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20242026
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6 papers · 1 filter

cs.SE2026

Cleaning Logs for Downstream Tasks (Registered Report)

Zahra G. Yazdi, Van-Hoang Le, Nyyti Saarimäki +3

Background: Software systems generate logs during execution to record critical events and runtime information for troubleshooting and monitoring. However, in practice, logs often c…

cs.SE2026

Syntax-driven Incremental Program Verification of Matching Logic Properties

Domenico Bianculli, Antonio Filieri, Carlo Ghezzi +2

Incrementality is a fundamental design principle to master the complexity of large, long-lived software systems. This principle has been embraced by agile development processes and…

cs.SE2025

LLM meets ML: Data-efficient Anomaly Detection on Unstable Logs

Fatemeh Hadadi, Qinghua Xu, Domenico Bianculli +1

Most log-based anomaly detectors assume logs are stable, though logs are often unstable due to software or environmental changes. Anomaly detection on unstable logs (ULAD) is there…

cs.SE2025

A Comprehensive Study of Machine Learning Techniques for Log-Based Anomaly Detection

Shan Ali, Chaima Boufaied, Domenico Bianculli +2

Growth in system complexity increases the need for automated log analysis techniques, such as Log-based Anomaly Detection (LAD). While deep learning (DL) methods have been widely u…

cs.SE2024

Impact of Log Parsing on Deep Learning-Based Anomaly Detection

Zanis Ali Khan, Donghwan Shin, Domenico Bianculli +1

Software systems log massive amounts of data, recording important runtime information. Such logs are used, for example, for log-based anomaly detection, which aims to automatically…

cs.SE2024

Systematic Evaluation of Deep Learning Models for Log-based Failure Prediction

Fatemeh Hadadi, Joshua H. Dawes, Donghwan Shin +2

With the increasing complexity and scope of software systems, their dependability is crucial. The analysis of log data recorded during system execution can enable engineers to auto…