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SYCRAFT: A Tool for Synthesizing Distributed Fault-Tolerant Programs [chapter]

Borzoo Bonakdarpour, Sandeep S. Kulkarni
2008 Lecture Notes in Computer Science  
We present the tool Sycraft (SYmboliC synthesizeR and Adder of Fault-Tolerance). In Sycraft, a distributed fault-intolerant program is specified in terms of a set of processes and an invariant.  ...  Given a set of fault actions and a specification, the tool transforms the input distributed fault-intolerant program into a distributed fault-tolerant program via a symbolic implementation of respective  ...  The Tool SYCRAFT The tool Sycraft implements a set of symbolic heuristics for synthesizing faulttolerant distributed programs. It has been tested using various case studies.  ... 
doi:10.1007/978-3-540-85361-9_16 fatcat:zdblv2nv6bfbpcucfuf3lesgeu

Data-Driven Synthesis of Full Probabilistic Programs [chapter]

Sarah Chasins, Phitchaya Mangpo Phothilimthana
2017 Lecture Notes in Computer Science  
To make the modeling process easier, we have created a tool that synthesizes PPL programs from relational datasets.  ...  Our synthesizer leverages the input data to generate a program sketch, then applies simulated annealing to complete the sketch.  ...  This work is supported in part by NSF Grants CCF-1139138, CCF-1337415, NSF ACI-1535191, and Graduate Research Fellowship DGE-1106400, a Microsoft Research PhD Fellowship, a grant from the U.S.  ... 
doi:10.1007/978-3-319-63387-9_14 fatcat:idnaf7svwrc2thcmndstn6gjxm

Efficient synthesis of probabilistic programs

Aditya V. Nori, Sherjil Ozair, Sriram K. Rajamani, Deepak Vijaykeerthy
2015 Proceedings of the 36th ACM SIGPLAN Conference on Programming Language Design and Implementation - PLDI 2015  
A core difficulty in synthesizing probabilistic programs is computing the likelihood L(P | D) of a candidate program P generating data D.  ...  Our algorithm efficiently synthesizes a probabilistic program that is most consistent with the data.  ...  Next, we evaluate how well the posterior distribution of the synthesized probabilistic program matches with the intended distribution.  ... 
doi:10.1145/2737924.2737982 dblp:conf/pldi/NoriORV15 fatcat:6k3nkkbzfra5vplekzxot3rsoi

Efficient synthesis of probabilistic programs

Aditya V. Nori, Sherjil Ozair, Sriram K. Rajamani, Deepak Vijaykeerthy
2015 SIGPLAN notices  
A core difficulty in synthesizing probabilistic programs is computing the likelihood L(P | D) of a candidate program P generating data D.  ...  Our algorithm efficiently synthesizes a probabilistic program that is most consistent with the data.  ...  Next, we evaluate how well the posterior distribution of the synthesized probabilistic program matches with the intended distribution.  ... 
doi:10.1145/2813885.2737982 fatcat:4zrdv2tnhvb67dowwxnpflj6ii

Efficient Pragmatic Program Synthesis with Informative Specifications [article]

Saujas Vaduguru, Kevin Ellis, Yewen Pu
2022 arXiv   pre-print
In this paper, we show that it is possible to build a program synthesizer that is both pragmatic and efficient by approximating the joint distribution of programs with a product of independent factors,  ...  Surprisingly, we find that the synthesizer assuming a factored approximation performs better than a synthesizer assuming an exact joint distribution when evaluated on natural human inputs.  ...  Introduction Program synthesizers are systems that take a specification of user intent as input, and synthesize a program in a domain-specific language (DSL) that satisfies the specification.  ... 
arXiv:2204.02495v1 fatcat:44eny3qrnbeypgwzvhdj7iljse

Synthesis of small crystals zeolite NaY

Shiyun Sang, Zhongmin Liu, Peng Tian, Ziyu Liu, Lihong Qu, Yangyang Zhang
2006 Materials letters (General ed.)  
Zeolite NaY with small crystals was hydrothermally synthesized using a two-stage variable-temperature program without the presence of organic templates, structure-directing agent, seeding crystals and  ...  The temperature was found to be a crucial factor for the control of the crystal size.  ...  The particle size distributions of as-synthesized samples by an isothermal program at 333 and 373 K were shown in Fig. 2(A) .  ... 
doi:10.1016/j.matlet.2005.10.110 fatcat:tjqa4pl5brdivjvsk5xjwksrhm

Synthesizing efficient out-of-core programs for block recursive algorithms using block-cyclic data distributions

Zhiyong Li, J.H. Reif, S.K.S. Gupta
1999 IEEE Transactions on Parallel and Distributed Systems  
Further, we formalize the procedure of synthesizing efficient out-of-core programs for tensor product formulas with various block-cyclic distributions as a dynamic programming problem.  ...  We accurately represent the number of parallel I/O operations required for the synthesized programs for tensor products and matrix transposition as a function of tensor bases and data distributions.  ...  The choice of data distribution has a large influence on the performance of the synthesized programs, 2.  ... 
doi:10.1109/71.755830 fatcat:j2tw754kyvemvhjisyd433mz7u

Program Synthesis Over Noisy Data with Guarantees [article]

Shivam Handa, Martin Rinard
2021 arXiv   pre-print
By formalizing the concept of a Noise Source, an Input Source, and a prior distribution over programs, we formalize the probabilistic process which constructs a noisy dataset.  ...  This formalism allows us to define the correctness of a synthesis algorithm, in terms of its ability to synthesize the hidden underlying program.  ...  Formally, ℎ = { ∈ | ℎ } Prior Distribution over Programs: Given a set of programs , let be a prior distribution over programs in .  ... 
arXiv:2103.05030v4 fatcat:5kibvu2q6rguddx4z4lbmzna5i

MapReduce program synthesis

Calvin Smith, Aws Albarghouthi
2016 Proceedings of the 37th ACM SIGPLAN Conference on Programming Language Design and Implementation - PLDI 2016  
In this paper, we ask whether we can automatically synthesize MapReduce-style distributed programs from input-output examples.  ...  The question we ask here is how can we synthesize a MapReduce program from input-output examples?  ...  in a distributed environment.  ... 
doi:10.1145/2908080.2908102 dblp:conf/pldi/SmithA16 fatcat:cxb2uah3xzhpnalb5wqyi5negm

MapReduce program synthesis

Calvin Smith, Aws Albarghouthi
2016 SIGPLAN notices  
In this paper, we ask whether we can automatically synthesize MapReduce-style distributed programs from input-output examples.  ...  The question we ask here is how can we synthesize a MapReduce program from input-output examples?  ...  in a distributed environment.  ... 
doi:10.1145/2980983.2908102 fatcat:v32qb2hemrdvhbicqcsjgq67ne

Synthesize, Execute and Debug: Learning to Repair for Neural Program Synthesis [article]

Kavi Gupta, Peter Ebert Christensen, Xinyun Chen, Dawn Song
2020 arXiv   pre-print
Instead of purely relying on the neural program synthesizer to generate the final program, SED first produces initial programs using the neural program synthesizer component, then utilizes a neural program  ...  However, when the program semantics become more complex, it still remains a challenge to synthesize programs that are consistent with the specification.  ...  Middle and right: The joint distributions of the edit distances between the initial program predicted by the LGRL synthesizer (init), the gold program, and the program predicted by SED that passes all  ... 
arXiv:2007.08095v2 fatcat:ya7nzo5dqbbyjcvk4tmk7ek5rm

Chlorophyll

Phitchaya Mangpo Phothilimthana, Tikhon Jelvis, Rohin Shah, Nishant Totla, Sarah Chasins, Rastislav Bodik
2013 Proceedings of the 35th ACM SIGPLAN Conference on Programming Language Design and Implementation - PLDI '14  
We show that the synthesized programs are no more than 19% slower than highly optimized expert-written programs on the MD5 benchmark and are faster than programs produced by a heuristic, non-synthesizing  ...  We developed Chlorophyll, a synthesis-aided programming model and compiler for the GreenArrays GA144, an extremely minimalist low-power spatial architecture that requires partitioning a program into fragments  ...  Rather than writing a program directly, the user provides a goal (the specification) and the synthesizer automatically generates the program.  ... 
doi:10.1145/2594291.2594339 dblp:conf/pldi/PhothilimthanaJSTCB14 fatcat:kxqmfqg275cevdfxcennhbi6sq

Learning to Infer Program Sketches [article]

Maxwell Nye, Luke Hewitt, Joshua Tenenbaum, Armando Solar-Lezama
2019 arXiv   pre-print
programming problems.  ...  The key idea of this work is that a flexible combination of pattern recognition and explicit reasoning can be used to solve these complex programming problems.  ...  Our system consists of two main components: 1) a sketch generator, and 2) a program synthesizer. The sketch generator is a distribution over program sketches given the spec: q φ (sketch|X ).  ... 
arXiv:1902.06349v2 fatcat:p6p3yqqapvevtkwng7y5gjqflq

Program Synthesis for Character Level Language Modeling

Pavol Bielik, Veselin Raychev, Martin T. Vechev
2017 International Conference on Learning Representations  
Learning is done in two phases: (i) we synthesize a program from the DSL, essentially learning a good representation for the data, and (ii) we learn parameters from the training datathe process is done  ...  The model is parameterized by a program from a domain-specific language (DSL) that allows expressing non-trivial data dependencies.  ...  We note that P (x t | x <t , p) is a valid probability distribution since p(t, x <t ) always computes a unique program f and the distributions P f (x t | f (t, x <t )) are valid probability distributions  ... 
dblp:conf/iclr/BielikRV17 fatcat:vehogxb3e5aq3hele4vkktyahe

Learning to Represent Programs with Property Signatures [article]

Augustus Odena, Charles Sutton
2020 arXiv   pre-print
We discuss several potential applications of property signatures and show experimentally that they can be used to improve over a baseline synthesizer so that it emits twice as many programs in less than  ...  We introduce the notion of property signatures, a representation for programs and program specifications meant for consumption by machine learning algorithms.  ...  Most of all, we owe a substantial debt to Niklas Een, on whose Evo programming language (https://github.com/tensorflow/deepmath/tree/master/ deepmath/zz/CodeBreeder) the Searcho language is heavily based  ... 
arXiv:2002.09030v1 fatcat:ew5evgqhtjcwdllz4oc5fj75x4
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