Statistical assertion: A more powerful method for debugging scientific applications-Reference-Cited by-同舟云学术

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Statistical assertion: A more powerful method for debugging scientific applications

Published:2014-03 Issue:2 Volume:5 Page:126-134
ISSN:1877-7503
Container-title:Journal of Computational Science
language:en
Short-container-title:Journal of Computational Science

Author:

Dinh Minh Ngoc,Abramson David,Jin Chao

Publisher

Elsevier BV

Subject

Modeling and Simulation,General Computer Science,Theoretical Computer Science

Reference23 articles.

1. Data Mining: A knowledge Discovery Approach;Cios,2007

2. Assertion based parallel debugging;Dinh,2011

3. Scalable relative debugging;Dinh;IEEE Transactions on Parallel and Distributed Systems,2013

4. A debugging and testing tool for supporting software evolution;Abramson;Journal of Automated Software Engineering,1996

5. Why Programs Fail: A Guide to Systematic Debugging;Zeller,2006

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1. Measurements of errors in large-scale computational simulations at runtime;2020 RIVF International Conference on Computing and Communication Technologies (RIVF);2020-10

2. Tracking scientific simulation using online time-series modelling;2020 20th IEEE/ACM International Symposium on Cluster, Cloud and Internet Computing (CCGRID);2020-05

3. An Assertion Framework for Mobile Robotic Programming with Spatial Reasoning;2018 IEEE 42nd Annual Computer Software and Applications Conference (COMPSAC);2018-07

4. 10 Years of research on debugging concurrent and multicore software: a systematic mapping study;Software Quality Journal;2016-01-21

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