The essence of any modeling approach for product line architectures lies in its ability to express variability. Existing approaches do so by explicitly specifying variation points inside the architectural specification of the entire product line, usually with optional and alternative elements of some form. This, however, leads to a sizable mismatch between conceptual variability (i.e., the features through which architects logically view and interpret differences in product architectures) and actual variability (i.e., the modeling constructs through which the logical differences must be expressed). We contribute a new product line architecture modeling approach that unites the two. Our approach uses change sets to group related architectural differences and relationships to govern which change set combinations are valid when composed into a particular product architecture. The result lifts modeling of variability out of modeling architectural structure, consolidates related variation points, and explicitly and separately manages their compatibilities.

Distributed applications that lack a central, trustworthy authority for control and validation are properly termed decentralized. Multiple, independent agencies, or "partners", cooperate to achieve their separate goals. Issues of trust are paramount for designers of such partners. While the research literature has produced a variety of trust technology building blocks, few have attempted to articulate how these various technologies can regularly be composed to meet trust goals. This paper presents a particular, event-based, architectural style, PACE, that shows where and how to incorporate various types of trust-related technologies within a partner, positions the technologies with respect to the rest of the application, allows variation in the underlying network model, and works in a dynamic setting. Initial experiments with variants of two sample decentralized applications developed in the PACE style reveal the virtues of dealing with all aspects of application structure and trust in a comprehensive fashion.

Applications built in a strongly decoupled, event-based interaction style have many commendable characteristics, including ease of dynamic configuration, accommodation of platform heterogeneity, and ease of distribution over a network. It is not always easy to humanly grasp the dynamic behavior of such applications, since many threads are active and events are asynchronously (and profusely) transmitted. We present a set of requirements for an aid to assist in the human understanding and exploration of the behavior of such applications through the incremental refinement of rules for determining causality relationships between messages sent among components. A prototype tool is presented, indicating one viable approach to meeting these requirements. Experience with the tool reinforces some of the requirements and indicates others.