88,391 research outputs found

    Preserving the Quality of Architectural Tactics in Source Code

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    In any complex software system, strong interdependencies exist between requirements and software architecture. Requirements drive architectural choices while also being constrained by the existing architecture and by what is economically feasible. This makes it advisable to concurrently specify the requirements, to devise and compare alternative architectural design solutions, and ultimately to make a series of design decisions in order to satisfy each of the quality concerns. Unfortunately, anecdotal evidence has shown that architectural knowledge tends to be tacit in nature, stored in the heads of people, and lost over time. Therefore, developers often lack comprehensive knowledge of underlying architectural design decisions and inadvertently degrade the quality of the architecture while performing maintenance activities. In practice, this problem can be addressed through preserving the relationships between the requirements, architectural design decisions and their implementations in the source code, and then using this information to keep developers aware of critical architectural aspects of the code. This dissertation presents a novel approach that utilizes machine learning techniques to recover and preserve the relationships between architecturally significant requirements, architectural decisions and their realizations in the implemented code. Our approach for recovering architectural decisions includes the two primary stages of training and classification. In the first stage, the classifier is trained using code snippets of different architectural decisions collected from various software systems. During this phase, the classifier learns the terms that developers typically use to implement each architectural decision. These ``indicator terms\u27\u27 represent method names, variable names, comments, or the development APIs that developers inevitably use to implement various architectural decisions. A probabilistic weight is then computed for each potential indicator term with respect to each type of architectural decision. The weight estimates how strongly an indicator term represents a specific architectural tactics/decisions. For example, a term such as \emph{pulse} is highly representative of the heartbeat tactic but occurs infrequently in the authentication. After learning the indicator terms, the classifier can compute the likelihood that any given source file implements a specific architectural decision. The classifier was evaluated through several different experiments including classical cross-validation over code snippets of 50 open source projects and on the entire source code of a large scale software system. Results showed that classifier can reliably recognize a wide range of architectural decisions. The technique introduced in this dissertation is used to develop the Archie tool suite. Archie is a plug-in for Eclipse and is designed to detect wide range of architectural design decisions in the code and to protect them from potential degradation during maintenance activities. It has several features for performing change impact analysis of architectural concerns at both the code and design level and proactively keep developers informed of underlying architectural decisions during maintenance activities. Archie is at the stage of technology transfer at the US Department of Homeland Security where it is purely used to detect and monitor security choices. Furthermore, this outcome is integrated into the Department of Homeland Security\u27s Software Assurance Market Place (SWAMP) to advance research and development of secure software systems

    Digital Architecture as Crime Control

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    This paper explains how theories of realspace architecture inform the prevention of computer crime. Despite the prevalence of the metaphor, architects in realspace and cyberspace have not talked to one another. There is a dearth of literature about digital architecture and crime altogether, and the realspace architectural literature on crime prevention is often far too soft for many software engineers. This paper will suggest the broad brushstrokes of potential design solutions to cybercrime, and in the course of so doing, will pose severe criticisms of the White House\u27s recent proposals on cybersecurity. The paper begins by introducing four concepts of realspace crime prevention through architecture. Design should: (1) create opportunities for natural surveillance, meaning its visibility and susceptibility to monitoring by residents, neighbors, and bystanders; (2) instill a sense of territoriality so that residents develop proprietary attitudes and outsiders feel deterred from entering a private space; (3) build communities and avoid social isolation; and (4) protect targets of crime. There are digital analogues to each goal. Natural-surveillance principles suggest new virtues of open-source platforms, such as Linux, and territoriality outlines a strong case for moving away from digital anonymity towards psuedonymity. The goal of building communities will similarly expose some new advantages for the original, and now eroding, end-to-end design of the Internet. An understanding of architecture and target prevention will illuminate why firewalls at end points will more effectively guarantee security than will attempts to bundle security into the architecture of the Net. And, in total, these architectural lessons will help us chart an alternative course to the federal government\u27s tepid approach to computer crime. By leaving the bulk of crime prevention to market forces, the government will encourage private barricades to develop - the equivalent of digital gated communities - with terrible consequences for the Net in general and interconnectivity in particular

    A concern-oriented approach to software architecture

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    A major cause of many complications in the field of software architectures is the lack of appropriate abstractions for separating, combining and encapsulating concerns of various kinds in architectural descriptions. Architectures of most complex software-intensive systems involve concerns that inherently crosscut the natural boundaries of the elements composing the architecture descriptions. Crosscutting concerns intersect the common modularity of systems as prescribed by their architecture descriptions, by traversing both the components and connectors, i.e., the relationships among the components. Crosscutting concerns are critical aspects of many architectural problems. However, architectural descriptions written in special-purpose languages (ADLs) like Wright, Darwin, Rapide and Acme should support descriptions of multiple structures, which include diagrams, models and views, that intentionally address different kinds of concerns. ADLs should show how various concerns affect each other in architectural designs; they should also allow one to identify, analyze and elaborate architectural concerns that cut across several software components, such as transactions, security, load balancing, synchronization, reuse, customization, scalability, etc.; they should, but they do not. This dissertation presents a new approach to software architecture that is suitable for supporting concern-oriented development and documentation of architectures for software-intensive systems. This approach allows for creating and documenting a multidimensional software structure that is referred to as concern-oriented software architecture; it provides new mechanisms for encapsulating individual concerns into independent architectural constructs. The ultimate goal of this new approach is to provide support for achieving design by concerns all through the development and description of software architectures. Moving towards this goal, we present a particular concern-oriented architectural framework called Perspectival Concern-Spaces (PCS). The PCS Framework offers a flexible and extensible means a) for supporting advanced separation of concerns in architectural design, and in the construction and evolution of software-intensive systems; and b) for filling the gap between architectural descriptions and modern software development artifacts. To show the feasibility of the proposed approach, we provide new modeling techniques that are used to describe and apply an aspect-oriented architectural pattern, called the On-demand Remodularization pattern. We give several examples of how the PCS Framework can be used to integrate concern-oriented architectural documentations with mainstream software development artifacts

    Towards a Layered Architectural View for Security Analysis in SCADA Systems

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    Supervisory Control and Data Acquisition (SCADA) systems support and control the operation of many critical infrastructures that our society depend on, such as power grids. Since SCADA systems become a target for cyber attacks and the potential impact of a successful attack could lead to disastrous consequences in the physical world, ensuring the security of these systems is of vital importance. A fundamental prerequisite to securing a SCADA system is a clear understanding and a consistent view of its architecture. However, because of the complexity and scale of SCADA systems, this is challenging to acquire. In this paper, we propose a layered architectural view for SCADA systems, which aims at building a common ground among stakeholders and supporting the implementation of security analysis. In order to manage the complexity and scale, we define four interrelated architectural layers, and uses the concept of viewpoints to focus on a subset of the system. We indicate the applicability of our approach in the context of SCADA system security analysis.Comment: 7 pages, 4 figure
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