Quantifying the Potential to Automate the Synchronization of Variants in Clone-and-Own

In clone-and-own - the predominant paradigm for developing multi-variant software systems in practice - a new variant of a software system is created by copying and adapting an existing one. While clone-and-own is flexible, it causes high maintenance effort in the long run as cloned variants evolve in parallel; certain changes, such as bug fixes, need to be propagated between variants manually. On top of the principle of cherry-picking and by collecting lightweight domain knowledge on cloned variants and software changes, a recent line of research proposes to automate such synchronization tasks when migration to a software product line is not feasible. However, it is yet unclear how far this synchronization can actually be pushed. We conduct an empirical study in which we quantify the potential to automate the synchronization of variants in clone-and-own. We simulate the variant synchronization using the history of a real-world multi-variant software system as a case study. Our results indicate that existing patching techniques propagate changes with an accuracy of up to 85%, if applied consistently from the start of a project. This can be even further improved to 93% by exploiting lightweight domain knowledge about which features are affected by a change, and which variants implement affected features. Based on our findings, we conclude that there is potential to automate the synchronization of cloned variants through existing patching techniques.