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1. Reconciling enumerative and deductive program synthesis

   https://doi.org/10.1145/3385412.3386027  

   Huang, Kangjing; Qiu, Xiaokang; Shen, Peiyuan; Wang, Yanjun (June 2020, Proceedings of the 41st ACM SIGPLAN Conference on Programming Language Design and Implementation)

   null (Ed.)

   Syntax-guided synthesis (SyGuS) aims to find a program satisfying semantic specification as well as user-provided structural hypotheses. There are two main synthesis approaches: enumerative synthesis, which repeatedly enumerates possible candidate programs and checks their correctness, and deductive synthesis, which leverages a symbolic procedure to construct implementations from specifications. Neither approach is strictly better than the other: automated deductive synthesis is usually very efficient but only works for special grammars or applications; enumerative synthesis is very generally applicable but limited in scalability. In this paper, we propose a cooperative synthesis technique for SyGuS problems with the conditional linear integer arithmetic (CLIA) background theory, as a novel integration of the two approaches, combining the best of the two worlds. The technique exploits several novel divide-and-conquer strategies to split a large synthesis problem to smaller subproblems. The subproblems are solved separately and their solutions are combined to form a final solution. The technique integrates two synthesis engines: a pure deductive component that can efficiently solve some problems, and a height-based enumeration algorithm that can handle arbitrary grammar. We implemented the cooperative synthesis technique, and evaluated it on a wide range of benchmarks. Experiments showed that our technique can solve many challenging synthesis problems not possible before, and tends to be more scalable than state-of-the-art synthesis algorithms. 

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2. Towards Reactive Synthesis as a Programming Paradigm

   Cui, Leyi; Rothkopf, Raven; Santolucito, Mark (May 2024, Kilthub)

   Reactive program synthesis from logical specifications has yet to match the user-friendly approach of examplebased programming for spreadsheets, despite its success in specific domains. A main challenge hindering the broader adoption of reactive synthesis is in the complexity of specification engineering in temporal logics. We map out challenges and tools that arise as users write temporal logic specifications in Temporal Stream Logic. Our goal is to provide a roadmap for future usability work that can elevate temporal specification engineering for synthesis to match the usability support available for software engineering. By generalizing these concepts, we can gain a deeper insight into the challenges people face when reasoning about the temporal behavior of their systems. 

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3. Concise Read-Only Specifications for Better Synthesis of Programs with Pointers

   https://doi.org/10.1007/978-3-030-44914-8_6  

   Costea Andreea, Zhu Amy (April 2020, 29th European Symposium on Programming)

   In program synthesis there is a well-known trade-off between concise and strong specifications: if a specification is too verbose, it might be harder to write than the program; if it is too weak, the synthesised program might not match the user’s intent. In this work we explore the use of annotations for restricting memory access permissions in program synthesis, and show that they can make specifications much stronger while remaining surprisingly concise. Specifically, we enhance Synthetic Separation Logic (SSL), a framework for synthesis of heap-manipulating programs, with the logical mechanism of read-only borrows. We observe that this minimalistic and conservative SSL extension benefits the synthesis in several ways, making it more (a) expressive (stronger correctness guarantees are achieved with a modest annotation overhead), (b) effective (it produces more concise and easier-to-read programs), (c) efficient (faster synthesis), and (d) robust (synthesis efficiency is less affected by the choice of the search heuristic). We explain the intuition and provide formal treatment for read-only borrows. We substantiate the claims (a)–(d) by describing our quantitative evaluation of the borrowing-aware synthesis implementation on a series of standard benchmark specifications for various heap-manipulating programs. 

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4. Optimizing Ordered Graph Algorithms with GraphIt

   Zhang, Yunming; Brahmakshatriya, Ajay; Chen, Xinyi; Dhulipala, Laxman; Kamil, Shoaib; Amarasinghe, Saman; Shun, Julian (February 2020, International Symposium on Code Generation and Optimization)

   Many graph problems can be solved using ordered parallel graph algorithms that achieve significant speedup over their unordered counterparts by reducing redundant work. This paper introduces a new priority-based extension to GraphIt, a domain-specific language for writing graph applications, to simplify writing high-performance parallel ordered graph algorithms. The extension enables vertices to be processed in a dynamic order while hiding low-level implementation details from the user. We extend the compiler with new program analyses, transformations, and code generation to produce fast implementations of ordered parallel graph algorithms. We also introduce bucket fusion, a new performance optimization that fuses together different rounds of ordered algorithms to reduce synchronization overhead, resulting in 1.2x--3x speedup over the fastest existing ordered algorithm implementations on road networks with large diameters. With the extension, GraphIt achieves up to 3x speedup on six ordered graph algorithms over state-of-the-art frameworks and hand-optimized implementations (Julienne, Galois, and GAPBS) that support ordered algorithms. 

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5. Perfect Is the Enemy of Good: Best-Effort Program Synthesis

   https://doi.org/10.4230/LIPIcs.ECOOP.2020.2  

   Peleg, Hila; Polikarpova, Nadia (November 2020, Leibniz international proceedings in informatics)

   Hirschfeld, Robert; Pape, Tobias (Ed.)

   Program synthesis promises to help software developers with everyday tasks by generating code snippets automatically from input-output examples and other high-level specifications. The conventional wisdom is that a synthesizer must always satisfy the specification exactly. We conjecture that this all-or-nothing paradigm stands in the way of adopting program synthesis as a developer tool: in practice, the user-written specification often contains errors or is simply too hard for the synthesizer to solve within a reasonable time; in these cases, the user is left with a single over-fitted result or, more often than not, no result at all. In this paper we propose a new program synthesis paradigm we call best-effort program synthesis, where the synthesizer returns a ranked list of partially-valid results, i.e. programs that satisfy some part of the specification. To support this paradigm, we develop best-effort enumeration, a new synthesis algorithm that extends a popular program enumeration technique with the ability to accumulate and return multiple partially-valid results with minimal overhead. We implement this algorithm in a tool called BESTER, and evaluate it on 79 synthesis benchmarks from the literature. Contrary to the conventional wisdom, our evaluation shows that BESTER returns useful results even when the specification is flawed or too hard: i) for all benchmarks with an error in the specification, the top three BESTER results contain the correct solution, and ii) for most hard benchmarks, the top three results contain non-trivial fragments of the correct solution. We also performed an exploratory user study, which confirms our intuition that partially-valid results are useful: the study shows that programmers use the output of the synthesizer for comprehension and often incorporate it into their solutions. 

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