LAUSR

Large‐scale corrective and perfective maintenance is often automated thanks to rewriting rules using tools such as Python2to3, Spoon, or Coccinelle. Such tools consider these rules as black‐boxes and compose multiple rules by chaining them: giving the output of a given rewriting rule as input to the next one. It is up to the developer to identify the right order (if it exists) among all the different rules to yield the right program. In this paper, we define a formal model compatible with the black‐box assumption that reifies the modifications (Δs) made by each rule. Leveraging these Δs, we propose a way to safely compose multiple rules when applied to the same program by (a) ensuring the isolated application of the different rules and (b) identifying unexpected behaviors that were silently ignored before. We assess this approach on two large‐scale case studies: (a) identifying conflicts in the Linux source‐code automated maintenance and (b) fixing energy antipatterns existing in Android applications available on GitHub.