too many exampls just form sbse

[timm]

I have one point of critique though. All examples seem to come from the field of SBSE. However, there are lots of other optimisation techniques. In particular, there's constraint solving (SAT,SMT,CSP, and other). These all deal with optimisation problems, and not all are stochastic solutions. Nevertheless, most points I would imagine apply (define search space, fitness/evaluation criteria etc.).

I would thus suggest to remove "(e.g., metaheuristics and evolutionary algorithms)" from the introduction; add additional examples: e.g., change "The algorithm underlying an approach (e.g., the metaheuristic) " to "The algorithm underlying an approach (e.g., the metaheuristic, CDCL)" and change: "One should sample from data multiple times in a controlled manner." to "One should sample from data multiple times in a controlled manner, where appropriate." (or smth, as it's not always necessary)

I tried to find an exemplary paper that would compare SBSE and constraint-based approaches. There have been quite a few constraint-based approaches proposed for test input generation, but I wasn't sure which one to pick. Perhaps others might have suggestions.

Thanks again for all the efforts.

[timm]

Intro para changed to

• Research studies that focus on the formulation of software engineering problems as search problems, and apply optimization techniques to solve such problems. Note that there are many such optimization techniques (metaheuristic; numerical optimizers; constraint solving theorem provers SAT,SMT,CSP; and other), some of which are stochastic.

[timm]

Later dot point changed to

• The algorithm underlying an approach (e.g., the numerical optimizer, the specific metaheuristic, the constraint solving method, etc ) should be justified and appropriate for the problem being optimized.