Exceptional C or C with exceptions
Software—Practice & Experience
PADS: a domain-specific language for processing ad hoc data
Proceedings of the 2005 ACM SIGPLAN conference on Programming language design and implementation
Interpreting the data: Parallel analysis with Sawzall
Scientific Programming - Dynamic Grids and Worldwide Computing
MapReduce: simplified data processing on large clusters
OSDI'04 Proceedings of the 6th conference on Symposium on Opearting Systems Design & Implementation - Volume 6
Enhancing server availability and security through failure-oblivious computing
OSDI'04 Proceedings of the 6th conference on Symposium on Opearting Systems Design & Implementation - Volume 6
What Supercomputers Say: A Study of Five System Logs
DSN '07 Proceedings of the 37th Annual IEEE/IFIP International Conference on Dependable Systems and Networks
Pig latin: a not-so-foreign language for data processing
Proceedings of the 2008 ACM SIGMOD international conference on Management of data
NSDI'10 Proceedings of the 7th USENIX conference on Networked systems design and implementation
| Hi-index | 0.00 |
Programmers and data analysts get frustrated when their long-running data processing scripts crash without producing results, due to either bugs in their code or inconsistencies in data sources. To alleviate this frustration, we developed a dynamic analysis technique that guarantees scripts will never crash: It converts all uncaught exceptions into special NA (Not Available) objects and continues executing rather than crashing. Thus, imperfect scripts will run to completion and produce partial results and an error log, which is more informative than simply crashing with no results. We implemented our technique as a "Sloppy" Python interpreter that automatically adds error tolerance to existing scripts without any programmer effort or run-time slowdown.