Differencing and merging of architectural views

Differencing and merging architectural views is an important activity in software engineering. However, existing approaches are still based on restrictive assumptions, such as requiring view elements to have unique identifiers or exactly matching types, which is often not the case in many application domains. We propose an approach based on structural information. We generalize a published polynomial-time tree-to-tree correction algorithm that detects inserts, renames and deletes, into a novel algorithm that additionally detects restricted moves. Our algorithm also supports forcing and preventing matches between view elements. We incorporate the algorithm into tools to compare and merge Component-and-Connector (C&C) architectural views. We provide an empirical evaluation of the algorithm. We illustrate the tools using extended examples, and use them to detect and reconcile interesting differences between real architectural views. This article is an expanded version of the following paper: Abi-Antoun, M., Aldrich, J., Nahas, N., Schmerl, B., and Garlan, D: 2006, ‘Differencing and Merging of Architectural Views’. In: Proceedings of the 21st IEEE International Conference on Automated Software Engineering, pp. 47–58.     

Architectural styles, design patterns, and objects

Architectural styles, object-oriented design and design patterns all hold promise as approaches that simplify software design and reuse by capturing and exploiting system design knowledge. This article explores the capabilities and roles of the various approaches, their strengths and their limitations     

Agents of change: educating software engineering leaders

Most professional degree programs for software engineering focus on solving today's problems with today's technologies. Carnegie Mellon's Master of Software Engineering program takes a different approach, preparing engineers to work with new science and technology throughout their careers and helping them become agents of change in the industry. The approach aims to cultivate future leaders in software engineering. It combines a long-term, mentored software development project with an unusual core curriculum that stresses broad-based models and problem-solving skills     

Using tool abstraction to compose systems

The tool abstraction paradigm, which supports the evolution of large-scale software systems by easing design changes in the system functions, is discussed. Systems that support tool abstraction are structured as a pool of abstract data structures shared by a collection of cooperating `toolies', where each toolie provides a piece of the overall system function. When one toolie updates the shared data, other toolies must be notified: otherwise, cooperating-but-independent toolies may not execute, and the overall system function may be compromised. The KWIC (key word in context) index production system is used to illustrate the idea of tool abstraction. The relationship of tool abstraction to other concepts is examined     

Towards a Formal Treatment of Implicit Invocation Using Rely/Guarantee Reasoning

Implicit invocation [SuN92, GaN91] has become an important architectural style for large-scale system design and evolution. This paper addresses the lack of specification and verification formalisms for such systems. A formal computational model for implicit invocation is presented. We develop a verification framework for implicit invocation that is based on Jones' rely/guarantee reasoning for concurrent systems [Jon83, St?91]. The application of the framework is illustrated with several examples. The merits and limitations of the rely/guarantee paradigm in the context of implicit invocation systems are also discussed. Received August 1997 / Accepted in revised form June 1998     

The uncertainty interaction problem in self-adaptive systems

Software and Systems Modeling - The problem of mitigating uncertainty in self-adaptation has driven much of the research proposed in the area of software engineering for self-adaptive systems in...     

Task-based adaptation for ubiquitous computing

An important domain for autonomic systems is the area of ubiquitous computing: users are increasingly surrounded by technology that is heterogeneous, pervasive, and variable. In this paper we describe our work in developing self-adapting computing infrastructure that automates the configuration and reconfiguration of such environments. Focusing on the engineering issues of self-adaptation in the presence of heterogeneous platforms, legacy applications, mobile users, and resource variable environments, we describe a new approach based on the following key ideas: 1) explicit representation of user tasks allows us to determine what service qualities are required of a given configuration; 2) decoupling task and preference specification from the lower level mechanisms that carry out those preferences provides a clean engineering separation of concerns between what is needed and how it is carried out; and 3) efficient algorithms allow us to calculate in real time near-optimal resource allocations and reallocations for a given task.     

Evolution styles: foundations and models for software architecture evolution

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.