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Proceedings ArticleDOI

QuOnt: an ontology for the reuse of quality criteria

16 May 2009-pp 57-64
TL;DR: This work presents an ontology that supports the reuse of quality criteria in the input stage of software product audits and shows that the same quality criteria can be applied to different software products.
Abstract: Software product audits are knowledge-intensive tasks in which architectural knowledge plays a pivotal role. In the input stage of a software product audit, quality criteria are selected to which the software product should conform. These quality criteria resemble architectural tactics and can be viewed as a definition of the Soll-architecture of the product. Like tactics, the same quality criteria can be applied to different software products. However, there are currently no models that support the codification of quality criteria as reusable assets. In this work, we present an ontology that supports the reuse of quality criteria in the input stage of software product audits.

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Citations
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Dissertation
05 Oct 2009
TL;DR: To illustrate the effect of LSA on the document vector-space model, LSA was applied to the 8 documents from the audit that were still available, and both auditors seem to agree that there are two large document clusters.
Abstract: 2 1 1 2 4 5 5 5 5 5 concrete content 1 1 1 1 3 5 5 5 4 4 packing input for development 1 1 1 1 3 4 5 5 4 4 output of development descriptive / static 1 1 1 1 3 3 5 5 4 4 use / time dimension app. functionality 1 1 1 1 3 3 3 4 5 5 system administration design 1 1 1 1 3 4 3 5 5 5 deployment conceptual 1 1 1 2 2 4 3 4 5 5 concrete/instance high level 5 3 1 1 2 5 3 4 4 4 detailed absolute 1 1 1 1 3 5 2 2 2 2 relative (wrt prev. version) application 1 1 1 1 5 2 2 2 2 2 organisation used by me 4 2 1 2 5 2 1 1 3 3 not used by me analyzed, for instance to determine clusters of documents that contain similar documents. Figs. 16.6 and 16.7 depict the document clusters according to auditor 1 and 2 respectively. The clusters have been determined with the single linkage hierarchical clustering method (Johnson, 1967). The axis denotes the difference between the documents, calculated as 1 minus the similarity. For instance, for auditor 1 the similarity between documents FD and FM has been calculated as 0.87, therefore the difference between the two equals 0.13, as shown in Fig. 16.6. Although there are some differences between the two cluster configurations, both auditors seem to agree that there are two large document clusters. One cluster contains documents FD, FM, PD, and XX. The other documents are grouped in the second cluster. Note that we left AS and DB out of the figures to allow for a fair comparison with the effect of LSA. Recall that those two documents were no longer available, due to which LSA was unable to process them. Had we included them in the cluster figures, they would have shown as a small sub-cluster of two very similar documents (similarity according to auditor 1: 0.96; auditor 2: 1.00). For both auditors this sub-cluster is most similar to document IM (auditor 1: 0.79, auditor 2: 0.84). To illustrate the effect of LSA on the document vector-space model, we applied LSA to the 8 documents from the audit that were still available. We determined the

58 citations

Proceedings ArticleDOI
23 Oct 2009
TL;DR: This paper presents how ontology-driven visualization of architectural design decisions can be used to assist software product audits, in which independent auditors perform an assessment of a product's quality.
Abstract: There is a gradual increase of interest to use ontologies to capture architectural knowledge, in particular architectural design decisions. While ontologies seem a viable approach to codification, the application of such codified knowledge to everyday practice may be non-trivial. In particular, browsing and searching an architectural knowledge repository for effective reuse can be cumbersome. In this paper, we present how ontology-driven visualization of architectural design decisions can be used to assist software product audits, in which independent auditors perform an assessment of a product's quality. Our visualization combines the simplicity of tabular information representation with the power of on-the-fly ontological inference of decision attributes typically used by auditors. In this way, we are able to support the auditors in effectively reusing their know-how, and to actively assist the core aspects of their decision making process, namely trade-off analysis, impact analysis, and if-then scenarios. We demonstrate our visualization with examples from a real-world application.

37 citations

Book ChapterDOI
08 Aug 2014
TL;DR: System Quality and Software Architecture collects state-of-the-art knowledge on how to intertwine software quality requirements with software architecture and how quality attributes are exhibited by the architecture of the system.
Abstract: System Quality and Software Architecture collects state-of-the-art knowledge on how to intertwine software quality requirements with software architecture and how quality attributes are exhibited by the architecture of the system. Contributions from leading researchers and industry evangelists detail the techniques required to achieve quality management in software architecting, and the best way to apply these techniques effectively in various application domains (especially in cloud, mobile and ultra-large-scale/internet-scale architecture) Taken together, these approaches show how to assess the value of total quality management in a software development process, with an emphasis on architecture. The book explains how to improve system quality with focus on attributes such as usability, maintainability, flexibility, reliability, reusability, agility, interoperability, performance, and more. It discusses the importance of clear requirements, describes patterns and tradeoffs that can influence quality, and metrics for quality assessment and overall system analysis. The last section of the book leverages practical experience and evidence to look ahead at the challenges faced by organizations in capturing and realizing quality requirements, and explores the basis of future work in this area.Explains how design decisions and method selection influence overall system quality, and lessons learned from theories and frameworks on architectural qualityShows how to align enterprise, system, and software architecture for total qualityIncludes case studies, experiments, empirical validation, and systematic comparisons with other approaches already in practice.

21 citations

BookDOI
02 Nov 2015
TL;DR: This edited volume presents state of the art techniques, methodologies, tools, best practices and guidelines for software quality assurance and offers guidance for future software engineering research and practice.
Abstract: Software Quality Assurance in Large Scale and Complex Software-intensive Systems presents novel and high-quality research related approaches that relate the quality of software architecture to system requirements, system architecture and enterprise-architecture, or software testing. Modern software has become complex and adaptable due to the emergence of globalization and new software technologies, devices and networks. These changes challenge both traditional software quality assurance techniques and software engineers to ensure software quality when building today (and tomorrows) adaptive, context-sensitive, and highly diverse applications. This edited volume presents state of the art techniques, methodologies, tools, best practices and guidelines for software quality assurance and offers guidance for future software engineering research and practice. Each contributed chapter considers the practical application of the topic through case studies, experiments, empirical validation, or systematic comparisons with other approaches already in practice. Topics of interest include, but are not limited, to: quality attributes of system/software architectures; aligning enterprise, system, and software architecture from the point of view of total quality; design decisions and their influence on the quality of system/software architecture; methods and processes for evaluating architecture quality; quality assessment of legacy systems and third party applications; lessons learned and empirical validation of theories and frameworks on architectural quality; empirical validation and testing for assessing architecture quality.Focused on quality assurance at all levels of software design and developmentCovers domain-specific software quality assurance issues e.g. for cloud, mobile, security, context-sensitive, mash-up and autonomic systemsExplains likely trade-offs from design decisions in the context of complex software system engineering and quality assuranceIncludes practical case studies of software quality assurance for complex, adaptive and context-critical systems

16 citations

Book ChapterDOI
01 Jan 2011
TL;DR: This work investigates the notion of software product quality from the point of view of its integration into the modeling activities on the same level of abstraction as traditional functional models (a conceptualization of quality).
Abstract: We investigate the notion of software product quality from the point of view of its integration into the modeling activities on the same level of abstraction as traditional functional models (a conceptualization of quality) We pay special attention to the evolution of the approaches for obtaining this conceptualization through the history of conceptual modeling, propose their classification according to common attributes and outline their distinguishing features Based on the proposed classification, we outline a way of establishing an evaluation framework for quality conceptualizations aiming at supporting the choice of a conceptualization solution best suited for the problem at hand

10 citations

References
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Journal ArticleDOI
TL;DR: The Service-Centric Systems Engineering (SeCSE) project provides solutions to the challenges of specifying both requirements and services, discovering services that match user requirements, and guide service integrators to exploit Web services to improve their specifications.
Abstract: An effective solution for exploiting Web services to improve requirements must support specifying both requirements and services, discover services that match user requirements, and guide service integrators to exploit Web services to improve their specifications. The Service-Centric Systems Engineering (SeCSE) project provides solutions to these challenges.

3 citations