Mikael Soares, Gustavo Grechkin, Maxim Le, Vu Marron, Mark Polozov, Oleksandr Singh, Rishabh Zorn, Benjamin Gulwani, Sumit Ecole Polytech Fed Lausanne Lausanne Switzerland Univ Fed Campina Grande Campina Grande PB Brazil UW Seattle WA USA Univ Calif Davis Davis CA USA Microsoft Res Redmond WA USA

ISBN: (纸本)9781450337793

programming by examples (PBE) has the potential to revolutionize end-user programming by enabling end users, most of whom are non-programmers, to create small scripts for automating repetitive tasks. However, examples, though often easy to provide, are an ambiguous specification of the user's intent. Because of that, a key impedance in adoption of PBE systems is the lack of user confidence in the correctness of the program that was synthesized by the system. We present two novel user interaction models that communicate actionable information to the user to help resolve ambiguity in the examples. One of these models allows the user to effectively navigate between the huge set of programs that are consistent with the examples provided by the user. The other model uses active learning to ask directed example-based questions to the user on the test input data over which the user intends to run the synthesized program. Our user studies show that each of these models significantly reduces the number of errors in the performed task without any difference in completion time. Moreover, both models are perceived as useful, and the proactive active-learning based model has a slightly higher preference regarding the users' confidence in the result.

关键词： program navigation programming by example data manipulation disambiguation

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Interactive programming by example

Interactive Programming by Example

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作者： Mikael MAYER ECOLE POLYTECHNIQUE FEDERALE DE LAUSANNE

学位级别：博士

As of today, programming has never been so accessible. Yet, it remains a challenge for end-users: students, non-technical employees, experts in their domains outside of computer science, and so on. With its forecast potential for solving problems by only observing inputs and outputs, programming-by-example was supposed to alleviate complex tasks requiring programming for end-users. The initial ideas of macro-based editors paved the way to subsequent practical solutions, such as spreadsheet transformations from examples. Finding the right program is the core of the programming-by-example systems. However, users find it difficult to trust such generated programs. In this thesis, we contribute to proving that some forms of interaction alleviate, by having users provide examples, the problem of finding correct and reliable programs. We first report on two experiments that enable us to conjecture what kind of interaction brings benefits to programming-by-example. First, we present a new kind of game engine, Pong Designer. In this game engine, by using their finger, users program rules on the fly, by modifying the game state. We analyze its potential, and its eventual downsides that have probably prevented its wide adoption. Second, we present StriSynth, an interactive command-line tool that uses programming-by-example to transform string and collections. The resulting programs can also rename or otherwise manage files. We obtained the result that confirms that many users preferred StriSynth over usual programming languages, but would appreciate to have both. We then report on two new exciting experiments with verified results, using two forms of interaction truly benefiting programming-by-example. Third, on top of a programming- by-example-based engine for extracting structured data out of text files, in this thesis we study two interaction models implemented in a tool named FlashProg: a view of the program with notification about ambiguities, and the asking of clarifica

关键词： programming by example programming by demonstration program synthesis accessibility domain-specific languages active learning

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Live programming and programming by example: Better Together (Keynote) 2021

Live Programming and Programming by Example: Better Together...

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20th ACM SIGPLAN International Conference on Generative programming: Concepts and Experiences (GPCE)

作者： Lerner, Sorin Univ Calif San Diego La Jolla CA 92093 USA

ISBN: (纸本)9781450391122

Live programming is a paradigm in which values from program execution are shown to the programmer through continual feedback. programming by example is a paradigm in which code is synthesized from example values showing a desired behavior. This talk presents some of our recent research that combines these two paradigms in beneficial ways. I will walk through our ideas, explain our contributions, discuss what we learned and finally provide thoughts for the future.

关键词： Live programming programming by example Program Synthesis

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A reporting tool using “programming by example” for format designation 00

A reporting tool using “programming by example” for format...

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Proceedings of the 5th international conference on Intelligent user interfaces

作者： Tetsuya Masuishi Nobuo Takahashi Business & Information Systems Development Division Hitachi Ltd. 890 Kashimada Saiwai Kawasaki 211-8567 Japan Software Division Hitachi Ltd. Kaneichi Building 549-6 Shinano-cho Totsuka Yokohama 244-0801 Japan

ISBN: (纸本)9781581131345

This paper describes a report tool in which report formats are designated by “programming by example”-like operations. Users specify a sample layout of an example row of relational table data on a sheet, and select an iteration pattern of the sample layout. The tool extracts a set of general formatting rules from the sample layout. The rules consist of absolute positions of non-iterative data, relative positions of iterative data, the iteration pattern, and the increment of the iteration. The tool interprets the rules and generates new reports of the format for different table data.

关键词： reporting tool relational database user interface programming by example

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