1 citations · 1 across the 3 of their papers we have counts for
3 papers
Quality-Driven Selective Mutation for Deep Learning
Zaheed Ahmed, Emmanuel Charleson Dapaah, Philip Makedonski +1
Mutants support testing and debugging in two roles: (i) as test goals and (ii) as substitutes for real faults. Hard-to-kill mutants provide better guidance for test improvement, wh…
An Empirical Study of the Realism of Mutants in Deep Learning
Zaheed Ahmed, Philip Makedonski, Jens Grabowski
Mutation analysis is a well-established technique for assessing test quality in the traditional software development paradigm by injecting artificial faults into programs. Its appl…
A new perspective on the competent programmer hypothesis through the reproduction of bugs with repeated mutations
Zaheed Ahmed, Eike Stein, Steffen Herbold +2
The competent programmer hypothesis states that most programmers are competent enough to create correct or almost correct source code. Because this implies that bugs should usually…