GenAI is bringing a profound shift in just about every area of our lives — how we interact, work, and as engineers, how we build products and systems. Some changes are alreadyhere while others will take time to play out. In this talk I will focus on what this generational technology shift means for the current web, and highlight some of the areas we should be focused on to successfully apply this technology to many domains.

A distributed system's allocation of software components to hardware nodes (i.e., deployment architecture) can have a significant impact on its quality of service (QoS). For a given system, there may be many deployment architectures that provide the same functionality, but with different levels of QoS. The parameters that influence the quality of a system's deployment architecture are often not known before the system's initial deployment and may change at runtime. This means that redeployment of the software system may be necessary to improve the system's QoS properties. This paper presents and evaluates a framework aimed at finding the most appropriate deployment architecture for a distributed software system with respect to multiple, possibly conflicting QoS dimensions. The framework supports formal modeling of the problem and provides a set of tailorable algorithms for improving a system's deployment. We have realized the framework on top of a visual deployment architecture modeling and analysis environment. The framework has been evaluated for precision and execution-time complexity on a large number of simulated distributed system scenarios, as well as in the context of two third-party families of distributed applications.

A recent emergence of small, resource-constrained, and highly mobile computing platforms presents numerous new challenges for software developers. We refer to development in this new setting as programming-in-the-small-and-many (Prism). This paper provides a description and evaluation of Prism-MW, a middleware platform intended to support software architecture-based development in the Prism setting. Prism-MW provides efficient and scalable implementation-level support for the key aspects of Prism application architectures, including their architectural styles. Additionally, Prism-MW is extensible to support different application requirements suitable for the Prism setting. Prism-MW has been applied in a number of applications and used as an educational tool in graduate-level software architecture and embedded systems courses. Recently, Prism-MW has been successfully evaluated by a major industrial organization for use in one of their key distributed embedded systems. Our experience with the middleware indicates that the principles of architecture-based software development can be successfully, and flexibly, applied in the Prism setting.

As with any other artifact produced as part of the software life cycle, software architectures evolve and this evolution must be managed. One approach to doing so would be to apply any of a host of existing configuration management systems, which have long been used successfully at the level of source code. Unfortunately, such an approach leads to many problems that prevent effective management of architectural evolution. To overcome these problems, we have developed an alternative approach centered on the use of an integrated architectural and configuration management system model. Because the system model combines architectural and configuration management concepts in a single representation, it has the distinct benefit that all architectural changes can be precisely captured and clearly related to each other---both at the fine-grained level of individual architectural elements and at the coarse-grained level of architectural configurations. To support the use of the system model, we have developed Mae, an architectural evolution environment through which users can specify architectures in a traditional manner, manage the evolution of the architectures using a check-out/check-in mechanism that tracks all changes, select a specific architectural configuration, and analyze the consistency of a selected configuration. We demonstrate the benefits of our approach by showing how the system model and its accompanying environment were used in the context of several representative projects.

In the world of software development everything evolves. So, then, do software architectures. Unlike source code, for which the use of a configuration management (CM) system is the predominant approach to capturing and managing evolution, approaches to capturing and managing architectural evolution span a wide range of disconnected alternatives. This paper contributes a novel architecture evolution environment, called Mae, which brings together a number of these alternatives. The environment facilitates an incremental design process in which all changes to all architectural elements are integrally captured and related. Key to the environment is a rich system model that combines architectural concepts with those from the field of CM. Not only does this system model form the basis for Mae, but in precisely capturing architectural evolution it also facilitates automated support for several innovative capabilities that rely on the integrated nature of the system model. This paper introduces three of those: the provision of design guidance at the architectural level, the use of specialized software connectors to ensure run-time reliability during component upgrades, and the creation of component-level patches to be applied to deployed system configurations.