Article DOI: 10.1111/j.1468-0394.2012.00625.x Eliciting and prioritizing quality requirements supported by ontologies: a case study using the ElicitO framework and tool Taiseera Hazeem Al Balushi, 1 Pedro R. Falcone Sampaio 2 and Pericles Loucopoulos 3 (1) College of Economics and Political Science, Sultan Qaboos University, P.O. Box 20, PC 123 Al Khod, Oman Email: taisira@squ.edu.om (2) Centre for Services Research Group, Manchester Business School, University of Manchester, Manchester M15 6PB, UK Email: P.Sampaio@manchester.ac.uk (3) Management Science and Information Systems Group, Loughborough University, Loughborough LE11 3TU, UK Email: P.Loucopoulos@lboro.ac.uk Abstract: As software complexity grows and clients demand higher quality software, quality requirements can no longer be considered to be of secondary importance. Thus, eliciting, specifying, prioritizing and validating quality requirements is a prerequisite to the development of effective and efficient information systems. Despite the critical importance of quality requirements, there is a considerable gap in the breadth and depth of quality requirements engineering (RE) support in most RE approaches. In practice, it is often the case to have quality requirements considered as an afterthought in the systems development process. While there is a wealth of modelling techniques and tools for functional requirements, there is very limited support for quality requirements in RE. Support for quality requirements is usually ad-hoc, without clear guidelines on how to capture, specify and manage quality requirements and also without proper usage of standardized terminologies based on established quality models such as the ISO/IEC 9126 quality model. In this paper, we discuss a quality-driven RE framework and tool that applies knowledge management techniques and quality ontologies to support RE activities. The ontology implements the quality characteristics and metrics prescribed by the ISO/9126 quality model, providing a common vocabulary to address quality concerns/aspects across RE activities. We empirically validate how the framework and tool can be used to effectively support the requirements elicitation and prioritization activities through a case study addressing the development of an intranet portal project at the University of Manchester. Keywords: nonfunctional requirements, requirements engineering, quality requirements, ontologies, case study 1. Introduction Despite the importance of departing from a correct and complete set of requirements to attain high-quality soft- ware, there are statistics showing that almost 60% of errors identified in software project deliverables originate from in- correct/incomplete requirements obtained through require- ments engineering (RE) activities (Weinberg, 1997). Incom- plete, conflicting and inconsistent requirements are leading causes of software project failures according to the Stan- dish Group (Standish group, 1994) and also according to the LASCAD and TAURAS project results (Lyytinen & Robey, 1999). Errors in requirements have a significant cost impact due to their propagation into final system deliverables. RE is a success-critical factor in software projects (Hof- mann & Lehner, 2001) as requirements reflect stakehold- ers’ needs. Thus, eliciting, specifying, validating and docu- menting these needs in a format that is amenable to analysis and communication significantly impacts the effectiveness of software project delivery (Nuseibeh & Easterbrook, 2000). RE also plays a pivotal role in identifying requirements for new value adding products and services helping to fos- ter technology-driven innovation (Kauppinen et al., 2007). There are three main types of requirements: (1) Functional Requirements, which are associated with specific functions, tasks or behaviours that the system must support (Robertson & James, 2006), (2) Non-Functional Requirements (NFRs) also known as quality requirements, which represent qual- ity properties for a particular service, function, component or the entire system, and (3) Constraints, which impose ex- plicitly defined limits on how products/services are to be constructed (Alexander & Beus-Dukic, 2009). According to (Zave, 1997; Kotonya & Sommerville, 1998; Pohl, 2010), RE encompasses several core activities: require- ments elicitation, requirements modelling/specification, re- quirements prioritization/negotiation, requirements valida- tion and requirements management. The importance of RE activities has changed considerably with the capabilities aris- ing from the Internet of Services and the Internet of Things (Pohl, 2010). Novel on demand service-oriented systems of- ten have high levels of uncertainty and complexity originat- ing from the unpredictable quality characteristics attached to the operational environments such as cloud computing and mobile computing platforms and high levels of systemic C  2012 Blackwell Publishing Ltd Expert Systems, xxx 2012, Vol. 00, No. 00 1