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About 10,000 papers for “Line code”

Execution Guided Line-by-Line Code Generation

Boaz Lavon, Shmuel Katz, Lior Wolf · ArXiv.org · 2025

We present a novel approach to neural code generation that incorporates real-time execution signals into the language model generation process. While large language models (LLMs) have demonstrated impressive code generation capabilities, they typically do not utilize execution feedback during inference, a critical signal that human programmers regularly leverage. Our method, Execution-Guided Classifier-Free Guidance (EG-CFG), dynamically incorporates execution signals as the model generates code, providing line-by-line feedback that guides the generation process toward executable solutions. EG-CFG employs a multi-stage process: first, we conduct beam search to sample candidate program completions for each line; second, we extract execution signals by executing these candidates against test cases; and finally, we incorporate these signals into the prompt during generation. By maintaining consistent signals across tokens within the same line and refreshing signals at line boundaries, our approach provides coherent guidance while preserving syntactic structure. Moreover, the method naturally supports native parallelism at the task level in which multiple agents operate in parallel, exploring diverse reasoning paths and collectively generating a broad set of candidate solutions. Our experiments across diverse coding tasks demonstrate that EG-CFG significantly improves code generation performance compared to standard approaches, achieving state-of-the-art results across various levels of complexity, from foundational problems to challenging competitive programming and data science tasks. Our code is available at: https://github.com/boazlavon/eg_cfg

Cited by 0Open access

Programme for line code demonstration

Zelený, Ondřej · Brno University of Technology Digital Library (Brno University of Technology) · 2020

Tato semestrální práce má za cíl návrh základních funkcí pro generování nejpoužívanějších linkových kódů, nastavování parametrů generátoru a přenost dat z PC do generátoru. Teoretická část se zabívá rozborem jednotlivých linkových kódů a popisem pravidel pro jejich generování. Praktická část se poté věnuje samotné implementaci pravidel v programovacím prostředí Matlab.

Cited by 0

Command-line QR Code generator

Augusto P. Goulart · Zenodo (CERN European Organization for Nuclear Research) · 2026

An ISO 18004 compliant QR Code generator for the terminal, capable of outputting as a bitmap or vector image.

Cited by 0Open access

Command-line QR Code generator

Goulart, Augusto · Zenodo (CERN European Organization for Nuclear Research) · 2026

An ISO 18004 compliant QR Code generator for the terminal, capable of outputting as a bitmap or vector image.

Cited by 0Open access

Line-by-line code ILBL from 26 Aug 2022

Notholt, Justus · Zenodo (CERN European Organization for Nuclear Research) · 2023

High resolution line-by-line code to calculate the radiation in the atmosphere, including the temperature evolution.

Cited by 1Open access

Line-by-line code ILBL from 26 Aug 2022

Notholt, Justus · Zenodo (CERN European Organization for Nuclear Research) · 2023

High resolution line-by-line code to calculate the radiation in the atmosphere, including the temperature evolution.

Cited by 0Open access

SCRAM: not a line shape code.

Hansen, Stephanie B. · OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information) · 2020

Abstract not provided.

Cited by 0Open access

Learning to Schedule Straight-Line Code

Eliot Moss, Paul Utgoff, John Cavazos et al. · 1997

Execution speed of programs on modern computer architectures is sensitive, by a factor of two or more, to the order in which instructions are presented to the processor. To realize potential execution efficiency, it is now customary for an optimizing compiler to employ a heuristic algorithm for instruction scheduling. These algorithms are painstakingly hand-crafted, which is expenseive and time-consuming. We show how to cast the instruction scheduling problem as a learning task, so that one obtains the heuristic scheduling algorithm automatically. Our focus is the narrower problem of scheduling straight-line code, also known as a basic block of instructions. Our empirical results show that just a few features are adequate for quite good performance at this task for a real modern processor, and that any of several supervised learning methods perform nearly optimally with respect to the features used. Category: Applications (compiler optimization) Original: This work has not been submi...

Cited by 5