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Context: A Legacy system can be defined as a system that significantlyresists modification and evolution. According to the literature, there are twomain strategies to migrate a legacy system: (a) to replace the legacy system bya new one, (b) to incrementally migrate parts from the legacy system to the newone. Incremental migration allows developers to better control the risks thatmay occur during the migration process. However, this strategy is more complexbecause it requires decomposition of the legacy system into different parts,e.g. a set of files, and to define the order of migration of them along themigration process. To our knowledge, there is no approach to support developerson those activities. Objective: This paper presents an approach, namedMigrationExp, to support incremental language migrations of applications fromone source language to another target language. MigrationExp recommends thefiles that should be migrated first in a particular migration iteration. As anovelty, our approach relies on a ranking model learned, using alearning-to-rank algorithm, from migrations made by developers. Method: Wevalidate our approach in the context of the migrations of Android apps, fromJava to Kotlin, a new official language for Android. We train our model usingmigrations of Java code to Kotlin written by developers on open-sourceapplications. Results: The results show that, on the task of proposing files tomigrate, our approach outperforms a previous migration strategy proposed byGoogle, in terms of its ability to accurately predict empirically observedmigration orders. Conclusion: Since most Android applications are written inJava, we conclude that approaches to support developers such as MigrationExpmay significantly impact the development of Android applications.

Learning migration models for supporting incremental language migrations of software applications