Bug isolation via remote program sampling Export

@inproceedings{citeulike:745875, abstract = {We propose a low-overhead sampling infrastructure for gathering information from the executions experienced by a program's user community. Several example applications illustrate ways to use sampled instrumentation to isolate bugs. Assertion-dense code can be transformed to share the cost of assertions among many users. Lacking assertions, broad guesses can be made about predicates that predict program errors and a process of elimination used to whittle these down to the true bug. Finally, even for non-deterministic bugs such as memory corruption, statistical modeling based on logistic regression allows us to identify program behaviors that are strongly correlated with failure and are therefore likely places to look for the error.}, address = {New York, NY, USA}, author = {Liblit, Ben and Aiken, Alex and Zheng, Alice X. and Jordan, Michael I.}, booktitle = {PLDI '03: Proceedings of the ACM SIGPLAN 2003 conference on Programming language design and implementation}, citeulike-article-id = {745875}, citeulike-linkout-0 = {http://portal.acm.org/citation.cfm?id=781148}, citeulike-linkout-1 = {http://dx.doi.org/10.1145/781131.781148}, doi = {10.1145/781131.781148}, issn = {0362-1340}, keywords = {proposal, sw\_engineering, testing}, pages = {141--154}, posted-at = {2008-04-17 02:47:07}, priority = {0}, publisher = {ACM Press}, title = {Bug isolation via remote program sampling}, url = {http://dx.doi.org/10.1145/781131.781148}, year = {2003} }

TY - CONF ID - citeulike:745875 L3 - citeulike-article-id:745875 N2 - We propose a low-overhead sampling infrastructure for gathering information from the executions experienced by a program's user community. Several example applications illustrate ways to use sampled instrumentation to isolate bugs. Assertion-dense code can be transformed to share the cost of assertions among many users. Lacking assertions, broad guesses can be made about predicates that predict program errors and a process of elimination used to whittle these down to the true bug. Finally, even for non-deterministic bugs such as memory corruption, statistical modeling based on logistic regression allows us to identify program behaviors that are strongly correlated with failure and are therefore likely places to look for the error. SN - 0362-1340 AD - New York, NY, USA EP - 154 TI - Bug isolation via remote program sampling PB - ACM Press T2 - PLDI '03: Proceedings of the ACM SIGPLAN 2003 conference on Programming language design and implementation SP - 141 KW - proposal KW - sw_engineering KW - testing AU - Liblit, Ben AU - Aiken, Alex AU - Zheng, Alice AU - Jordan, Michael PY - 2003/// UR - http://dx.doi.org/10.1145/781131.781148 ER -