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A list of awesome research on log analysis, anomaly detection, fault localization, and AIOps
https://github.com/logpai/awesome-log-analysis
List: awesome-log-analysis
aiops anamoly-detection bug-finding failure-diagnosis fault-localization log-analysis
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A list of awesome research on log analysis, anomaly detection, fault localization, and AIOps
Host: GitHub
URL: https://github.com/logpai/awesome-log-analysis
Owner: logpai
License: mit
Created: 2018-03-09T07:00:46.000Z (over 6 years ago)
Default Branch: master
Last Pushed: 2023-12-31T14:10:09.000Z (10 months ago)
Last Synced: 2024-04-10T15:05:38.352Z (7 months ago)
Topics: aiops, anamoly-detection, bug-finding, failure-diagnosis, fault-localization, log-analysis
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- Readme: README.md
- License: LICENSE
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awesome-machine-learning-resources - **[List - log-analysis?style=social) (Table of Contents)
ultimate-awesome - awesome-log-analysis - A list of awesome research on log analysis, anomaly detection, fault localization, and AIOps. (Other Lists / PowerShell Lists)
README

        
  


# Awesome Log Analysis

A curated list of awesome publications and researchers on log analysis, anomaly detection, fault localization, and AIOps.

- [Awesome Log Analysis](#awesome-log-analysis)

  - [Researchers](#researchers)

  - [Conferences and Journals](#conferences-and-journals)

  - [Datasets](#datasets)

  - [Papers](#papers)

    - [Surveys & Tutorials & Magazines](#surveys--tutorials--magazines)

    - [Logging](#logging)

    - [Log Compression](#log-compression)

    - [Log Parsing](#log-parsing)

    - [Log Mining](#log-mining)

      - [Anomaly Detection](#anomaly-detection)

      - [Failure Prediction](#failure-prediction)

      - [Failure Diagnosis](#failure-diagnosis)

      - [Others](#others)

  - [License](#license)

## Researchers

| China (& HK SAR) | ||||

| :---------| :------ | :------ | :------ | :------ |

| [Michael R. Lyu](http://www.cse.cuhk.edu.hk/lyu/), CUHK | [Dongmei Zhang](https://www.microsoft.com/en-us/research/people/dongmeiz/), Microsoft | [Pengfei Chen](http://sdcs.sysu.edu.cn/content/3747), SYSU | [Dan Pei](https://netman.aiops.org/~peidan/), Tsinghua | |

| [Pinjia He](https://pinjiahe.github.io/), CUHK-Shenzhen|

| **USA** |||||

| [Yuanyuan Zhou](https://cseweb.ucsd.edu/~yyzhou/), UCSD | [Tao Xie](http://taoxie.cs.illinois.edu/), UIUC | [Dawson Engler](http://web.stanford.edu/~engler/), Stanford | [Ben Liblit](http://pages.cs.wisc.edu/~liblit/#bug-isolation), Wisconsin–Madison ||

| **Canada** |||||

| [Ding Yuan](http://www.eecg.toronto.edu/~yuan/Home.html), Toronto University | [Ahmed E. Hassan](http://research.cs.queensu.ca/~ahmed/home/), Queen's University | [Weiyi Shang](https://users.encs.concordia.ca/~shang/), Concordia University |[Zhen Ming (Jack) Jiang](http://www.cse.yorku.ca/~zmjiang/), York University||

| [Wahab Hamou-Lhadj](https://users.encs.concordia.ca/~abdelw/), Concordia University|

| **UK** |||||

|  |||||

| **Europe** |||||

|  |||||

| **Australia** |||||

| [Ingo Weber](https://people.csiro.au/W/I/Ingo-Weber), CSIRO |||||

## Conferences and Journals

Logs are a type of valuable data generated from many sources such as software, systems, networks, devices, etc. They have also been used for a number of tasks related to reliability, security, performance, and energy. Therefore, the research of log analysis has attracted interests from different research areas.

+ **System area**

    + Conferences: [OSDI](https://dblp.uni-trier.de/db/conf/osdi/index) | [SOSP](https://dblp.uni-trier.de/db/conf/sosp/index) | [ATC](https://dblp.uni-trier.de/db/conf/usenix/index) | [ICDCS](https://dblp.uni-trier.de/db/conf/icdcs/index)

    + Journals: [TC](https://dblp.uni-trier.de/db/journals/tc/index.html) | [TOCS](https://dblp.uni-trier.de/db/journals/tocs/index) | [TPDS](https://dblp.uni-trier.de/db/journals/tpds/index.html)

+ **Cloud computing area**

    + Conferences: [SoCC](https://dblp.uni-trier.de/db/conf/cloud/index.html) | [CLOUD](https://dblp.uni-trier.de/db/conf/IEEEcloud/index)

    + Journals: [TCC](https://dblp.uni-trier.de/db/journals/tcc/index.html)

+ **Networking area**

    + Conferences: [NSDI](https://dblp.uni-trier.de/db/conf/nsdi/index) | [INFOCOMM](https://dblp.uni-trier.de/db/conf/infocom/index)

    + Journals: [TON](https://dblp.uni-trier.de/db/journals/ton/index.html)

+ **Software engineering area**

    + Conferences: [ICSE](https://dblp.uni-trier.de/db/conf/icse/index) | [FSE](https://dblp.uni-trier.de/db/conf/sigsoft/index) | [ASE](https://dblp.org/db/conf/kbse/index.html)

    + Journals: [TSE](https://dblp.org/db/journals/tse/index) | [TOSEM](https://dblp.uni-trier.de/db/journals/tosem/index)

+ **Reliability area**

    + Conferences: [DSN](https://dblp.uni-trier.de/db/conf/dsn/index) | [ISSRE](https://dblp.uni-trier.de/db/conf/issre/index.html) | [SRDS](https://dblp.uni-trier.de/db/conf/srds/index)

    + Journals: [TDSC](https://ieeexplore.ieee.org/xpl/RecentIssue.jsp?punumber=8858) | [TR](https://ieeexplore.ieee.org/xpl/RecentIssue.jsp?punumber=24)

+ **Security area**

    + Conferences: [CCS](http://www.wikicfp.com/cfp/servlet/event.showcfp?eventid=83847) | [DSN](http://www.dsn.org/)

    + Journals: [TDSC](https://dblp.uni-trier.de/db/journals/tdsc/index.html)

+ **AI and Bigdata area**

    + Conferences: [KDD](https://dblp.uni-trier.de/db/conf/kdd/index) | [CIKM](https://dblp.uni-trier.de/db/conf/cikm/index) | [ICDM](https://dblp.uni-trier.de/db/conf/icdm/index) | [BigData](https://dblp.org/db/conf/bigdataconf/index)

    + Journals: [TKDE](https://dblp.uni-trier.de/db/journals/tkde/index) | [TBD](https://dblp.uni-trier.de/db/journals/tbd/index.html)

+ **Industrial conferences**

    + [SREcon](https://www.usenix.org/conferences/byname/925) | [GOPS](https://www.bagevent.com/event/GOPS2019-shenzhen?bag_track=bagevent)

## Datasets

Loghub

## Papers

### Surveys & Tutorials & Magazines

1. [**ACM Computing Survey**] [A Survey on Automated Log Analysis for Reliability Engineering](https://arxiv.org/abs/2009.07237)

1. [**Blog**] [What is AIOps? Artificial Intelligence for IT Operations Explained](http://www.bmc.com/blogs/what-is-aiops/)

1. [**Book'14**] [I Heart Logs](https://www.oreilly.com/library/view/i-heart-logs/9781491909379/)

1. [**Book'12**] [Logging and Log Management: The Authoritative Guide to Understanding the Concepts Surrounding Logging and Log Management](http://mirror.thelifeofkenneth.com/sites/qt.vidyagam.es/library/Forensics/Logging%20and%20Log%20Management_%20The%20Authoritats%20Surrounding%20Logging%20and%20Log%20Management/Logging%20and%20Log%20Management_%20The%20Authoritative%20Guide%20to%20Undeanagement%20-%20Anton%20Chuvakin%20&%20Kevin%20Schmidt%20&%20Chris%20Phillips.pdf), by Anton A. Chuvakin, Kevin J. Schmidt, Christopher Phillips.

1. [**Thesis**] [Log Engineering: Towards Systematic Log Mining to Support the Development of Ultra-large Scale Systems](https://users.encs.concordia.ca/~shang/pubs/2014_LogEngineering_TowardsSystematicLogMiningToSupportTheDevelopmentOfUltra-largeScaleSystems.pdf)

1. [**IST'20**] [A Systematic Literature Review on Automated Log Abstraction Techniques](https://www.sciencedirect.com/science/article/pii/S0950584920300264)

1. [**IEEE Software'16**] [Operational-Log Analysis for Big Data Systems: Challenges and Solutions](https://www.computer.org/csdl/magazine/so/2016/02/mso2016020052/13rRUzp02mr)

### Logging

- [OSDI 2012] [Be Conservative: Enhancing Failure Diagnosis with Proactive Logging](https://www.eecg.utoronto.ca/~yuan/papers/osdi12-errlog.pdf)

- [TSE 2013] [Event Logs for the Analysis of Software Failures: A Rule-Based Approach](http://ieeexplore.ieee.org/document/6320555/)

- [ICSE 2015] [Learning to Log: Helping Developers Make Informed Logging Decisions](http://ieeexplore.ieee.org/document/7194593/)

- [ICSE 2015] [Where do developers log? an empirical study on logging practices in industry](http://dl.acm.org/citation.cfm?doid=2591062.2591175)

- [ATC 2015] [Log2 : A Cost-Aware Logging Mechanism for Performance Diagnosis](https://www.usenix.org/system/files/conference/atc15/atc15-paper-ding.pdf)

- [SOSP 2017] [Log20: Fully Automated Optimal Placement of Log Printing Statements under Specified Overhead Threshold](http://log20.dsrg.utoronto.ca/log20_sosp17_paper.pdf)

- [HotOS 2017] [The Game of Twenty Questions: Do You Know Where to Log?](https://dl.acm.org/doi/10.1145/3102980.3103001)

- [ASE 2020] [Where Shall We Log? Studying and Suggesting Logging Locations in Code Blocks](https://users.encs.concordia.ca/~shang/pubs/Zhenhao_ASE20.pdf)

- [ASPLOS 2011] [Improving Software Diagnosability via Log Enhancement](http://opera.ucsd.edu/paper/asplos11-logenhancer.pdf)

- [ASE 2018] [Characterizing the Natural Language Descriptions in Software Logging Statements](https://pinjiahe.github.io/papers/ASE18.pdf)

- [TSE 2019] [Which Variables Should I Log?](https://xin-xia.github.io/publication/tse197.pdf)

- [ICPC 2019] [PADLA: a dynamic log level adapter using online phase detection](https://sel.ist.osaka-u.ac.jp/lab-db/betuzuri/archive/1157/1157.pdf)

- [ECOOP 1997] [Aspect-oriented programming](https://www.cs.ubc.ca/~gregor/papers/kiczales-ECOOP1997-AOP.pdf)

- [DSN 2010] [Assessing and improving the effectiveness of logs for the analysis of software faults](http://ieeexplore.ieee.org/document/5544279/)

- [ICSE 2012] [Characterizing logging practices in open-source software](http://petertsehsun.github.io/soen691/current/papers/log_icse12.pdf)

- [ICSME 2014] [Understanding Log Lines Using Development Knowledge](http://ieeexplore.ieee.org/document/6976068/)

- [ICSE 2015] [Industry practices and event logging: assessment of a critical software development process](https://dl.acm.org/doi/10.5555/2819009.2819035)

- [ESE 2015] [Studying the relationship between logging characteristics and the code quality of platform software](http://link.springer.com/10.1007/s10664-013-9274-8)

- [ICSE 2017] [Characterizing and Detecting Anti-patterns in the Logging Code](https://dl.acm.org/doi/pdf/10.1109/ICSE.2017.15)

- [OSDI 2018] [The FuzzyLog: A Partially Ordered Shared Log](https://www.usenix.org/conference/osdi18/presentation/lockerman)

- [ATC 2018] [Troubleshooting Transiently-Recurring Errors in Production Systems with Blame-Proportional Logging](https://www.usenix.org/system/files/conference/atc18/atc18-luo.pdf)

- [ATC 2018] [NanoLog: A Nanosecond Scale Logging System](https://www.usenix.org/system/files/conference/atc18/atc18-yang.pdf)

- [NSDI 2018] [Carousel: Scalable Logging for Intrusion Prevention Systems](https://www.usenix.org/conference/nsdi10-0/carousel-scalable-logging-intrusion-prevention-systems)

- [ICSE 2019] [DLFinder: Characterizing and Detecting Duplicate Logging Code Smells](https://users.encs.concordia.ca/~shang/pubs/icse2019_zhenhao.pdf)

- [ICSE 2016] [The bones of the system: a case study of logging and telemetry at Microsoft](http://dl.acm.org/citation.cfm?doid=2889160.2889231)

- [MSR 2016] [Logging library migrations: a case study for the apache software foundation projects](http://dl.acm.org/citation.cfm?doid=2901739.2901769)

- [ESE 2017] [Characterizing logging practices in Java-based open source software projects - a replication study in Apache Software Foundation](http://link.springer.com/10.1007/s10664-016-9429-5)

- [ESE 2018] [Studying and detecting log-related issues](http://link.springer.com/10.1007/s10664-018-9603-z)

- [ESE 2018] [Examining the stability of logging statements](http://link.springer.com/10.1007/s10664-017-9518-0)

- [ESE 2018] [An exploratory study on assessing the energy impact of logging on Android applications](https://www.eecs.yorku.ca/~zmjiang/publications/emse2017_chowdhury.pdf)

- [ESE 2019] [Studying the characteristics of logging practices in mobile apps: a case study on F-Droid](http://link.springer.com/10.1007/s10664-019-09687-9)

- [ICSE 2020] [Studying the Use of Java Logging Utilities in the Wild](http://www.cse.yorku.ca/~zmjiang/publications/icse2020_chen.pdf)

- [EMSE 2022] [The Sense of Logging in the Linux Kernel](https://users.encs.concordia.ca/~abdelw/papers//EMSE22_LinuxLogs.pdf)

### Log Compression

- [IPDPS 2006] [Lossless compression for large scale cluster logs](https://ieeexplore.ieee.org/document/1639692)

- [ADBIS 2007] [Fast and efficient log file compression](http://www.adbis.org/docs/lp/6.pdf)

- [ICSE 2008] [An Industrial Case Study of Customizing Operational Profiles Using Log Compression](https://dl.acm.org/doi/abs/10.1145/1368088.1379445)

- [SIGMOD 2013] [Adaptive log compression for massive log data](https://dl.acm.org/doi/10.1145/2463676.2465341)

- [IEEE Trustcom/BigDataSE/ISPA 2016] [MLC: An Efficient Multi-level Log Compression Method for Cloud Backup Systems](https://ieeexplore.ieee.org/document/7847098/)

- [TCSET 2008] [Sub-atomic field processing for improved web log compression](https://ieeexplore.ieee.org/document/5423436)

- [CCGRID 2015] [Cowic: A column-wise independent compression for log stream analysis](https://ieeexplore.ieee.org/document/7152468)

- [IMCC 2014] [Lightweight Packing of Log Files for Improved Compression in Mobile Tactical Networks](https://ieeexplore.ieee.org/document/6956758)

- [DCC 2004] [High density compression of log files](https://ieeexplore.ieee.org/document/1281533)

- [DaWaK 2003] [Comprehensive Log Compression with Frequent Patterns](https://link.springer.com/chapter/10.1007/978-3-540-45228-7_36)

- [ICEIS 2019] [Rough Logs: A Data Reduction Approach for Log Files](https://www.scitepress.org/Papers/2019/77351/pdf/index.html)

- [ASE 2019] [Logzip: extracting hidden structures via iterative clustering for log compression](https://arxiv.org/abs/1910.00409)

- [EMSE 2019] [A Study of the Performance of General Compressors on Log Files](https://users.encs.concordia.ca/~shang/pubs/Kundi_EMSE2020.pdf)

- [Ph.D. Dissertation 2008] [Using semantic knowledge to improve compression on log files](https://homes.cs.ru.ac.za/B.Irwin/theses/Otten%202008%20%20Msc%20Using%20semantic%20knowledge%20to%20improve%20compression%20on%20log%20files.pdf)

### Log Parsing

- [IPOM'03] [A Data Clustering Algorithm for Mining Patterns from Event Logs](http://www.quretec.com/u/vilo/edu/2003-04/DM_seminar_2003_II/ver1/P12/slct-ipom03-web.pdf)

- [QSIC'08] [Abstracting Execution Logs to Execution Events for Enterprise Applications](https://www.researchgate.net/publication/4366728_Abstracting_Execution_Logs_to_Execution_Events_for_Enterprise_Applications_Short_Paper)

- [ICDM'09] [Execution Anomaly Detection in Distributed Systems through Unstructured Log Analysis](https://www.microsoft.com/en-us/research/wp-content/uploads/2016/02/DM790-CR.pdf)

- [MSR'10] [Abstracting Log Lines to Log Event Types for Mining Software System Logs](http://www.se.rit.edu/~mei/publications/pdfs/Abstracting-Log-Lines-to-Log-Event-Types-for-Mining-Software-System-Logs.pdf)

- [CIKM'11] [LogSig: Generating System Events from Raw Textual Logs](https://users.cs.fiu.edu/~taoli/pub/liang-cikm2011.pdf) 

- [KDD'09] [Clustering Event Logs Using Iterative Partitioning](https://web.cs.dal.ca/~makanju/publications/paper/kdd09.pdf)

- [TKDE'12] [A Lightweight Algorithm for Message Type Extraction in System Application Logs](https://ieeexplore.ieee.org/document/5936060)

- [CNSM'15] [LogCluster - A Data Clustering and Pattern Mining Algorithm for Event Logs](http://dl.ifip.org/db/conf/cnsm/cnsm2015/1570161213.pdf)

- [CIKM'16] [LogMine: Fast Pattern Recognition for Log Analytics](http://www.cs.unm.edu/~mueen/Papers/LogMine.pdf)

- [TDSC'18] [Towards Automated Log Parsing for Large-Scale Log Data Analysis](https://pinjiahe.github.io/papers/TDSC17.pdf)

- [ICPC'18] [A Search-based Approach for Accurate Identification of Log Message Formats](http://publications.uni.lu/bitstream/10993/35286/1/ICPC-2018.pdf)

- [SCC'13] [Incremental Mining of System Log Format](http://ieeexplore.ieee.org/document/6649746/)

- [arXiv'15] [Length Matters: Clustering System Log Messages using Length of Words](https://arxiv.org/pdf/1611.03213.pdf)

- [TKDE'18] [Spell: Online Streaming Parsing of Large Unstructured System Logs](https://ieeexplore.ieee.org/document/8489912)

- [ICWS'17] [Drain: An Online Log Parsing Approach with Fixed Depth Tree](https://jiemingzhu.github.io/pub/pjhe_icws2017.pdf)

- [arXiv'18] [A Directed Acyclic Graph Approach to Online Log Parsing](https://arxiv.org/abs/1806.04356)

- [TSE'20] [Logram: Efficient Log Parsing Using n-Gram Dictionaries](https://arxiv.org/abs/2001.03038)

- [ICSE-SEIP'19] [Tools and benchmarks for automated log parsing](https://arxiv.org/abs/1811.03509)

- [ICSME'22] [An Effective Approach for Parsing Large Log Files](https://users.encs.concordia.ca/~abdelw/papers/ICSME2022_ULP.pdf)

### Log Mining

#### Anomaly Detection

- [OSDI 2016] [Non-intrusive performance profiling for entire software stacks based on the flow reconstruction principle](https://www.usenix.org/system/files/conference/osdi16/osdi16-zhao.pdf)

- [FSE 2018] [Using finite-state models for log differencing](https://www.cs.tau.ac.il/~maozs/papers/log-diff-fse18.pdf)

- [ICSE 2016] [Behavioral log analysis with statistical guarantees](https://www.cs.tau.ac.il/~maozs/papers/sg-icse16.pdf#:~:text=Behavioral%20Log%20Analysis%20with%20Statistical%20Guarantees%20Nimrod%20Busany,temporal%20properties%20from%20logs%20generated%20by%20run-ning%20systems.)

- [FSE 2011] [Leveraging existing instrumentation to automatically infer invariant-constrained models](https://www.cs.ubc.ca/~bestchai/papers/esecfse2011-final.pdf)

- [KDD 2010] [Mining program workflow from interleaved traces](https://dl.acm.org/doi/10.1145/1835804.1835883)

- [ICSE 2014] [Inferring models of concurrent systems from logs of their behavior with CSight](https://dl.acm.org/doi/10.1145/2568225.2568246)

- [ASE 2019] [Statistical log differencing](http://www.mysmu.edu/faculty/davidlo/papers/ase19-sld.pdf)

- [SOSP 2009] [Detecting Large-Scale System Problems by Mining Console Logs](https://www2.eecs.berkeley.edu/Pubs/TechRpts/2009/EECS-2009-103.pdf)

- [IPOM 2003] [A data clustering algorithm for mining patterns from event logs](https://ristov.github.io/publications/slct-ipom03-web.pdf)

- [FSE 2018] [Identifying impactful service system problems via log analysis](https://shilinhe.github.io/media/papers/fse18.pdf)

- [ICSE 2016] [Log clustering based problem identification for online service systems](https://dl.acm.org/doi/pdf/10.1145/2889160.2889232)

- [ICDM 2007] [Failure prediction in ibm bluegene/l event logs](https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=4470294)

- [IEICE Transactions on Communications 2018] [Proactive failure detection learning generation patterns of large-scale network logs](https://dl.acm.org/doi/10.1109/CNSM.2015.7367332)

- [ISSRE 2015] [Experience report: Anomaly detection of cloud application operations using log and cloud metric correlation analysis](https://ieeexplore.ieee.org/document/7381796)

- [USENIX ATC 2010] [Mining Invariants from Console Logs for System Problem Detection](https://dl.acm.org/doi/10.5555/1855840.1855864)

- [ICSE 2013] [Assisting developers of big data analytics applications when deploying on hadoop clouds](http://www.cse.yorku.ca/~zmjiang/publications/ICSE2013_Shang.pdf)

- [ICDM 2009] [Online system problem detection by mining patterns of console logs](https://people.eecs.berkeley.edu/~jordan/papers/xu-etal-icdm09.pdf)

- [ISSRE 2017] [Experience report: Log-based behavioral differencing](https://ieeexplore.ieee.org/document/8109094)

- [KDD 2016] [Anomaly detection using program control flow graph mining from execution logs](https://www.kdd.org/kdd2016/papers/files/adf1233-nandiA.pdf)

- [ICDM 2009] [Execution Anomaly Detection in Distributed Systems through Unstructured Log Analysis](https://www.microsoft.com/en-us/research/wp-content/uploads/2016/02/DM790-CR.pdf)

- [ASPLOS 2016] [Cloudseer: Workflow monitoring of cloud infrastructures via interleaved logs](https://people.engr.ncsu.edu/gjin2/asplos-2016-cloudseer.pdf)

- [KDD 2005] [Dynamic syslog mining for network failure monitoring](https://dl.acm.org/doi/10.1145/1081870.1081927)

- [ISSRE 2016] [Experience report: System log analysis for anomaly detection](https://ieeexplore.ieee.org/document/7774521/)

- [CCS 2017] [Deeplog: Anomaly detection and diagnosis from system logs through deep learning](https://www.cs.utah.edu/~lifeifei/papers/deeplog.pdf)

- [FSE 2019] [Robust log-based anomaly detection on unstable log data](https://dl.acm.org/doi/pdf/10.1145/3338906.3338931)

- [IJCAI 2019] [LogAnomaly: Unsupervised Detection of Sequential and Quantitative Anomalies in Unstructured Logs](https://www.ijcai.org/Proceedings/2019/0658.pdf)

- [ICCCN 2020] [Semantic-aware Representation Framework for Online Log Analysis](http://nkcs.iops.ai/wp-content/uploads/2020/05/paper-ICCCN20-Log2Vec.pdf)

- [TCCN 2020] [An Intelligent Anomaly Detection Scheme for Micro-services Architectures with Temporal and Spatial Data Analysis](https://ieeexplore.ieee.org/document/8957683)

- [ISSRE 2020] [Cross-System Log Anomaly Detection for Software Systems (to appear)]

- [Information Systems Frontiers 2020] [LogGAN: a Log-level Generative Adversarial Network for Anomaly Detection using Permutation Event Modeling](https://link.springer.com/article/10.1007/s10796-020-10026-3)

- [DASC/PiCom/DataCom/CyberSciTech 2018] [Detecting anomaly in big data system logs using convolutional neural network](https://ieeexplore.ieee.org/document/8511880)

- [CCS 2019] [Log2vec: A Heterogeneous Graph Embedding Based Approach for Detecting Cyber Threats within Enterprise](https://dl.acm.org/doi/10.1145/3319535.3363224)

- [MLCS 2018] [Recurrent Neural Network Attention Mechanisms for Interpretable System Log Anomaly Detection](https://dl.acm.org/doi/pdf/10.1145/3217871.3217872)

#### Failure Prediction

- [MACS18] [PreFix: Switch failure prediction in datacenter networks](https://doi.org/10.1145/3179405)

- [HPDC18] [Desh: deep learning for system health prediction of lead times to failure in HPC](https://doi.org/10.1145/3208040.3208051)

- [KDD03] [Critical event prediction for proactive management in large-scale computer clusters](https://doi.org/10.1145/956750.956799)

- [IPDPS20] [Aarohi: Making real-time node failure prediction feasible](https://doi.org/10.1109/IPDPS47924.2020.00115)

- [CLUSTER17] [Data Mining-Based Analysis of HPC Center Operations](https://doi.org/10.1109/CLUSTER.2017.23)

- [CLUSTER14] [Exploring void search for fault detection on extreme scale systems](https://doi.org/10.1109/CLUSTER.2014.6968757)

- [WWW19] [Outage Prediction and Diagnosis for Cloud Service Systems](http://dl.acm.org/citation.cfm?doid=3308558.3313501)

- [FSE18] [Predicting Node failure in cloud service systems](http://dl.acm.org/citation.cfm?doid=3236024.3236060)

- [FSE19] [Latent error prediction and fault localization for microservice applications by learning from system trace logs](http://dl.acm.org/citation.cfm?doid=3338906.3338961)

#### Failure Diagnosis

- [ICSE 2019] [An empirical study on leveraging logs for debugging production failures](https://dl.acm.org/doi/10.1109/ICSE-Companion.2019.00055)

- [ASPLOS 2016] [SherLog: error diagnosis by connecting clues from run-time logs](http://opera.ucsd.edu/paper/asplos10-sherlog.pdf)

- [ISSTA 2009] [AVA:automated interpretation of dynamically detected anomalies](https://dl.acm.org/doi/pdf/10.1145/1572272.1572300)

- [IC2E 2016] [LOGAN: Problem diagnosis in the cloud using log-based reference models](https://ieeexplore.ieee.org/document/7484164)

- [ICWS 2017] [An approach for anomaly diagnosis based on hybrid graph model with logs for distributed services](https://ieeexplore.ieee.org/document/8029741)

- [Cloud 2017] [Logsed: Anomaly diagnosis through mining time-weighted control flow graph in logs](https://ieeexplore.ieee.org/document/8030620) 

- [FSE 2018] [CloudRaid: hunting concurrency bugs in the cloud via log-mining](https://dl.acm.org/doi/abs/10.1145/3236024.3236071)

- [TPDS 2013] [Toward fine-grained, unsupervised, scalable performance diagnosis for production cloud computing systems](https://ieeexplore.ieee.org/document/6410318)

- [CLUSTER 2014] [Digging deeper into cluster system logs for failure prediction and root cause diagnosis](https://ieeexplore.ieee.org/document/6968768)

- [ASPLOS 2014] [Comprehending performance from real-world execution traces: A device-driver case](https://dl.acm.org/doi/10.1145/2644865.2541968)

- [ICWS 2017] [Log-based abnormal task detection and root cause analysis for spark](https://ieeexplore.ieee.org/document/8029786)

- [EDCC 2015] [Insights into the diagnosis of system failures from cluster message logs](https://ieeexplore.ieee.org/abstract/document/7371970)

- [HPC 2010] [Diagnosing the root-causes of failures from cluster log files](https://ieeexplore.ieee.org/document/5713159)

- [ASE 2019] [SCMiner: localizing system-level concurrency faults from large system call traces](https://ieeexplore.ieee.org/document/8952396)

- [NSDI 2012] [Structured comparative analysis of systems logs to diag- nose performance problems](https://www.usenix.org/system/files/conference/nsdi12/nsdi12-final61.pdf)

- [ICSE 2013] [Assisting developers of big data analytics applications when deploying on hadoop clouds](https://ieeexplore.ieee.org/document/6606586)

- [TPDS 2016] [Failure diagnosis for distributed systems using targeted fault injection](https://ieeexplore.ieee.org/document/7484300)

- [ICSE 2017] [What causes my test alarm? Automatic cause analysis for test alarms in system and integration testing](https://dl.acm.org/doi/10.1109/ICSE.2017.71)

- [GLOBECOM 2018] [Root-Cause Diagnosis Using Logs Generated by User Actions](https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=8647957)

- [ICSE 2019] [Mining Historical Issue Repositories to Heal Large-Scale Online Service Systems](https://ieeexplore.ieee.org/document/6903589)

- [CLOUD 2019] [An Approach to Cloud Execution Failure Diagnosis Based on Exception Logs in OpenStack](https://ieeexplore.ieee.org/abstract/document/8814553)

- [FAST 2009] [Understanding customer problem troubleshooting from storage system logs](https://www.usenix.org/legacy/events/fast09/tech/full_papers/jiang/jiang.pdf)

- [DSN 2013] [Reading between the lines of failure logs: Understanding how HPC systems fail](https://ieeexplore.ieee.org/document/6575356)

- [DSN 2014] [What logs should you look at when an application fails? insights from an industrial case study](https://ieeexplore.ieee.org/document/6903626)

- [TSE 2018] [Fault analysis and debugging of microservice systems: Industrial survey, benchmark system, and empirical study](https://ieeexplore.ieee.org/document/8580420)

- [FSE 2019] [How bad can a bug get? an empirical analysis of software failures in the OpenStack cloud computing platform](https://dl.acm.org/doi/10.1145/3338906.3338916)

#### Others

- [DSN14] [Mining Historical Issue Repositories to Heal Large-Scale Online Service Systems](https://doi.org/10.1109/DSN.2014.39)

- [ASE98] [Testing using log file analysis: Tools, methods, and issues](https://doi.org/10.1109/ASE.1998.732614)

- [ASE18] [An automated approach to estimating code coverage measures via execution logs](https://doi.org/10.1145/3238147.3238214)

- [ASE19] [An experience report of generating load tests using log-recovered workloads at varying granularities of user behaviour](https://doi.org/10.1109/ASE.2019.00068)

- [ASE15] [Have we seen enough traces? (T)](https://doi.org/10.1109/ASE.2015.62)

- [ICSE08] [An approach to detecting duplicate bug reports using natural language and execution information](https://doi.org/10.1145/1368088.1368151)

## License

This repo is under the MIT license.