Dynamically transforming data structures

Fine-tuning which data structure implementation to use for a given problem is sometimes tedious work since the optimum solution depends on the context, i.e., on the operation sequences, actual parameters as well as on the hardware available at run time. Sometimes a data structure with higher asymptotic time complexity performs better in certain contexts because of lower constants. The optimal solution may not even be possible to determine at compile time. We introduce transformation data structures that dynamically change their internal representation variant based on a possibly changing context. The most suitable variant is selected at run time rather than at compile time. We demonstrate the effect on performance with a transformation ArrayList data structure using an array variant and a linked hash bag variant as alternative internal representations. Using our transformation ArrayList, the standard DaCapo benchmark suite shows a performance gain of 5.19% in average.