Abstract: As new market opportunities, technologies, platforms, and frameworks become available, systems require large-scale and systematic architectural restructuring to accommodate them. Today’s architects have few techniques to help them plan this architecture evolution. In particular, they have little assistance in planning alternative evolution paths, trading off various aspects of the different paths, or knowing best practices for particular domains. In this paper we describe an approach for planning and reasoning about architecture evolution. Our approach focuses on providing architects with the means to model prospective evolution paths and supporting analysis to select among these candidate paths. To demonstrate the usefulness of our approach, we show how it can be applied to an actual architecture evolution. In addition, we present some theoretical results about our evolution path constraint specification language.

Abstract: Security features are often hardwired into software applications, making it difficult to adapt security responses to reflect changes in runtime context and new attacks. In prior work, we proposed the idea of architecture-based self-protection as a way of separating adaptation logic from application logic and providing a global perspective for reasoning about security adaptations in the context of other business goals. In this paper, we present an approach, based on this idea, for combating denial-of-service (DoS) attacks. Our approach allows DoS-related tactics to be composed into more sophisticated mitigation strategies that encapsulate possible responses to a security problem. Then, utility-based reasoning can be used to consider diff erent business contexts and qualities. We describe how this approach forms the underpinnings of a scientific approach to self-protection, allowing us to reason about how to make the best choice of mitigation at runtime. Moreover, we also show how formal analysis can be used to determine whether the mitigations cover the range of conditions the system is likely to encounter, and the effect of mitigations on other quality attributes of the system. We evaluate the approach using the Rainbow self-adaptive framework and show how Rainbow chooses DoS mitigation tactics that are sensitive to diff erent business contexts.

Abstract: 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.

Abstract: Recent research has developed a theoretical basis for providing software architects with better support for planning and carrying out major evolutions of software systems. However, these theoretical models have yet to be implemented in a complete, integrated tool. In this paper, we consider some of the challenges involved in developing such a tool as a plug-in to an existing architecture modeling framework. We present an experience report based on the development of a prototype architecture evolution tool as a plug-in to MagicDraw, a commercial UML tool. We find that there are many practical obstacles to developing tools for architecture evolution modeling as plug-ins, and we discuss some of the key factors that plug-in developers should weigh when considering frameworks.

Abstract: Virtually all software systems of significant size and longevity eventually undergo changes to their basic architectural structure. Such changes may be prompted by new feature requests, new quality attribute requirements, changing technology, or other reasons. Whatever the cause, software architecture evolution is commonplace in real-world software projects. However, research in this area has suffered from problems of validation; previous work has tended to make heavy use of toy examples and hypothetical scenarios and has not been well supported by real-world examples. To help address this problem, this paper presents a case study of an ongoing effort at the Jet Propulsion Laboratory to rearchitect the Advanced Multimission Operations System used to operate NASA�s deep-space and astrophysics missions. Based on examination of project documents and interviews with project personnel, I describe the goals and approach of this evolution effort, then demonstrate how approaches and formal methods from previous research in architecture evolution may be applied to this evolution while using languages and tools already in place at the Jet Propulsion Laboratory.

Abstract: As new market opportunities, technologies, platforms, and frameworks become available, systems require large-scale and systematic architectural restructuring to accommodate them. Today’s architects have few tools and techniques to help them plan this architecture evolution. In particular, they have little assistance in planning alternative evolution paths, trading-off various aspects of the different paths, or knowing best practices for particular domains. In this paper we describe an approach for assisting architects in developing and reasoning about architectural evolution paths. The key in-sight of our approach is that, architecturally, many system evolutions follow certain common patterns – or evolution styles. We define what we mean by an evolution style, and show how it can be used to provide automated assistance for expressing architectural evolution, and for reasoning about both the correctness and quality of evolution paths.

Abstract: Many software systems eventually undergo changes to their basic architectural structure. Such changes may be prompted by new feature requests, new quality attribute requirements, changing technology, or other reasons. Whatever the causes, architecture evolution is commonplace in real-world software projects. Today’s software architects, however, have few techniques to help them plan such evolution. In particular, they have little assistance in planning alternatives, making trade-offs among these different alternatives, or applying best practices for particular domains. To address this, we have developed an approach for assisting architects in planning and reasoning about software architecture evolution. Our approach is based on modeling and analyzing potential evolution paths that represent different ways of evolving the system. We represent an evolution path as a sequence of transitional architectural states leading from the initial architecture to the target architecture, along with evolution operators that characterize the transitions among these states. We support analysis of evolution paths through the definition and application of constraints that express rules governing the evolution of the systemand evaluation functions that assess path quality. Finally, a set of these modeling elements may be grouped together into an evolution style that encapsulates a body of knowledge relevant to a particular domain of architecture evolution. We evaluate this approach in three ways. First, we evaluate its applicability to real-world architecture evolution projects. This is accomplished through case studies of two very different software organizations. Second, we undertake a formal evaluation of the computational complexity of verifying evolution constraints. Finally, we evaluate the implementability of the approach based on our experiences developing prototype tools for software architecture evolution.

Abstract: Many software systems eventually undergo changes to their basic architectural structure. As systems age, they often require redesign in order to accommodate new requirements, support new technologies, or respond to changing market conditions. At present, however, software architects lack tools to assist them in developing plans for carrying out such evolution.

In previous research, we have developed an approach to support architects in reasoning about evolution. Our approach is based on formally modeling and reasoning about possible evolution paths—sequences of transitional architectures leading from the current state to some desired target architecture.

To date, much of this work has been theoretical in character. We have focused our efforts on the definition and elaboration of a theoretical framework for architecture evolution, and have done relatively little work on applying this theoretical research in practical contexts.

This report presents a case study examining architecture evolution in depth in a real-world software organization: the IT division of a major global retailer. Based on content analysis of interview data and architectural documentation, the case study examines how practicing architects plan and reason about evolution, what challenges they face in doing so, and whether our modeling approach is adequate for capturing the concerns that arise in a real-world evolution. It finds that architects face a variety of pressing challenges in planning evolutions of major software systems, and use a variety of techniques to manage these challenges. It further finds that most of the major considerations that architects described in connection within a specific evolution can be successfully modeled using our approach, suggesting that the conceptual framework and specification languages that we have developed are expressive enough to be applicable to a real-world architecture evolution.

Abstract: Analysis at the level of a runtime architecture matches the way experts reason about security or privacy better than a purely code-based strategy. However, the architecture must still be correctly realized in the implementation.

We previously developed Scholia to analyze, at compile time, communication integrity between arbitrary object-oriented code, and a rich, hierarchical intended runtime architecture, using typecheckable annotations. This paper applies Scholia to security runtime architectures. Having established traceability between the target architecture and the code, we extend Scholia to enforce structural architectural constraints. At the code level, annotations enforce local, modular constraints. At the architectural level, predicates enforce global constraints. We validate the end-to-end approach in practice using a real 3,000-line Java implementation, and enforce its conformance to a security architecture designed by an expert.