Locating faults in a constant number of parallel testing rounds
SPAA '89 Proceedings of the first annual ACM symposium on Parallel algorithms and architectures
Fault diagnosis in a small constant number of parallel testing rounds
SPAA '93 Proceedings of the fifth annual ACM symposium on Parallel algorithms and architectures
Pair Programming Illuminated
Improving the CS1 experience with pair programming
SIGCSE '03 Proceedings of the 34th SIGCSE technical symposium on Computer science education
Strengthening the Case for Pair Programming
IEEE Software
FOCS '95 Proceedings of the 36th Annual Symposium on Foundations of Computer Science
Reliable Fault Diagnosis with Few Tests
Combinatorics, Probability and Computing
ICDCS '04 Proceedings of the 24th International Conference on Distributed Computing Systems (ICDCS'04)
RANDOM k-SET POOL DESIGNS WITH DISTINCT COLUMNS
Probability in the Engineering and Informational Sciences
Improved Combinatorial Group Testing Algorithms for Real-World Problem Sizes
SIAM Journal on Computing
Private combinatorial group testing
Proceedings of the 2008 ACM symposium on Information, computer and communications security
How to generate and exchange secrets
SFCS '86 Proceedings of the 27th Annual Symposium on Foundations of Computer Science
Pair programming in CS1: overcoming objections to its adoption
ACM SIGCSE Bulletin
Pipelined algorithms to detect cheating in long-term grid computations
Theoretical Computer Science
Searching for high-value rare events with uncheatable grid computing
ACNS'05 Proceedings of the Third international conference on Applied Cryptography and Network Security
Indexing information for data forensics
ACNS'05 Proceedings of the Third international conference on Applied Cryptography and Network Security
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We formalize a problem we call combinatorial pair testing (CPT), which has applications to the identification of uncooperative or unproductive participants in pair programming, massively distributed computing, and crowdsourcing environments. We give efficient adaptive and nonadaptive CPT algorithms and we show that our methods use an optimal number of testing rounds to within constant factors. We also provide an empirical evaluation of some of our methods.