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Found 11 papers, 3 papers with code
A Novel Approach for Automatic Program Repair using Round-Trip Translation with Large Language Models
We investigate whether this correction capability of Large Language Models (LLMs) extends to Automatic Program Repair (APR).
An Exploratory Literature Study on Sharing and Energy Use of Language Models for Source Code
Large language models trained on source code can support a variety of software development tasks, such as code recommendation and program repair.
The EarlyBIRD Catches the Bug: On Exploiting Early Layers of Encoder Models for More Efficient Code Classification
These findings show that early layers can be used to obtain better results using the same resources, as well as to reduce resource usage during fine-tuning and inference.
Constructing a Knowledge Graph from Textual Descriptions of Software Vulnerabilities in the National Vulnerability Database
Knowledge graphs have shown promise for several cybersecurity tasks, such as vulnerability assessment and threat analysis.
Fully Autonomous Programming with Large Language Models
Current approaches to program synthesis with Large Language Models (LLMs) exhibit a "near miss syndrome": they tend to generate programs that semantically resemble the correct answer (as measured by text similarity metrics or human evaluation), but achieve a low or even zero accuracy as measured by unit tests due to small imperfections, such as the wrong input or output format.
CHESS: A Framework for Evaluation of Self-adaptive Systems based on Chaos Engineering
There is an increasing need to assess the correct behavior of self-adaptive and self-healing systems due to their adoption in critical and highly dynamic environments.
On Evaluating Self-Adaptive and Self-Healing Systems using Chaos Engineering
In this paper, we propose CHESS, an approach for the systematic evaluation of self-adaptive and self-healing systems that builds on chaos engineering.
Featherweight Assisted Vulnerability Discovery
We also find that words are of greatest value in the datasets with a more homogeneous vocabulary.
CVEfixes: Automated Collection of Vulnerabilities and Their Fixes from Open-Source Software
Data-driven research on the automated discovery and repair of security vulnerabilities in source code requires comprehensive datasets of real-life vulnerable code and their fixes.
Adaptive Immunity for Software: Towards Autonomous Self-healing Systems
To help advance the state-of-the-art, we develop a research agenda for building self-healing software systems using AISs, identifying required foundations, and promising research directions.
Improving Problem Identification via Automated Log Clustering using Dimensionality Reduction
(2) How does dimensionality reduction affect the quality of automated log clustering?
