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ICSE 2020
Wed 24 June - Thu 16 July 2020

Context: Programmers frequently look for the code of previously solved problems that they can adapt for their own problem. Despite existing example code on the web, on sites like Stack Overflow, cryptographic APIs are commonly misused. There is little known about what makes examples helpful for developers in using crypto APIs. Analogical problem solving is a psychological theory that investigates how people use known solutions to solve new problems. There is evidence that the capacity to reason and solve novel problems a.k.a fluid intelligence and structurally and procedurally similar solutions support problem solving. Aim: Our goal is to understand whether similarity and \gls{Gf} also have an effect in the context of using cryptographic APIs with the help of code examples. Method: We conducted a controlled experiment with 76 student participants developing with or without procedurally similar examples, one of two Java crypto libraries and measured the fluid intelligence of the participants as well as the effect on usability (effectiveness, efficiency, satisfaction) and security bugs. Results: We observed a strong effect of code examples with a high procedural similarity on all dependent variables. Fluid intelligence had no effect. It also made no difference which library the participants used. Conclusions: Example code must be more highly similar to a concrete solution, not very abstract and generic to have a positive effect in a development task.