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37th ACM SIGPLAN Conference on programming Language Design and Implementation

作者： Yaghmazadeh, Navid Klinger, Christian Dillig, Isil Chaudhuri, Swarat Univ Texas Austin Austin TX 78712 USA Univ Freiburg Freiburg Germany Rice Univ Houston TX 77251 USA

ISBN: (纸本)9781450342612

This paper presents a new approach for synthesizing transformations on tree-structured data, such as Unix directories and XML documents. We consider a general abstraction for such data, called hierarchical data trees (HDTs) and present a novel example-driven synthesis algorithm for HDT transformations. Our central insight is to reduce the problem of synthesizing tree transformers to the synthesis of list transformations that are applied to the paths of the tree. The synthesis problem over lists is solved using a new algorithm that combines SMT solving and decision tree learning. We have implemented our technique in a system called HADES and show that HADES can automatically synthesize a variety of interesting transformations collected from online forums.

关键词： Languages Program synthesis programming by example data transformations

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Synthesizing Transformations on Hierarchically Structured Data

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ACM SIGPLAN NOTICES 2016年第6期51卷 508-521页

作者： Yaghmazadeh, Navid Klinger, Christian Dillig, Isil Chaudhuri, Swarat Univ Texas Austin Austin TX 78712 USA Univ Freiburg Freiburg Germany Rice Univ Houston TX 77251 USA

关键词： Languages Program synthesis programming by example data transformations

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Learning Text Patterns Using Separate-and-Conquer Genetic programming 18

Learning Text Patterns Using Separate-and-Conquer Genetic Pr...

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18th European Conference on Genetic programming (EuroGP)

作者： Bartoli, Alberto De Lorenzo, Andrea Medvet, Eric Tarlao, Fabiano Univ Trieste DIA Trieste Italy

ISBN: (纸本)9783319165011;9783319165004

The problem of extracting knowledge from large volumes of unstructured textual information has become increasingly important. We consider the problem of extracting text slices that adhere to a syntactic pattern and propose an approach capable of generating the desired pattern automatically, from a few annotated examples. Our approach is based on Genetic programming and generates extraction patterns in the form of regular expressions that may be input to existing engines without any post-processing. Key feature of our proposal is its ability of discovering automatically whether the extraction task may be solved by a single pattern, or rather a set of multiple patterns is required. We obtain this property by means of a separate-and-conquer strategy: once a candidate pattern provides adequate performance on a subset of the examples, the pattern is inserted into the set of final solutions and the evolutionary search continues on a smaller set of examples including only those not yet solved adequately. Our proposal outperforms an earlier state-of-the-art approach on three challenging datasets.

关键词： Regular expressions Multiple pattern programming by example Text extraction

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Synthesizing Data Structure Transformations from Input-Output examples 15

Synthesizing Data Structure Transformations from Input-Outpu...

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36th ACM SIGPLAN Conference on programming Language Design and Implementation

作者： Feser, John K. Chaudhuri, Swarat Dillig, Isil Rice Univ Houston TX 77251 USA UT Austin Austin TX 78712 USA

ISBN: (纸本)9781450334686

We present a method for example-guided synthesis of functional programs over recursive data structures. Given a set of input-output examples, our method synthesizes a program in a functional language with higher-order combinators like map and fold. The synthesized program is guaranteed to be the simplest program in the language to fit the examples. Our approach combines three technical ideas: inductive generalization, deduction, and enumerative search. First, we generalize the input-output examples into hypotheses about the structure of the target program. For each hypothesis, we use deduction to infer new input/output examples for the missing subexpressions. This leads to a new subproblem where the goal is to synthesize expressions within each hypothesis. Since not every hypothesis can be realized into a program that fits the examples, we use a combination of best-first enumeration and deduction to search for a hypothesis that meets our needs. We have implemented our method in a tool called lambda(2), and we evaluate this tool on a large set of synthesis problems involving lists, trees, and nested data structures. The experiments demonstrate the scalability and broad scope of lambda(2). A highlight is the synthesis of a program believed to be the world's earliest functional pearl.

关键词： Program synthesis programming by example data transformations search-based synthesis automated deduction

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JSKETCH: Sketching for Java 2015

JSKETCH: Sketching for Java

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10th Joint Meeting of the European Software Engineering Conference (ESEC) / ACM SIGSOFT Symposium on the Foundations of Software Engineering (FSE)

作者： Jeon, Jinseong Qiu, Xiaokang Foster, Jeffrey S. Solar-Lezama, Armando Univ Maryland College Pk MD 20742 USA MIT Cambridge MA 02139 USA

ISBN: (纸本)9781450336758

Sketch-based synthesis, epitomized by the SKETCH tool, lets developers synthesize software starting from a partial program., also called a,sketch or template. This paper presents JSKETCH, a tool that brings sketcli-based synthesis to Java. JSKETCH'S input is a partial Java program that may include holes, which are unknown constants, expression generators, which range over sets of expressions, and class generators, which are partial classes. JSKETCH then translates the synthesis problem into a SKETCH problem;this translation is complex because SKETCH is not object oriented. Finally, JSKETCH synthesizes an executable Java program by interpreting the output of SKETCH.

关键词： Program Synthesis programming by example Java SKETCH

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StriSynth: Synthesis for Live programming 37

StriSynth: Synthesis for Live Programming

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IEEE/ACM 2nd International Workshop on Software Architecture and Metrics (SAM)

作者： Gulwani, Sumit Mayer, Mikael Niksic, Filip Piskac, Ruzica Microsoft Res Redmond Redmond WA USA Ecole Polytech Fed Lausanne Lausanne Switzerland MPI SWS Kaiserslautern Germany Yale Univ New Haven CT 06520 USA

ISBN: (纸本)9781479919345

Motivated by applications in automating repetitive file manipulations, we present a tool called StriSynth, which allows end-users to perform transformations over data using examples. Based on provided examples, our tool automatically generates scripts for non-trivial file manipulations. Although the current focus of StriSynth are file manipulations, it implements a more general string transformation framework. This framework builds on and further extends the functionality of Flash Fill-a Microsoft Excel extension for string transformations. An accompanying video to this paper is available at the following website http://***/kkDZphqIdFM.

关键词： File Manipulation Live programming programming by example Scripting Synthesis

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Interactive Parser Synthesis by example 15

Interactive Parser Synthesis by Example

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36th ACM SIGPLAN Conference on programming Language Design and Implementation

作者： Leung, Alan Sarracino, John Lerner, Sorin Univ Calif San Diego San Diego CA 92103 USA

ISBN: (纸本)9781450334686

Despite decades of research on parsing, the construction of parsers remains a painstaking, manual process prone to subtle bugs and pitfalls. We present a programming-by-example framework called Parsify that is able to synthesize a parser from input/output examples. The user does not write a single line of code. To achieve this, Parsify provides: (a) an iterative algorithm for synthesizing and refining a grammar one example at a time, (b) an interface that provides immediate visual feedback in response to changes in the grammar being refined, and (c) a graphical mechanism for specifying example parse trees using only textual selections. We empirically demonstrate the viability of our approach by using Parsify to construct parsers for source code drawn from Verilog, SQL, Apache, and Tiger.

关键词： Algorithms Human Factors Languages Parsing programming by example Program Synthesis

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Synthesizing Web Element Locators 15

Synthesizing Web Element Locators

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30th IEEE/ACM International Conference on Automated Software Engineering Workshops (ASEW)

作者： Bajaj, Kartik Pattabiraman, Karthik Mesbah, Ali Univ British Columbia Vancouver BC Canada

ISBN: (纸本)9781509000258

To programmatically interact with the user interface of a web application, element locators are used to select and retrieve elements from the Document Object Model (DOM). Element locators are used in JavaScript code, Cascading stylesheets, and test cases to interact with the runtime DOM of the webpage. Constructing these element locators is, however, challenging due to the dynamic nature of the DOM. We find that locators written by web developers can be quite complex, and involve selecting multiple DOM elements. We present an automated technique for synthesizing DOM element locators using examples provided interactively by the developer. The main insight in our approach is that the problem of synthesizing complex multi-element locators can be expressed as a constraint solving problem over the domain of valid DOM states in a web application. We implemented our synthesis technique in a tool called LED, which provides an interactive drag and drop support inside the browser for selecting positive and negative examples. We find that LED supports at least 86% of the locators used in the JavaScript code of deployed web applications, and that the locators synthesized by LED have a recall of 98% and a precision of 63%. LED is fast, taking only 0.23 seconds on average to synthesize a locator.

关键词： Program synthesis programming by example Element locators CSS selectors Web applications

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Evolutionary Learning of Syntax Patterns for Genic Interaction Extraction 15

Evolutionary Learning of Syntax Patterns for Genic Interacti...

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17th Genetic and Evolutionary Computation Conference (GECCO)

作者： Bartoli, Alberto De Lorenzo, Andrea Medvet, Eric Tarlao, Fabiano Virgolin, Marco Univ Trieste DIA I-34127 Trieste Italy

ISBN: (纸本)9781450334723

There is an increasing interest in the development of techniques for automatic relation extraction from unstructured text. The biomedical domain, in particular, is a sector that may greatly benefit from those techniques due to the huge and ever increasing amount of scientific publications describing observed phenomena of potential clinical interest. In this paper, we consider the problem of automatically identifying sentences that contain interactions between genes and proteins, based solely on a dictionary of genes and proteins and a small set of sample sentences in natural language. We propose an evolutionary technique for learning a classifier that is capable of detecting the desired sentences within scientific publications with high accuracy. The key feature of our proposal, that is internally based on Genetic programming, is the construction of a model of the relevant syntax patterns in terms of standard part-of-speech annotations. The model consists of a set of regular expressions that are learned automatically despite the large alphabet size involved. We assess our approach on two realistic datasets and obtain 74% accuracy, a value sufficiently high to be of practical interest and that is in line with significant baseline methods.

关键词： Regular Expressions Genetic programming programming by example Machine Learning

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LED: Tool for Synthesizing Web Element Locators 15

LED: Tool for Synthesizing Web Element Locators

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30th IEEE/ACM International Conference on Automated Software Engineering Workshops (ASEW)

作者： Bajaj, Kartik Pattabiraman, Karthik Mesbah, Ali Univ British Columbia Vancouver BC Canada

ISBN: (纸本)9781509000258

Web applications are growing fast in popularity and complexity. One of the major problems faced by web developers is writing JavaScript code that can retrieve Document Object Model (DOM) tree elements, and is consistent among multiple DOM states. We attempt to solve this problem by automatically synthesizing JavaScript code that interacts with the DOM. We present an automated tool called LED, to analyze the DOM elements, and synthesize code to select the DOM elements based on the DOM hierarchy as well as the nature of task that the user wants to perform. LED provides an interactive drag and drop support inside the browser for selecting positive and negative examples of DOM elements. We find that LED supports at least 86% of the locators used in the JavaScript code of deployed web applications, and that the locators synthesized by LED have a recall of 98% and a precision of 63%. LED is fast, taking only 0.23 seconds on average to synthesize a locator.

关键词： Program synthesis programming by example Element locators CSS selectors Web applications

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