Abstract: The oracle improvement process aims at reducing the false alarms and the missed program faults associated with the program oracle used during testing. In this talk, I will analyse the oracle improvement process from a theoretical view point, based on notions borrowed from the field of information theory.
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The talk is based on the paper:
Abstract: Automated test case generation has come a long way and is currently able to generate test cases with high structural coverage. However, the readability and understandability of automatically generated test cases has yet to improve. In this talk I will summarize two recent research works directed towards improving the understandability of test cases so that they become easier to maintain and more helpful in finding bugs.
The talk is based on the following papers:
I update my mobile phone applications (apps for short), why my cell phone battery is already low? How does it happen that I already used almost all the data of my monthly phone plan? Is it worth buying the app, or should I continue using the free version? Should I trust an app that often tracks my location?
Abstract: We introduce a foundational theory, and a practical technique for assessing and improving test oracles by reducing the incidence of both false positives and false negatives. Our technique combines test case generation to reveal false positives and mutation testing to reveal false negatives. We applied the decision support tool that implements our oracle improvement technique to five real-world subjects. The experimental results show that the fault detection rate of the improved oracles increases, on average, by 52% (92% over the implicit oracle).
This seminar is about the paper: "Learning Natural Coding Conventions" Allamanis M. et al. FSE ’14.