User-Customizable Transpilation of Scripting Languages
Bo Wang, Aashish Kolluri, Ivica Nikoli\'c, Teodora Baluta, Prateek, Saxena

TL;DR
This paper introduces DuoGlot, a novel transpiler that enables fine-grained, user-guided customization of code translation from Python to Javascript, achieving high accuracy and producing readable code.
Contribution
The paper presents a new incremental, rule-based transpilation approach that allows user-guided customization without requiring understanding of global semantics.
Findings
DuoGlot achieves 90% translation accuracy on GeeksForGeeks benchmarks.
DuoGlot outperforms existing transpilers in accuracy.
Produced code is readable and maintains application-specific goals.
Abstract
A transpiler converts code from one programming language to another. Many practical uses of transpilers require the user to be able to guide or customize the program produced from a given input program. This customizability is important for satisfying many application-specific goals for the produced code such as ensuring performance, readability, maintainability, compatibility, and so on. Conventional transpilers are deterministic rule-driven systems often written without offering customizability per user and per program. Recent advances in transpilers based on neural networks offer some customizability to users, e.g. through interactive prompts, but they are still difficult to precisely control the production of a desired output. Both conventional and neural transpilation also suffer from the "last mile" problem: they produce correct code on average, i.e., on most parts of a given…
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Taxonomy
TopicsAdversarial Robustness in Machine Learning · Parallel Computing and Optimization Techniques · Software Engineering Research
