concrete meta research - how to collect, manage, and read papers?
TRANSCRIPT
CONCRETE META-RESEARCH- How to collect, manage, and read papers?
Software Engineering LaboratoryDepartment of Computer Science, Sun Yat-Sen University
With thanks to our supervisors: Prof. Li and Prof. Zhou
October 2011Sun Yat-Sen University, Guangzhou, China
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CONCRETE META-RESEARCH
“Our professors often talk abstractly and high-level?”
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Motivation of this talk
Share research tools and experience Discover stains and pitfalls of my habits
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How to access Internet without limits?
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VPNs
goagent http://code.google.com/p/goagent/
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“越过长城，走向世界”
Auto Proxy for browsers
Switchy! http://code.google.com/p/switchyplus/ Auto Switch Rules:
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How to find first-tier conferences/journals in a specific research area?
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Microsoft Academic Search
Top conferences ( find research trends) http://academic.research.microsoft.com/RankList?entitytype=3&topDomainID=2&subD
omainID=4&last=5&start=1&end=100
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Microsoft Academic Search
Top journals ( find evaluation methods) http://academic.research.microsoft.com/RankList?entitytype=4&topDomainID=2&subD
omainID=4&last=0&start=1&end=100
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WIKIPEDIA
List of computer science conferences http://en.wikipedia.org/wiki/List_of_computer_science_conferences
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How to get the paper list of a particular conference?
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DBLP (Digital Bibliography & Library Project)
DBLP listed more than 1.3 million articles on computer science in January 2010. http://www.informatik.uni-trier.de/~ley/db/conf/
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DBLP (Digital Bibliography & Library Project)
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DBLP (Digital Bibliography & Library Project)
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DBLP (Digital Bibliography & Library Project)
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DBLP (Digital Bibliography & Library Project)
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DBLP (Digital Bibliography & Library Project)
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DBLP (Digital Bibliography & Library Project)
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How to search a paper? (in others’ references, by author name, by keyword)
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Complete Search DBLP
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Ranked by publication time Based on Ajax query
Google Scholar
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Ranked by relevance and citation number Show versions through different databases
Google Scholar
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Ranked by relevance and citation number Show versions from different databases
Google Scholar
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Ranked by relevance and citation number Show versions from different databases
What are the common research databases in Computer Science? (for the purpose of downloading full-text papers)
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IEEE Xplore
http://ieeexplore.ieee.org/Xplore/guesthome.jsp
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IEEE Xplore
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ACM Digital Library
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How to manage papers in local host?
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Note Express
Tortoise http://682.116.65.75/c/document_library/get_file?folderId=1&
name=DLFE-381.ppt
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How to search papers in local host?
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Everything Much faster than the original ‘find’ tool
http://www.voidtools.com/
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Note Express
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How to take notes for papers?
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Note Express
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You can even copy screenshots into a note!
Google Notebook
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HTML format-copy Synchronization
Google Notebook
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Export as HTML
How to generate citation?
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IEEE Xplore
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ACM Digital Library
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Note Express
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ACM Ref
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What resources can we utilize in our library?
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Resources in our library Please visit - http://library.sysu.edu.cn/web/guest/fwzn/dzpx
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How to get a quick preview of terminology?
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WIKIPEDIA
E.g., ‘mutation testing’
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How to find similar papers?
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Keywords
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Keywords
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References
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James A. Jones, James F. Bowring, and Mary Jean Harrold. 2007. Debugging in Parallel. In Proceedings of the 2007 international symposium on Software testing and analysis (ISSTA '07). ACM, New York, NY, USA, 16-26. DOI=10.1145/1273463.1273468 http://doi.acm.org/10.1145/1273463.1273468
References
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James A. Jones, James F. Bowring, and Mary Jean Harrold. 2007. Debugging in Parallel. In Proceedings of the 2007 international symposium on Software testing and analysis (ISSTA '07). ACM, New York, NY, USA, 16-26. DOI=10.1145/1273463.1273468 http://doi.acm.org/10.1145/1273463.1273468
Names of authors
References
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James A. Jones, James F. Bowring, and Mary Jean Harrold. 2007. Debugging in Parallel. In Proceedings of the 2007 international symposium on Software testing and analysis (ISSTA '07). ACM, New York, NY, USA, 16-26. DOI=10.1145/1273463.1273468 http://doi.acm.org/10.1145/1273463.1273468
Title
References
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James A. Jones, James F. Bowring, and Mary Jean Harrold. 2007. Debugging in Parallel. In Proceedings of the 2007 international symposium on Software testing and analysis (ISSTA '07). ACM, New York, NY, USA, 16-26. DOI=10.1145/1273463.1273468 http://doi.acm.org/10.1145/1273463.1273468
Conference name or journal name
References
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James A. Jones, James F. Bowring, and Mary Jean Harrold. 2007. Debugging in Parallel. In Proceedings of the 2007 international symposium on Software testing and analysis (ISSTA '07). ACM, New York, NY, USA, 16-26. DOI=10.1145/1273463.1273468 http://doi.acm.org/10.1145/1273463.1273468
Address
References
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James A. Jones, James F. Bowring, and Mary Jean Harrold. 2007. Debugging in Parallel. In Proceedings of the 2007 international symposium on Software testing and analysis (ISSTA '07). ACM, New York, NY, USA, 16-26. DOI=10.1145/1273463.1273468 http://doi.acm.org/10.1145/1273463.1273468
Digital object identifier
Homepage of authors
Google it!
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Homepage of authors
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Homepage of laboratory
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We can find technical reports here E.g. (http://swerl.tudelft.nl/bin/view/Main/TechnicalReports)
How to read a paper?
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Papers are written in *one* template?
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Abstract The presence of multiple faults in a program can inhibit the ability of fault-localization techniques to locate the faults. This problem occurs for two reasons: when a program fails, the number of faults is, in general, unknown; and certain faults may mask or obfuscate other faults. This paper presents our approach to solving this problem that leverages the well-known advantages of parallel work flows to reduce the time-to-release of a program. Our approach consists of a technique that enables more effective debugging in the presence of multiple faults and a methodology that enables multiple developers to simultaneously debug multiple faults. The paper also presents an empirical study that demonstrates that our parallel-debugging technique and methodology can yield a dramatic decrease in total debugging time compared to a one-fault-at-a-time, or conventionally sequential, approach.
Papers are written in *one* template?
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Abstract The presence of multiple faults in a program can inhibit the ability of fault-localization techniques to locate the faults. This problem occurs for two reasons: when a program fails, the number of faults is, in general, unknown; and certain faults may mask or obfuscate other faults. This paper presents our approach to solving this problem that leverages the well-known advantages of parallel work flows to reduce the time-to-release of a program. Our approach consists of a technique that enables more effective debugging in the presence of multiple faults and a methodology that enables multiple developers to simultaneously debug multiple faults. The paper also presents an empirical study that demonstrates that our parallel-debugging technique and methodology can yield a dramatic decrease in total debugging time compared to a one-fault-at-a-time, or conventionally sequential, approach.
Background
Papers are written in *one* template?
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Abstract The presence of multiple faults in a program can inhibit the ability of fault-localization techniques to locate the faults. This problem occurs for two reasons: when a program fails, the number of faults is, in general, unknown; and certain faults may mask or obfuscate other faults. This paper presents our approach to solving this problem that leverages the well-known advantages of parallel work flows to reduce the time-to-release of a program. Our approach consists of a technique that enables more effective debugging in the presence of multiple faults and a methodology that enables multiple developers to simultaneously debug multiple faults. The paper also presents an empirical study that demonstrates that our parallel-debugging technique and methodology can yield a dramatic decrease in total debugging time compared to a one-fault-at-a-time, or conventionally sequential, approach.
Motivation
Papers are written in *one* template?
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Abstract The presence of multiple faults in a program can inhibit the ability of fault-localization techniques to locate the faults. This problem occurs for two reasons: when a program fails, the number of faults is, in general, unknown; and certain faults may mask or obfuscate other faults. This paper presents our approach to solving this problem that leverages the well-known advantages of parallel work flows to reduce the time-to-release of a program. Our approach consists of a technique that enables more effective debugging in the presence of multiple faults and a methodology that enables multiple developers to simultaneously debug multiple faults. The paper also presents an empirical study that demonstrates that our parallel-debugging technique and methodology can yield a dramatic decrease in total debugging time compared to a one-fault-at-a-time, or conventionally sequential, approach.
The authors’ approach
Papers are written in *one* template?
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Abstract The presence of multiple faults in a program can inhibit the ability of fault-localization techniques to locate the faults. This problem occurs for two reasons: when a program fails, the number of faults is, in general, unknown; and certain faults may mask or obfuscate other faults. This paper presents our approach to solving this problem that leverages the well-known advantages of parallel work flows to reduce the time-to-release of a program. Our approach consists of a technique that enables more effective debugging in the presence of multiple faults and a methodology that enables multiple developers to simultaneously debug multiple faults. The paper also presents an empirical study that demonstrates that our parallel-debugging technique and methodology can yield a dramatic decrease in total debugging time compared to a one-fault-at-a-time, or conventionally sequential, approach.
Brief insights of this approach
Papers are written in *one* template?
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Abstract The presence of multiple faults in a program can inhibit the ability of fault-localization techniques to locate the faults. This problem occurs for two reasons: when a program fails, the number of faults is, in general, unknown; and certain faults may mask or obfuscate other faults. This paper presents our approach to solving this problem that leverages the well-known advantages of parallel work flows to reduce the time-to-release of a program. Our approach consists of a technique that enables more effective debugging in the presence of multiple faults and a methodology that enables multiple developers to simultaneously debug multiple faults. The paper also presents an empirical study that demonstrates that our parallel-debugging technique and methodology can yield a dramatic decrease in total debugging time compared to a one-fault-at-a-time, or conventionally sequential, approach.
Evaluation and results
Q & A
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I hope this talk will be helpful…
Outline
Tools Cross the Great Wall via VPNs Databases of publications Local management
Everything Note Express
Rules Top conferences/journals
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Tools
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工欲善其事必先利其器
Skills of graduate students
Skills of graduate students
Technical skills (e.g. programming, performance
improvement, and validation)
Information acquisition skills (e.g. paper-reading,
points extraction, and asking questions)
Evaluation skills ( e.g. empirical study and statistical analysis)
Presentation (e.g. giving a talk and
communication via emails)
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Others
Springer Online Library Wiley Inter Science Elsevier Online Library Science Direct
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Resources in our library Please visit - http://library.sysu.edu.cn/web/guest/fwzn/dzpx
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Massive resources Please visit - http://library.sysu.edu.cn/web/guest/fwzn/dzpx
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Open courseware
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