Fast synthesis of fast collections

Loncaric, Calvin; Torlak, Emina; Ernst, M.

doi:10.1145/2980983.2908122

Cited by 8 publications

(3 citation statements)

References 28 publications

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“…This paper is related to a long line of recent work on program synthesis [1, 2, 6, 7, 22, 26-28, 32, 35, 36, 41, 42, 45-49, 53, 55]. While the goal of program synthesis is always to produce a program that satisfies the given specification, different synthesizers use different forms of specifications, including input-output examples [6,22,26,42,53], logical constraints [47][48][49], refinement types [41], or a reference implementation [27,35,45]. Our technique belongs in the latter category in that it uses the original implementation as the specification.…”

Section: Related Workmentioning

confidence: 99%

Synthesizing database programs for schema refactoring

Wang

Dong

Shah

et al. 2019

Proceedings of the 40th ACM SIGPLAN Conference on Programming Language Design and Implementation

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Many programs that interact with a database need to undergo schema refactoring several times during their life cycle. Since this process typically requires making significant changes to the program's implementation, schema refactoring is often non-trivial and error-prone. Motivated by this problem, we propose a new technique for automatically synthesizing a new version of a database program given its original version and the source and target schemas. Our method does not require manual user guidance and ensures that the synthesized program is equivalent to the original one. Furthermore, our method is quite efficient and can synthesize new versions of database programs (containing up to 263 functions) that are extracted from real-world web applications with an average synthesis time of 69.4 seconds.CCS Concepts • Software and its engineering → Programming by example; Automatic programming; • Information systems → Database utilities and tools.

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Section: Related Workmentioning

confidence: 99%

Synthesizing database programs for schema refactoring

Wang

Dong

Shah

et al. 2019

Proceedings of the 40th ACM SIGPLAN Conference on Programming Language Design and Implementation

View full text Add to dashboard Cite

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“…This is performed iteratively, beginning with points having the highest score (regardless of category) and proceeding downward in score. An optimized data structure automatically constructed using Cozy (Loncaric et al, 2016) holds the locations of drawn points and labels.…”

Section: Scattertextmentioning

confidence: 99%

Scattertext: a Browser-Based Tool for Visualizing how Corpora Differ

Kessler¹

2017

Proceedings of ACL 2017, System Demonstrations

103

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Scattertext is an open source tool for visualizing linguistic variation between document categories in a language-independent way. The tool presents a scatterplot, where each axis corresponds to the rankfrequency a term occurs in a category of documents. Through a tie-breaking strategy, the tool is able to display thousands of visible term-representing points and find space to legibly label hundreds of them. Scattertext also lends itself to a query-based visualization of how the use of terms with similar embeddings differs between document categories, as well as a visualization for comparing the importance scores of bag-of-words features to univariate metrics.

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“…Loncaric et al [18] extend the work of Hawkins et al by adding support for order among elements and complex retrieval operations. They generate intrusive data structures that avoid a layer of indirection by storing auxiliary pointers in domain elements directly, trading flexibility of generic collections for a potential increase in performance.…”

Section: Related Workmentioning

confidence: 99%

Towards a software product line of trie-based collections

Steindorfer

Vinju

2016

Proceedings of the 2016 ACM SIGPLAN International Conference on Generative Programming: Concepts and Experiences

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Collection data structures in standard libraries of programming languages are designed to excel for the average case by carefully balancing memory footprint and runtime performance. These implicit design decisions and hard-coded trade-offs do constrain users from using an optimal variant for a given problem. Although a wide range of specialized collections is available for the Java Virtual Machine (JVM), they introduce yet another dependency and complicate user adoption by requiring specific Application Program Interfaces (APIs) incompatible with the standard library.A product line for collection data structures would relieve library designers from optimizing for the general case. Furthermore, a product line allows evolving the potentially large code base of a collection family efficiently. The challenge is to find a small core framework for collection data structures which covers all variations without exhaustively listing them, while supporting good performance at the same time.We claim that the concept of Array Mapped Tries (AMTs) embodies a high degree of commonality in the sub-domain of immutable collection data structures. AMTs are flexible enough to cover most of the variability, while minimizing code bloat in the generator and the generated code. We implemented a Data Structure Code Generator (DSCG) that emits immutable collections based on an AMT skeleton foundation. The generated data structures outperform competitive handoptimized implementations, and the generator still allows for customization towards specific workloads.

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Fast synthesis of fast collections

Cited by 8 publications

References 28 publications

Synthesizing database programs for schema refactoring

Synthesizing database programs for schema refactoring

Scattertext: a Browser-Based Tool for Visualizing how Corpora Differ

Towards a software product line of trie-based collections

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