Large language models for software engineering: A systematic literature review
Large Language Models (LLMs) have significantly impacted numerous domains, notably
including Software Engineering (SE). Nevertheless, a well-rounded understanding of the …
including Software Engineering (SE). Nevertheless, a well-rounded understanding of the …
Llmparser: A llm-based log parsing framework
The process of log parsing, which converts log messages into structured formats, is a crucial
step for various log analysis tasks. Although numerous log parsers have been proposed …
step for various log analysis tasks. Although numerous log parsers have been proposed …
LILAC: Log parsing using LLMs with adaptive parsing cache
Log parsing transforms log messages into structured formats, serving as the prerequisite
step for various log analysis tasks. Although a variety of log parsing approaches have been …
step for various log analysis tasks. Although a variety of log parsing approaches have been …
Autolog: A log sequence synthesis framework for anomaly detection
The rapid progress of modern computing systems has led to a growing interest in informative
run-time logs. Various log-based anomaly detection techniques have been proposed to …
run-time logs. Various log-based anomaly detection techniques have been proposed to …
Go static: Contextualized logging statement generation
Logging practices have been extensively investigated to assist developers in writing
appropriate logging statements for documenting software behaviors. Although numerous …
appropriate logging statements for documenting software behaviors. Although numerous …
[PDF][PDF] A Large-Scale Evaluation for Log Parsing Techniques: How Far Are We?
Log data is pivotal in activities like anomaly detection and failure diagnosis in the automated
maintenance of software systems. Due to their unstructured format, log parsing is often …
maintenance of software systems. Due to their unstructured format, log parsing is often …
Face It Yourselves: An LLM-Based Two-Stage Strategy to Localize Configuration Errors via Logs
Configurable software systems are prone to configuration errors, resulting in significant
losses to companies. However, diagnosing these errors is challenging due to the vast and …
losses to companies. However, diagnosing these errors is challenging due to the vast and …
[PDF][PDF] A Large-Scale Evaluation for Log Parsing Techniques: How Far Are We?
Log data have facilitated various tasks of software development and maintenance, such as
testing, debugging and diagnosing. Due to the unstructured nature of logs, log parsing is …
testing, debugging and diagnosing. Due to the unstructured nature of logs, log parsing is …
An Empirical Study of Unit Test Generation with Large Language Models
Unit testing is an essential activity in software development for verifying the correctness of
software components. However, manually writing unit tests is challenging and time …
software components. However, manually writing unit tests is challenging and time …
The Emerging Artifacts of Centralized Open-Code
In 2022, generative model based coding assistants became widely available with the public
release of GitHub Copilot. Approaches to generative coding are often critiqued within the …
release of GitHub Copilot. Approaches to generative coding are often critiqued within the …