Programming by sketching for bit-streaming programs

By Armando Solar-Lezama, Rodric M. Rabbah, Rastislav Bodík, K. Ebcioglu. ACM-SIGPLAN Symposium on Programming Language Design and Implementation, 2005

305 citations recorded by the source corpus.

Subfields: Computer Science Applications, Hardware and Architecture, Mechanical Engineering

View Paper: https://www.semanticscholar.org/paper/f663cf55bf1bc4e5aaa61d98e73ae64065ecd530

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Citations in the corpus

Programming with a Differentiable Forth Interpreter (2016, background): “The core insight that enables this approach is the fact that programming languages can usually be formulated in terms of an abstract machine that executes the commands of the language.”
Neuro-Symbolic Program Synthesis (2016, methodology): “the back of the development of methods for learning programs in various domains, ranging from low-level bit manipulation code (Solar-Lezama et al., 2005) to data structure manipulations (Singh & Solar-Lezama, 2011) and regular expression based string transformations (Gulwani, 2011).”
Packet Transactions: High-Level Programming for Line-Rate Switches (2015, methodology): “esizer [90] for this purpose, as the atom templates can be easily expressed using SKETCH, while SKETCH also provides efﬁcient search algorithms and has been used for similar purposes in other domains [89,38,39,78]. As an illustration, assume we want to map the codelet x=x+1 to the atom template show”
Synthesis of loop-free programs (2011, methodology): “In this paper, we demonstrate how to semi-automate the discovery of small, but intricate, bitvector programs using the currently available formal veri.cation technology.”
Syntax-guided synthesis (2013, methodology): “For instance, in the programming approach advocated by the SKETCH system, a programmer writes a partial program with incomplete details, and the synthesizer fills in the missing details using user-specified assertions as the correctness specification [4].”
Formal verification of hybrid systems (2011, methodology): “Illustrative examples of this new view of synthesis include programming by examples for spreadsheet transformations in Microsoft Excel [27], and sketching of bit-streaming programs using program skeletons [51].”
Program synthesis by sketching (2008, methodology): “Many of the insights behind the Sketch language came from the lessons we learned through the user studies he encouraged us to undertake for the StreamBit system.”
SemFix: Program repair via semantic analysis (2013, background): “Such an approach would be more in the flavor of sketching [7], [8].”
Automated feedback generation for introductory programming assignments (2012, methodology): “Program synthesis has been used recently for many applications such as synthesis of efficient low-level code [29, 38], data structure manipulations [34], inference of efficient synchronization in concurrent programs [42], snippets of excel macros [18, 33], relational data representations [19, 20] an”
Expectation vs. Experience: Evaluating the Usability of Code Generation Tools Powered by Large Language Models (2022, background): “More recently, program synthesis has been applied to a variety of domains, e.g., low-level bit-vector implementations [36], data manipulation in excel [14], and regular expression synthesis [51].”
TerpreT: A Probabilistic Programming Language for Program Induction (2016, background): “, 2012; Polozov and Gulwani, 2015), inference of efficient synchronization in concurrent programs, synthesizing efficient low-level code from partial programs (Solar-Lezama et al., 2005), compilers for low-power spatial architectures (Phothilimthana et al.”