Data-driven elicitation, assessment and documentation of quality requirements in agile software development

Quality Requirements (QRs) are difficult to manage in agile software development. Given the pressure to deploy fast, quality concerns are often sacrificed for the sake of richer functionality. Besides, artefacts as user stories are not particularly well-suited for representing QRs. In this exploratory paper, we envisage a data-driven method, called Q-Rapids, to QR elicitation, assessment and documentation in agile software development. Q-Rapids proposes: 1) The collection and analysis of design and runtime data in order to raise quality alerts; 2) The suggestion of candidate QRs to address these alerts; 3) A strategic analysis of the impact of such requirements by visualizing their effect on a set of indicators rendered in a dashboard; 4) The documentation of the requirements (if finally accepted) in the backlog. The approach is illustrated with scenarios evaluated through a questionnaire by experts from a telecom company.Peer ReviewedPostprint (author's final draft

Towards a scope management of non-functional requirements in requirements engineering

Getting business stakeholders’ goals formulated clearly and project scope defined realistically increases the chance of success for any application development process. As a consequence, stakeholders at early project stages acquire as much as possible knowledge about the requirements, their risk estimates and their prioritization. Current industrial practice suggests that in most software projects this scope assessment is performed on the user’s functional requirements (FRs), while the non-functional requirements (NFRs) remain, by and large, ignored. However, the increasing software complexity and competition in the software industry has highlighted the need to consider NFRs as an integral part of software modeling and development. This paper contributes towards harmonizing the need to build the functional behavior of a system with the need to model the associated NFRs while maintaining a scope management for NFRs. The paper presents a systematic and precisely defined model towards an early integration of NFRs within the requirements engineering (RE). Early experiences with the model indicate its ability to facilitate the process of acquiring the knowledge on the priority and risk of NFRs

A critical analysis of the potential for EU Common Agricultural Policy measures to support wild pollinators on farmland

1. Agricultural intensification and associated loss of high‐quality habitats are key drivers of insect pollinator declines. With the aim of decreasing the environmental impact of agriculture, the 2014 EU Common Agricultural Policy (CAP) defined a set of habitat and landscape features (Ecological Focus Areas: EFAs) farmers could select from as a requirement to receive basic farm payments. To inform the post‐2020 CAP, we performed a European‐scale evaluation to determine how different EFA options vary in their potential to support insect pollinators under standard and pollinator‐friendly management, as well as the extent of farmer uptake. 2. A structured Delphi elicitation process engaged 22 experts from 18 European countries to evaluate EFAs options. By considering life cycle requirements of key pollinating taxa (i.e. bumble bees, solitary bees and hoverflies), each option was evaluated for its potential to provide forage, bee nesting sites and hoverfly larval resources. 3. EFA options varied substantially in the resources they were perceived to provide and their effectiveness varied geographically and temporally. For example, field margins provide relatively good forage throughout the season in Southern and Eastern Europe but lacked early‐season forage in Northern and Western Europe. Under standard management, no single EFA option achieved high scores across resource categories and a scarcity of late season forage was perceived. 4. Experts identified substantial opportunities to improve habitat quality by adopting pollinator‐friendly management. Improving management alone was, however, unlikely to ensure that all pollinator resource requirements were met. Our analyses suggest that a combination of poor management, differences in the inherent pollinator habitat quality and uptake bias towards catch crops and nitrogen‐fixing crops severely limit the potential of EFAs to support pollinators in European agricultural landscapes. 5. Policy Implications. To conserve pollinators and help protect pollination services, our expert elicitation highlights the need to create a variety of interconnected, well‐managed habitats that complement each other in the resources they offer. To achieve this the Common Agricultural Policy post‐2020 should take a holistic view to implementation that integrates the different delivery vehicles aimed at protecting biodiversity (e.g. enhanced conditionality, eco‐schemes and agri‐environment and climate measures). To improve habitat quality we recommend an effective monitoring framework with target‐orientated indicators and to facilitate the spatial targeting of options collaboration between land managers should be incentivised

Software Design Guidelines for Usability

For years, the Human Computer Interaction (HCI) community has crafted usability guidelines that clearly define what
characteristics a software system should have in order to be easy to use. However, in the Software Engineering (SE)
community keep falling short of successfully incorporating these recommendations into software projects. From a SE
perspective, the process of incorporating usability features into software is not always straightforward, as a large number
of these features have heavy implications in the underlying software architecture. For example, successfully including an
“undo” feature in an application requires the design and implementation of many complex interrelated data structures and
functionalities. Our work is focused upon providing developers with a set of software design patterns to assist them in the
process of designing more usable software. This would contribute to the proper inclusion of specific usability features
with high impact on the software design. Preliminary validation data show that usage of the guidelines also has positive
effects on development time and overall software design quality

Requirements: The Key to Sustainability

Software's critical role in society demands a paradigm shift in the software engineering mind-set. This shift's focus begins in requirements engineering. This article is part of a special issue on the Future of Software Engineering

Modelling and managing reliability growth during the engineering design process

[This is a keynote speech presented at the 2nd International Conference on Design Engineering and Science, discussing modelling and managing reliability growth during the engineering process.] Reliability is vital for safe and efficient operation of systems. Decisions about the configuration and selection of parts within a system, and the development activities to prove the chosen design, will influence the inherent reliability. Modelling provides a mechanism for explicating the relationship between the engineering activities and the statistical measures of reliability so that useful estimates of reliability can be obtained. Reliability modelling should be aligned to support the decisions taken during design and development. We examine why and how a reliability growth model can be structured, the type of data required and available to populate them, the selection of relevant summary measures, the process for updating estimates and feeding back into design to support planning decisions. The modelling process described is informed by our theoretical background in management science and our practical experience of working with UK industry

A framework for the selection of the right nuclear power plant

Civil nuclear reactors are used for the production of electrical energy. In the nuclear industry vendors propose several nuclear reactor designs with a size from 35–45 MWe up to 1600–1700 MWe. The choice of the right design is a multidimensional problem since a utility has to include not only financial factors as levelised cost of electricity (LCOE) and internal rate of return (IRR), but also the so called “external factors” like the required spinning reserve, the impact on local industry and the social acceptability. Therefore it is necessary to balance advantages and disadvantages of each design during the entire life cycle of the plant, usually 40–60 years. In the scientific literature there are several techniques for solving this multidimensional problem. Unfortunately it does not seem possible to apply these methodologies as they are, since the problem is too complex and it is difficult to provide consistent and trustworthy expert judgments. This paper fills the gap, proposing a two-step framework to choosing the best nuclear reactor at the pre-feasibility study phase. The paper shows in detail how to use the methodology, comparing the choice of a small-medium reactor (SMR) with a large reactor (LR), characterised, according to the International Atomic Energy Agency (2006), by an electrical output respectively lower and higher than 700 MWe