Architecture Quality Attributes Research Articles

An Enterprise Architecture Approach for Assessing the Alignment Between Projects and Goals

Enterprise architecture existing approaches are expected to support the organization's evolution from a current state to a future one. Although some researches address the identification of the alignment between projects and strategic objectives, the measurement and quantification of this architectural alignment, considering the information system architecture quality attributes, is not usually considered when defining or implementing projects. This paper contributes to fulfil this gap by extending Archimate enterprise architecture framework and proposing a 4-step approach for assessing the alignment between enterprise projects and goals, namely 1) identify the alignment between the projects and the strategic objectives, 2) identify the quality attributes derived from the strategic objectives, 3) identify the applicable metrics to the projects' architecture, 4) quantify the alignment level between the projects and the strategic objectives. The results show that it is possible to use enterprise architecture for selecting projects that have higher impact on the company's strategy.

SQME: a framework for modeling and evaluation of software architecture quality attributes

Designing a software architecture that satisfies all quality requirements is a difficult task. To determine whether the requirements are achieved, it is necessary to quantitatively evaluate quality attributes on the architecture model. A good evaluation process should have proper answers for these questions: (1) how to feedback the evaluation results to the architecture model (i.e., improve the architecture based on the evaluation results), (2) how to analyze uncertainties in calculations, and (3) how to handle conflicts that may exist between the quality preferences of stakeholders. In this paper, we introduce SQME as a framework for automatic evaluation of software architecture models. The framework uses evolutionary algorithms for architecture improvement, evidence theory for uncertainty handling, and EV/TOPSIS for making trade-off decisions. To validate the applicability of the framework, a case study is performed, and a software tool is developed to support the evaluation process.

Aesthetic perception of a small office with different daylighting systems

The quality of a lit environment cannot be deduced solely from the quantity of light. Therefore, daylighting studies should not only be focused on the usage of lighting metrics but should also consider the aesthetic experience. This paper examines the influence of daylighting systems on the aesthetic perception of a small office. One single side lit office was equipped with four different daylighting systems (white blinds, high-reflecting blinds, hybrid light shelf and mirror light shelf) under two sky conditions (clear sky and overcast sky). In total, eight stimuli were captured and presented via stereoscopic images. Fifty participants evaluated the images using the semantic differential scale to rate nine architectural quality attributes. The results from MANOVA indicated that both the daylighting systems and the type of sky had an effect on the aesthetic attributes, and that the significant interaction effect suggested that the aesthetic perception of a daylighting system depends on the type of sky. Subsequent statistical findings showed that the high-reflecting blinds comprised the daylighting system that scored highest in nearly all attributes under both clear and overcast sky conditions.

Software Architecture Quality Measurement Stability and Understandability

Over the past years software architecture has become an important sub-field of software engineering. There has been substantial advancement in developing new technical approaches to start handling architectural design as an engineering discipline. Measurement is an essential part of any engineering discipline. Quantifying the quality attributes of the software architecture will reveal good insights about the architecture. It will also help architects and practioners to choose the best fit of alternative architectures that meets their needs. This work paves the way for researchers to start investigating ways to measure software architecture quality attributes. Measurement of these qualities is essential for this sub-field of software engineering. This work explores Stability and Understandability of software architecture, several metrics that affect them, and literature review of these qualities.

Distribution, Data, Deployment: Software Architecture Convergence in Big Data Systems

Exponential data growth from the Internet, low-cost sensors, and high-fidelity instruments have fueled the development of advanced analytics operating on vast data repositories. These analytics bring business benefits ranging from Web content personalization to predictive maintenance of aircraft components. To construct the data repositories underpinning these systems, rapid innovation has occurred in distributed-data-management technologies, employing schemaless data models and relaxing consistency guarantees to satisfy scalability and availability requirements. These big data systems present many challenges to software architects. Distributed-software architecture quality attributes are tightly linked to both the data and deployment architectures. This causes a consolidation of concerns, and designs must be closely harmonized across these three architectures to satisfy quality requirements.

An AHP-based approach toward enterprise architecture analysis based on enterprise architecture quality attributes

Enterprise Architecture (EA) as a discipline that manages large amount of models and information about different aspects of the enterprise, can support decision making on enterprise-wide issues. In order to provide such support, EA information should be amenable to analysis of various utilities and quality attributes. In this regard, we have proposed the idea of characterizing and using enterprise architecture quality attributes. And this paper provides a quantitative AHP-based method toward expert-based EA analysis. Our method proposes a step-by-step process of assessing quality attribute achievement of different scenarios using AHP. By this method, most suitable EA scenarios are selected according to prioritized enterprise utilities and this selection has an important affect on decision making in enterprises. The proposed method also introduces a data structure that contains required information about quality attribute achievement of different EA scenarios in enterprises. The stored asset can be used for further decision making and progress assessment in future. Sensitivity analysis is also part of the process to identify sensitive points in the decision process. The applicability of the proposed method is demonstrated using a practical case study.

Generic Pipelined Multi-Agents Architecture for Multimedia Multimodal Software Environment.

Multimodal human-computer interaction needs intelligent architectures in order to enhance the flexibility and naturelness of the user interface. These architectures have the ability to manage several multithreaded input signals from different input media in order to perform their fusion into intelligent commands. In this paper, a generic comprehensive agent-based architecture for multimodal engine fusion is proposed. The architecture is sketched in term of its relevant components. Each element is modeled using timed colored Petri networks. The generic components of the engine fusion are then included in a pipelined based-agent global architecture for which the architectural quality attributes are outlined.