A list of awesome research on log analysis, anomaly detection, fault localization, and AIOps
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Updated
Dec 31, 2023
A list of awesome research on log analysis, anomaly detection, fault localization, and AIOps
Template Scripting Testing Language tool: automated test generation for Python
LLM-native static vulnerability detection: point it at a repo and get a reviewable vuln report, the way a human auditor would.
Tools for AI agents to test, fix and optimise your codebase
FLACOCO: Fault Localization for Java based on Industry-grade Coverage http://arxiv.org/pdf/2111.12513
An automated fault localization tool for Python programs.
Spectrum-based Fault Localization Engine
Experimental bed to study Linux faults
A program repair tool which modifies any bugged Python script based on cues from rest of program.
Source code of the paper "FirmRCA: Towards Post-Fuzzing Analysis on ARM Embedded Firmware with Efficient Event-based Fault Localization"
Implementation of the tarantula fault localisation algorithm
The AIOps library for automatic reduction of failure-unrelated metrics in Python
Structured code verification, fault localization, and semantic analysis — agent skill based on the Agentic Code Reasoning paper
Better Debugging: Combining Static Analysis and LLMs for Explainable Crashing Fault Localization
GenPark AI Agent Skill - Dynamically synthesizes and evaluates runtime assertions, pre/post-conditions, and state invariants to detect data corruption before crashes occur.
GenPark AI Agent Skill - Zeller's Delta Debugging (ddmin) algorithm minimizing failing code snippets, complex payloads, and config files to minimal reproducible examples (MRE).
GenPark AI Agent Skill - Parses Python stack traces into structured traceback frames, calculates Tarantula/Ochiai line suspiciousness scores, and isolates root-cause bug locations.
GenPark AI Agent Skill - Parses Python stack traces into structured traceback frames, calculates Tarantula/Ochiai line suspiciousness scores, and isolates root-cause bug locations.
GenPark AI Agent Skill - Synthesizes property-based and counterfactual unit test inputs (fuzzing boundary values, null states, edge cases) to reproduce runtime tool bugs.
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