Eraser: a dynamic data race detector for multithreaded programs
ACM Transactions on Computer Systems (TOCS)
On Comparisons of Random, Partition, and Proportional Partition Testing
IEEE Transactions on Software Engineering
Writing Secure Code
Annals of Software Engineering
TestEra: A Novel Framework for Automated Testing of Java Programs
Proceedings of the 16th IEEE international conference on Automated software engineering
Mock object creation for test factoring
Proceedings of the 5th ACM SIGPLAN-SIGSOFT workshop on Program analysis for software tools and engineering
IEEE Software
A genetic approach for random testing of database systems
VLDB '07 Proceedings of the 33rd international conference on Very large data bases
Cross feature testing in database systems
Proceedings of the 1st international workshop on Testing database systems
Science of Computer Programming
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The increasing size and complexity of software, coupled with concurrency and distributed systems, has made apparent the ineffectiveness of using only handcrafted tests. The misuse of code coverage and avoidance of random testing has exacerbated the problem. We must start again, beginning with good design (including dependency analysis), good static checking (including model property checking), and good unit testing (including good input selection). Code coverage can help select and prioritize tests to make you more efficient, as can the all-pairs technique for controlling the number of configurations. Finally, testers can use models to generate test coverage and good stochastic tests, and to act as test oracles.