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CloudRaid: hunting concurrency bugs in the cloud via log-mining

Authors:

Xiaobing FengAuthors Info & Claims

ESEC/FSE 2018: Proceedings of the 2018 26th ACM Joint Meeting on European Software Engineering Conference and Symposium on the Foundations of Software Engineering

Pages 3 - 14

https://doi.org/10.1145/3236024.3236071

Published: 26 October 2018 Publication History

Abstract

Cloud systems suffer from distributed concurrency bugs, which are notoriously difficult to detect and often lead to data loss and service outage. This paper presents CloudRaid, a new effective tool to battle distributed concurrency bugs. CloudRaid automatically detects concurrency bugs in cloud systems, by analyzing and testing those message orderings that are likely to expose errors. We observe that large-scale online cloud applications process millions of user requests per second, exercising many permutations of message orderings extensively. Those already sufficiently-tested message orderings are unlikely to expose errors. Hence, CloudRaid mines logs from previous executions to uncover those message orderings which are feasible, but not sufficiently tested. Specifically, CloudRaid tries to flip the order of a pair of messages <S,P> if they may happen in parallel, but S always arrives before P from existing logs, i.e., excercising the order P ↣ S. The log-based approach makes it suitable to live systems.

We have applied CloudRaid to automatically test four representative distributed systems: Apache Hadoop2/Yarn, HBase, HDFS and Cassandra. CloudRaid can automatically test 40 different versions of the 4 systems (10 versions per system) in 35 hours, and can successfully trigger 28 concurrency bugs, including 8 new bugs that have never been found before. The 8 new bugs have all been confirmed by their original developers, and 3 of them are considered as critical bugs that have already been fixed.

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Cited By

Xue KHan QHan SShi ZQiao Y(2024)A Review of Software Testing Process Log Parsing and Mining2024 IEEE International Conference on Software Services Engineering (SSE)10.1109/SSE62657.2024.00055(334-343)Online publication date: 7-Jul-2024
https://doi.org/10.1109/SSE62657.2024.00055
Fu YYan MHe PLiu CZhang XYang D(2024)End-to-end log statement generation at block-levelJournal of Systems and Software10.1016/j.jss.2024.112146216(112146)Online publication date: Oct-2024
https://doi.org/10.1016/j.jss.2024.112146
Ding ZTang YCheng XLi HShang W(2023) LoGenText-Plus: Improving Neural Machine Translation Based Logging Texts Generation with Syntactic TemplatesACM Transactions on Software Engineering and Methodology10.1145/362474033:2(1-45)Online publication date: 22-Dec-2023
https://dl.acm.org/doi/10.1145/3624740
Show More Cited By

Index Terms

CloudRaid: hunting concurrency bugs in the cloud via log-mining
1. Software and its engineering
  1. Software creation and management
    1. Software verification and validation
      1. Software defect analysis
        Software testing and debugging
  2. Software organization and properties
    1. Software system structures
      1. Distributed systems organizing principles
        Cloud computing

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cover image ACM Conferences

ESEC/FSE 2018: Proceedings of the 2018 26th ACM Joint Meeting on European Software Engineering Conference and Symposium on the Foundations of Software Engineering

October 2018

987 pages

ISBN:9781450355735

DOI:10.1145/3236024

General Chair:
Gary T. Leavens
University of Central Florida, USA
,
Program Chairs:
Alessandro Garcia
PUC-Rio, Brazil
,
Corina S. Păsăreanu
NASA Ames Research Center, USA

Copyright © 2018 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Published: 26 October 2018

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ESEC/FSE '18: 26th ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering

November 4 - 9, 2018

FL, Lake Buena Vista, USA

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Cited By

Xue KHan QHan SShi ZQiao Y(2024)A Review of Software Testing Process Log Parsing and Mining2024 IEEE International Conference on Software Services Engineering (SSE)10.1109/SSE62657.2024.00055(334-343)Online publication date: 7-Jul-2024
https://doi.org/10.1109/SSE62657.2024.00055
Fu YYan MHe PLiu CZhang XYang D(2024)End-to-end log statement generation at block-levelJournal of Systems and Software10.1016/j.jss.2024.112146216(112146)Online publication date: Oct-2024
https://doi.org/10.1016/j.jss.2024.112146
Ding ZTang YCheng XLi HShang W(2023) LoGenText-Plus: Improving Neural Machine Translation Based Logging Texts Generation with Syntactic TemplatesACM Transactions on Software Engineering and Methodology10.1145/362474033:2(1-45)Online publication date: 22-Dec-2023
https://dl.acm.org/doi/10.1145/3624740
Liu XYang CLi DZhou YLi SChen JChen Z(2023)Adonis: Practical and Efficient Control Flow Recovery through OS-level TracesACM Transactions on Software Engineering and Methodology10.1145/360718733:1(1-27)Online publication date: 4-Jul-2023
https://dl.acm.org/doi/10.1145/3607187
Sui YZhang YSun JXu TZhang SLi ZSun YGuo FShen JZhang YPei DYang XYu L(2023)LogKG: Log Failure Diagnosis Through Knowledge GraphIEEE Transactions on Services Computing10.1109/TSC.2023.329389016:5(3493-3507)Online publication date: Sep-2023
https://doi.org/10.1109/TSC.2023.3293890
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Fu YYan MXu JLi JLiu ZZhang XYang DRoychoudhury ACadar CKim M(2022)Investigating and improving log parsing in practiceProceedings of the 30th ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering10.1145/3540250.3558947(1566-1577)Online publication date: 7-Nov-2022
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Liu JZeng JWang XJi KLiang ZRyu SSmaragdakis Y(2022)TeLL: log level suggestions via modeling multi-level code block informationProceedings of the 31st ACM SIGSOFT International Symposium on Software Testing and Analysis10.1145/3533767.3534379(27-38)Online publication date: 18-Jul-2022
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Qiu ZShao SZhao QKhan HHui XJin GLo DMcIntosh SNovielli N(2022)A deep study of the effects and fixes of server-side request races in web applicationsProceedings of the 19th International Conference on Mining Software Repositories10.1145/3524842.3528463(744-756)Online publication date: 23-May-2022
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