Untangling the Knot: Enabling Architecture Evolution with Search-Based Refactoring

Abstract

Software-reliant systems need to evolve over time to meet new requirements and take advantage of new technology. However, all too often the structure of software becomes too complex to allow rapid and cost-effective improvements. This increasing complexity is often also a sign of degrading software architecture, making isolating a portion of software for use in a new context or for clean replacement by an improved version difficult. Isolating entangled software from the rest of the architecture typically relies on manual efforts to refactor code that can take thousands of days of effort, as tools provide only limited support for such activities. In this paper, we describe a search-based algorithm that recommends a series of refactorings that collectively isolate specified software from its tangle of architectural dependencies. This approach generates recommendations that reduce problematic dependencies by more than 87% on codebases as large as 1.2M LOC and has the potential to reduce the effort required for this kind of architecture improvement by two-thirds. In walkthroughs, developers found more than 84% of the recommended refactorings acceptable. Our approach provides a much needed foundation for tool support that addresses challenges commonly encountered when improving the architecture of existing software.