Modelling the Strategic Alignment of Software Requirements using Goal Graphs

This paper builds on existing Goal Oriented Requirements Engineering (GORE) research by presenting a methodology with a supporting tool for analysing and demonstrating the alignment between software requirements and business objectives. Current GORE methodologies can be used to relate business goals to software goals through goal abstraction in goal graphs. However, we argue that unless the extent of goal-goal contribution is quantified with verifiable metrics and confidence levels, goal graphs are not sufficient for demonstrating the strategic alignment of software requirements. We introduce our methodology using an example software project from Rolls-Royce. We conclude that our methodology can improve requirements by making the relationships to business problems explicit, thereby disambiguating a requirement's underlying purpose and value.Comment: v2 minor updates: 1) bitmap images replaced with vector, 2) reworded related work ref[6] for clarit

Towards an Approach for Analysing the Strategic Alignment of Software Requirements using Quantified Goal Graphs

Analysing the strategic alignment of software requirements primarily provides assurance to stakeholders that the software-to-be will add value to the organisation. Additionally, such analysis can improve a requirement by disambiguating its purpose and value, thereby supporting validation and value-oriented decisions in requirements engineering processes, such as prioritisation, release planning, and trade-off analysis. We review current approaches that could enable such an analysis. We focus on Goal Oriented Requirements Engineering methodologies, since goal graphs are well suited for relating software goals to business goals. However, we argue that unless the extent of goal-goal contribution is quantified with verifiable metrics, goal graphs are not sufficient for demonstrating the strategic alignment of software requirements. Since the concept of goal contribution is predictive, what results is a forecast of the benefits of implementing software requirements. Thus, we explore how the description of the contribution relationship can be enriched with concepts such as uncertainty and confidence, non-linear causation, and utility. We introduce the approach using an example software project from Rolls-Royce.Comment: arXiv admin note: text overlap with arXiv:1211.625

Repetition between stakeholder (user) and system requirements

Stakeholder requirements (also known as user requirements) are defined at an early stage of a software project to describe the problem(s) to be solved. At a later stage, abstract solutions to those problems are prescribed in system requirements. The quality of these requirements has long been linked to the quality of the software system and its development or procurement process. However, little is known about the quality defect of redundancy between these two sets of requirements. Previous literature is anecdotal rather than exploratory, and so this paper empirically investigates its occurrence and consequences with a case study from a UK defense contractor. We report on a survey of sixteen consultants to understand their perception of the problem, and on an analysis of real-world software requirements documents using natural language processing techniques. We found that three quarters of the consultants had seen repetition in at least half of their projects. Additionally, we found that on average, a third of the requirement pairs’ (comprised of a system and its related stakeholder requirement) description fields were repeated such that one requirement in the pair added only trivial information. That is, solutions were described twice while their respective problems were not described, which ultimately lead to suboptimal decisions later in the development process, as well as reduced motivation to read the requirements set. Furthermore, the requirement fields considered to be secondary to the primary “description” field, such as the “rationale” or “fit criterion” fields, had considerably more repetition within UR–SysR pairs. Finally, given that the UR–SysR repetition phenomena received most of its discussion in the literature over a decade ago, it is interesting that the survey participants did not consider its occurrence to have declined since then. We provide recommendations on preventing the defect, and describe the freely available tool developed to automatically detect its occurrence and alleviate its consequences

A national-scale assessment of climate change impacts on species: assessing the balance of risks and opportunities for multiple taxa

It is important for conservationists to be able to assess the risks that climate change poses to species, in order to inform decision making. Using standardised and repeatable methods, we present a national-scale assessment of the risks of range loss and opportunities for range expansion, that climate change could pose for over 3,000 plants and animals that occur in England. A basic risk assessment that compared projected future changes in potential range with recently observed changes classified 21% of species as being at high risk and 6% at medium risk of range loss under a B1 climate change scenario. A greater number of species were classified as having a medium (16%) or high (38%) opportunity to potentially expand their distribution. A more comprehensive assessment, incorporating additional ecological information, including potentially confounding and exacerbating factors, was applied to 402 species, of which 35 % were at risk of range loss and 42 % may expand their range extent. This study covers a temperate region with a significant proportion of species at their poleward range limit. The balance of risks and opportunities from climate change may be different elsewhere. The outcome of both risk assessments varied between taxonomic groups, with bryophytes and vascular plants containing the greatest proportion of species at risk from climate change. Upland habitats contained more species at risk than other habitats. Whilst the overall pattern was clear, confidence was generally low for individual assessments, with the exception of well-studied taxa such as birds. In response to climate change, nature conservation needs to plan for changing species distributions and increasing uncertainty of the future

Introduction to special issue:New Times Revisited: Britain in the 1980s

The authors in this volume are collectively engaged with a historical puzzle: What happens if we examine the decade once we step out of the shadows cast by Thatcher? That is, does the decade of the 1980s as a significant and meaningful periodisation (equivalent to that of the 1960s) still work if Thatcher becomes but one part of the story rather than the story itself? The essays in this collection suggest that the 1980s only makes sense as a political period. They situate the 1980s within various longer term trajectories that show the events of the decade to be as much the consequence as the cause of bigger, long-term historical processes. This introduction contextualises the collection within the wider literature, before explaining the collective and individual contributions made

Dimethyl fumarate in patients admitted to hospital with COVID-19 (RECOVERY): a randomised, controlled, open-label, platform trial

Dimethyl fumarate (DMF) inhibits inflammasome-mediated inflammation and has been proposed as a treatment for patients hospitalised with COVID-19. This randomised, controlled, open-label platform trial (Randomised Evaluation of COVID-19 Therapy [RECOVERY]), is assessing multiple treatments in patients hospitalised for COVID-19 (NCT04381936, ISRCTN50189673). In this assessment of DMF performed at 27 UK hospitals, adults were randomly allocated (1:1) to either usual standard of care alone or usual standard of care plus DMF. The primary outcome was clinical status on day 5 measured on a seven-point ordinal scale. Secondary outcomes were time to sustained improvement in clinical status, time to discharge, day 5 peripheral blood oxygenation, day 5 C-reactive protein, and improvement in day 10 clinical status. Between 2 March 2021 and 18 November 2021, 713 patients were enroled in the DMF evaluation, of whom 356 were randomly allocated to receive usual care plus DMF, and 357 to usual care alone. 95% of patients received corticosteroids as part of routine care. There was no evidence of a beneficial effect of DMF on clinical status at day 5 (common odds ratio of unfavourable outcome 1.12; 95% CI 0.86-1.47; p = 0.40). There was no significant effect of DMF on any secondary outcome

Modelling the instrumental value of software requirements

Numerous studies have concluded that roughly half of all implemented software requirements are never or rarely used in practice, and that failure to realise expected benefits is a major cause of software project failure. This thesis presents an exploration of these concepts, claims, and causes. It evaluates the literature s proposed solutions to them, and then presents a unified framework that covers additional concerns not previously considered. The value of a requirement is assessed often during the requirements engineering (RE) process, e.g., in requirement prioritisation, release planning, and trade-off analysis. In order to support these activities, and hence to support the decisions that lead to the aforementioned waste, this thesis proposes a framework built on the modelling languages of Goal Oriented Requirements Engineering (GORE), and on the principles of Value Based Software Engineering (VBSE). The framework guides the elicitation of a requirement s value using philosophy and business theory, and aims to quantitatively model chains of instrumental value that are expected to be generated for a system s stakeholders by a proposed software capability. The framework enriches the description of the individual links comprising these chains with descriptions of probabilistic degrees of causation, non-linear dose-response and utility functions, and credibility and confidence. A software tool to support the framework s implementation is presented, employing novel features such as automated visualisation, and information retrieval and machine learning (recommendation system) techniques. These software capabilities provide more than just usability improvements to the framework. For example, they enable visual comprehension of the implications of what-if? questions, and enable re-use of previous models in order to suggest modifications to a project s requirements set, and reduce uncertainty in its value propositions. Two case studies in real-world industry contexts are presented, which explore the problem and the viability of the proposed framework for alleviating it. The thesis research questions are answered by various methods, including practitioner surveys, interviews, expert opinion, real-world examples and proofs of concept, as well as less-common methods such as natural language processing analysis of real requirements specifications (e.g., using TF-IDF to measure the proportion of software requirement traceability links that do not describe the requirement s value or problem-to-be-solved). The thesis found that in general, there is a disconnect between the state of best practice as proposed by the literature, and current industry practice in requirements engineering. The surveyed practitioners supported the notion that the aforementioned value realisation problems do exist in current practice, that they would be treatable by better requirements engineering practice, and that this thesis proposed framework would be useful and usable in projects whose complexity warrants the overhead of requirements modelling (e.g., for projects with many stakeholders, competing desires, or having high costs of deploying incorrect increments of software functionality)