Synthesizing switching logic using constraint solving

Taly, Ankur; Gulwani, Sumit; Tiwari, Ashish

doi:10.1007/s10009-010-0172-8

Cited by 41 publications

(30 citation statements)

References 23 publications

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“…Program synthesis has traditionally been motivated by the need to synthesize non-trivial algorithms [12,22,23] or to discover tricky code-snippets [10,24]. In this paper, we apply program synthesis to discovering relatively simpler programs, but those that are cared about by a much larger class of spreadsheet end-users, who often struggle with manipulating tabular data in spreadsheets.…”

Section: Related Workmentioning

confidence: 99%

Spreadsheet table transformations from examples

Harris

Gulwani

2011

Proceedings of the 32nd ACM SIGPLAN Conference on Programming Language Design and Implementation

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Every day, millions of computer end-users need to perform tasks over large, tabular data, yet lack the programming knowledge to do such tasks automatically. In this work, we present an automatic technique that takes from a user an example of how the user needs to transform a table of data, and provides to the user a program that implements the transformation described by the example. In particular, we present a language of programs TableProg that can describe transformations that real users require. We then present an algorithm ProgFromEx that takes an example input and output table, and infers a program in TableProg that implements the transformation described by the example. When the program is applied to the example input, it reproduces the example output. When the program is applied to another, potentially larger, table with a "similar" layout as the example input table, then the program produces a corresponding table with a layout that is similar to the example output table. A user can apply ProgFromEx interactively, providing multiple small examples to obtain a program that implements the transformation that the user desires. Moreover, ProgFromEx can help identify "noisy" examples that contain errors.To evaluate the practicality of TableProg and ProgFromEx, we implemented ProgFromEx as a module for the Microsoft Excel spreadsheet program. We applied the module to automatically implement over 50 table transformations specified by endusers through examples on online Excel help forums. In seconds, ProgFromEx found programs that satisfied the examples and could be applied to larger input tables. This experience demonstrates that TableProg and ProgFromEx can significantly automate the tasks over tabular data that users need to perform.

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Section: Related Workmentioning

confidence: 99%

Spreadsheet table transformations from examples

Harris

Gulwani

2011

Proceedings of the 32nd ACM SIGPLAN Conference on Programming Language Design and Implementation

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“…Proof-theoretic synthesis [38] and similar approaches for hybrid systems [39] are deductive synthesis techniques, which encode the synthesis problem as a search for invariants, and therefore needs to infer complicated invariants (and requires a formal verifier with support for such reasoning). In contrast, PINS relies on directed path exploration and symbolic execution-based reasoning, and does not reason about invariants.…”

Section: Related Workmentioning

confidence: 99%

“…The user then runs PINS, using its output to further guide manual refinement of the template. We have found that this approach is much easier than other synthesis techniques that require constructing a template from scratch [38,39,33].…”

Section: Introductionmentioning

confidence: 99%

“…One challenge in using PINS, or any other template-based synthesis approach (e.g., proof-theoretic synthesis [38], invariantbased synthesis for hybrid systems [39] or Sketching [33]), is determining what template to use. For program inversion, we have developed a semi-automated technique for mining the template from the program to be inverted.…”

Section: Introductionmentioning

confidence: 99%

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Path-based inductive synthesis for program inversion

Srivastava¹,

Gulwani²,

Chaudhuri³

et al. 2011

Proceedings of the 32nd ACM SIGPLAN Conference on Programming Language Design and Implementation

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In this paper, we investigate the problem of semi-automated inversion of imperative programs, which has the potential to make it much easier and less error prone to write programs that naturally pair as inverses, such as insert/delete operations, compressors/decompressors, and so on. Viewing inversion as a subproblem of program synthesis, we propose a novel synthesis technique called Path-based Inductive Synthesis (PINS) and apply it to inversion. PINS starts from a program P and a template T for its inverse. PINS then iteratively refines the space of template instantiations by exploring paths in the composition of P and T with symbolic execution. PINS uses an SMT solver to intelligently guide the refinement process, based on the paths explored so far. The key idea motivating this approach is the small path-bound hypothesis: that the behavior of a program can be summarized with a small, carefully chosen set of its program paths.We evaluated PINS by using it to invert 14 programs such as compressors (e.g., Lempel-Ziv-Welch), encoders (e.g., UUEncode), and arithmetic operations (e.g., vector rotation). Most of these examples are difficult or impossible to invert using prior techniques, but PINS was able to invert all of them. We also found that a semi-automated technique we developed to mine a template from the program to be inverted worked well. In our experiments, PINS takes between one second to thirty minutes to synthesize inverses. We believe this proof-of-concept implementation demonstrates the viability of the PINS approach to program synthesis.

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“…However, it has traditionally focused on synthesizing nontrivial algorithms 20 (e.g., graph algorithms 9 and program inverses 19 ) and discovering intricate code-snippets (e.g., bit-vector tricks, 7 switching logic in hybrid systems 21 ). In this paper, we apply program synthesis to discover simpler programs required by the much larger class of spreadsheet end-users.…”

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confidence: 99%

Spreadsheet data manipulation using examples

2012

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Millions of computer end users need to perform tasks over large spreadsheet data, yet lack the programming knowledge to do such tasks automatically. We present a programming by example methodology that allows end users to automate such repetitive tasks. Our methodology involves designing a domain-specific language and developing a synthesis algorithm that can learn programs in that language from user-provided examples. We present instantiations of this methodology for particular domains of tasks: (a) syntactic transformations of strings using restricted forms of regular expressions, conditionals, and loops, (b) semantic transformations of strings involving lookup in relational tables, and (c) layout transformations on spreadsheet tables. We have implemented this technology as an add-in for the Microsoft Excel Spreadsheet system and have evaluated it successfully over several benchmarks picked from various Excel help forums.

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Synthesizing switching logic using constraint solving

Cited by 41 publications

References 23 publications

Spreadsheet table transformations from examples

Spreadsheet table transformations from examples

Path-based inductive synthesis for program inversion

Spreadsheet data manipulation using examples

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