The practice of programming
Bugs as deviant behavior: a general approach to inferring errors in systems code
SOSP '01 Proceedings of the eighteenth ACM symposium on Operating systems principles
The SLAM project: debugging system software via static analysis
POPL '02 Proceedings of the 29th ACM SIGPLAN-SIGACT symposium on Principles of programming languages
Isolating cause-effect chains from computer programs
Proceedings of the 10th ACM SIGSOFT symposium on Foundations of software engineering
Fault Injection Techniques and Tools
Computer
Code Churn: A Measure for Estimating the Impact of Code Change
ICSM '98 Proceedings of the International Conference on Software Maintenance
Squid: The Definitive Guide
Predicting Source Code Changes by Mining Change History
IEEE Transactions on Software Engineering
Low-overhead memory leak detection using adaptive statistical profiling
ASPLOS XI Proceedings of the 11th international conference on Architectural support for programming languages and operating systems
Use of relative code churn measures to predict system defect density
Proceedings of the 27th international conference on Software engineering
Discovering faults in idiom-based exception handling
Proceedings of the 28th international conference on Software engineering
Checking system rules using system-specific, programmer-written compiler extensions
OSDI'00 Proceedings of the 4th conference on Symposium on Operating System Design & Implementation - Volume 4
CP-Miner: a tool for finding copy-paste and related bugs in operating system code
OSDI'04 Proceedings of the 6th conference on Symposium on Opearting Systems Design & Implementation - Volume 6
/*icomment: bugs or bad comments?*/
Proceedings of twenty-first ACM SIGOPS symposium on Operating systems principles
Automated Identification of Failure Causes in System Logs
ISSRE '08 Proceedings of the 2008 19th International Symposium on Software Reliability Engineering
Understanding customer problem troubleshooting from storage system logs
FAST '09 Proccedings of the 7th conference on File and storage technologies
A toolset for automated failure analysis
ICSE '09 Proceedings of the 31st International Conference on Software Engineering
Automatic Generation of Runtime Failure Detectors from Property Templates
Software Engineering for Self-Adaptive Systems
Detecting large-scale system problems by mining console logs
Proceedings of the ACM SIGOPS 22nd symposium on Operating systems principles
Toward Translating Design Constraints to Run-Time Assertions
Electronic Notes in Theoretical Computer Science (ENTCS)
SherLog: error diagnosis by connecting clues from run-time logs
Proceedings of the fifteenth edition of ASPLOS on Architectural support for programming languages and operating systems
Scalable and systematic detection of buggy inconsistencies in source code
Proceedings of the ACM international conference on Object oriented programming systems languages and applications
Improving software diagnosability via log enhancement
Proceedings of the sixteenth international conference on Architectural support for programming languages and operating systems
MoonBox: debugging with online slicing and dryrun
Proceedings of the Asia-Pacific Workshop on Systems
MoonBox: debugging with online slicing and dryrun
APSys'12 Proceedings of the Third ACM SIGOPS Asia-Pacific conference on Systems
Be conservative: enhancing failure diagnosis with proactive logging
OSDI'12 Proceedings of the 10th USENIX conference on Operating Systems Design and Implementation
Contextual analysis of program logs for understanding system behaviors
Proceedings of the 10th Working Conference on Mining Software Repositories
Report on the international symposium on high confidence software (ISHCS 2011/2012)
ACM SIGSOFT Software Engineering Notes
Challenges to error diagnosis in hadoop ecosystems
LISA'13 Proceedings of the 27th international conference on Large Installation System Administration
Structured and Interoperable Logging for the Cloud Computing Era: The Pitfalls and Benefits
UCC '13 Proceedings of the 2013 IEEE/ACM 6th International Conference on Utility and Cloud Computing
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Software logging is a conventional programming practice. As its efficacy is often important for users and developers to understand what have happened in production run, yet software logging is often done in an arbitrarily manner. So far, there have been little study for understanding logging practices in real world software. This paper makes the first attempt (to the best of our knowledge) to provide quantitative characteristic study of the current log messages within four pieces of large open-source software. First, we quantitatively show that software logging is pervasive. By examining developers’ own modifications to logging code in revision history, we find that they often do not make the log messages right in their first attempts, and thus need to spend significant amount of efforts to modify the log messages as after-thoughts. Our study further provides several interesting findings on where developers spend most of their efforts in modifying the log messages, which can give insights for programmers, tool developers, and language and compiler designers to improve the current logging practice. To demonstrate the benefit of our study, we built a simple checker based on one of our findings and effectively detected 138 new problematic logging code from studied software (24 of them are already confirmed and fixed by developers).