In previous research, we have developed a theoretical framework to help software architects make better decisions when planning software evolution. Our approach is based on representation and analysis of candidate evolution paths-sequences of transitional architectures leading from the current system to a desired target architecture. One problem with this kind of approach is that it imposes a heavy burden on the software architect, who must explicitly define and model these candidate paths. In this paper, we show how automated planning techniques can be used to support automatic generation of evolution paths, relieving this burden on the architect. We illustrate our approach by applying it to a data migration scenario, showing how this architecture evolution problem can be translated into a planning problem and solved using existing automated planning tools.

We present a semi-automated approach, SECORIA, for analyzing a security runtime architecture for security and for conformance to an object-oriented implementation. Type-checkable annotations describe architectural intent within the code, enabling a static analysis to extract a hierarchical object graph that soundly reflects all runtime objects and runtime relations between them. In addition, the annotations can describe modular, code-level policies. A separate analysis establishes traceability between the extracted object graph and a target architecture documented in an architecture description language. Finally, architectural types, properties, and logic predicates describe global constraints on the target architecture, which will also hold in the implementation. We validate the SECORIA approach by analyzing a 3,000-line pedagogical Java implementation and a runtime architecture designed by a security expert.