A Conceptual UX-aware Model of Requirements

User eXperience (UX) is becoming increasingly important for success of software products. Yet, many companies still face various challenges in their work with UX. Part of these challenges relate to inadequate knowledge and awareness of UX and that current UX models are commonly not practical nor well integrated into existing Software Engineering (SE) models and concepts. Therefore, we present a conceptual UX-aware model of requirements for software development practitioners. This layered model shows the interrelation between UX and functional and quality requirements. The model is developed based on current models of UX and software quality characteristics. Through the model we highlight the main differences between various requirement types in particular essentially subjective and accidentally subjective quality requirements. We also present the result of an initial validation of the model through interviews with 12 practitioners and researchers. Our results show that the model can raise practitioners' knowledge and awareness of UX in particular in relation to requirement and testing activities. It can also facilitate UX-related communication among stakeholders with different backgrounds.Comment: 6th International Working Conference on Human-Centred Software Engineerin

Is it Possible to Disregard Obsolete Requirements? A Family of Experiments in Software Effort Estimation

Context: Expert judgement is a common method for software effort estimations in practice today. Estimators are often shown extra obsolete requirements together with the real ones to be implemented. Only one previous study has been conducted on if such practices bias the estimations. Objective: We conducted six experiments with both students and practitioners to study, and quantify, the effects of obsolete requirements on software estimation. Method By conducting a family of six experiments using both students and practitioners as research subjects (N = 461), and by using a Bayesian Data Analysis approach, we investigated different aspects of this effect. We also argue for, and show an example of, how we by using a Bayesian approach can be more confident in our results and enable further studies with small sample sizes. Results: We found that the presence of obsolete requirements triggered an overestimation in effort across all experiments. The effect, however, was smaller in a field setting compared to using students as subjects. Still, the over-estimations triggered by the obsolete requirements were systematically around twice the percentage of the included obsolete ones, but with a large 95% credible interval. Conclusions: The results have implications for both research and practice in that the found systematic error should be accounted for in both studies on software estimation and, maybe more importantly, in estimation practices to avoid over-estimation due to this systematic error. We partly explain this error to be stemming from the cognitive bias of anchoring-and-adjustment, i.e. the obsolete requirements anchored a much larger software. However, further studies are needed in order to accurately predict this effect

Agile software development one year into the COVID-19 pandemic

As a result of the COVID-19 pandemic, many agile practitioners had to transition into a remote work environment. Despite remote work not being a new concept for agile software practitioners, the forced or recommended nature of remote work is new. This study investigates how the involuntary shift to remote work and how social restrictions imposed by the COVID-19 pandemic have affected agile software development (ASD), and how agile practitioners have been affected in terms of ways of working. An explanatory sequential mixed methods study was performed. Data were collected one year into the COVID-19 pandemic through a questionnaire with 96 respondents and in-depth semi-structured interviews with seven practitioners from seven different companies. Data were analyzed through Bayesian analysis and thematic analysis. The results show, in general, that the aspects of ASD that have been the most affected is communication and social interactions, while technical work aspects have not experienced the same changes. Moreover, feeling forced to work remotely has a significant impact on different aspects of ASD, e.g., productivity and communication, and industry practitioners’ employment of agile development and ways of working have primarily been affected by the lack of social interaction and the shift to digital communication. The results also suggest that there may be a group maturing debt when teams do go back into office, as digital communication and the lack of psychological safety stand in the way for practitioners’ ability to have sensitive discussions and progress as a team in a remote setting

Cost and benefit analysis of quality requirements in competitive software product management: a case study on the QUPER model

In market-driven product development, it is important that the software product is released to the market at the right time, and offers higher quality than the competitors. In release planning, the allocation of development effort in investments into product enhancements, functions are competing with quality requirements for limited resources. In addition, it is important to find the right balance between competing quality requirements. In this paper, we present an industrial evaluation of the benefit and cost views in the QUality PERformance (QUPER) model. The results indicate that the model is relevant in the release planning process, and that the combination of the benefit and cost views provides a clear picture of the current market situation

Results of matching valve and root repair to aortic valve and root pathology

ObjectiveFor patients with aortic root pathology and aortic valve regurgitation, aortic valve replacement is problematic because no durable bioprosthesis exists, and mechanical valves require lifetime anticoagulation. This study sought to assess outcomes of combined aortic valve and root repair, including comparison with matched bioprosthesis aortic valve replacement.MethodsFrom November 1990 to January 2005, 366 patients underwent modified David reimplantation (n = 72), root remodeling (n = 72), or valve repair with sinotubular junction tailoring (n = 222). Active follow-up was 99% complete, with a mean of 5.6 ± 4.0 years (maximum 17 years); follow-up for vital status averaged 8.5 ± 3.6 years (maximum 19 years). Propensity-adjusted models were developed for fair comparison of outcomes.ResultsThirty-day and 5-, 10-, and 15-year survivals were 98%, 86%, 74%, and 58%, respectively, similar to that of the US matched population and better than that after bioprosthesis aortic valve replacement. Propensity-score–adjusted survival was similar across procedures (P > .3). Freedom from reoperation at 30 days and 5 and 10 years was 99%, 92%, and 89%, respectively, and was similar across procedures (P > .3) after propensity-score adjustment. Patients with tricuspid aortic valves were more likely to be free of reoperation than those with bicuspid valves at 10 years (93% vs 77%, P = .002), equivalent to bioprosthesis aortic valve replacement and superior after 12 years. Bioprostheses increasingly deteriorated after 7 years, and hazard functions for reoperation crossed at 7 years.ConclusionsValve preservation (rather than replacement) and matching root procedures have excellent early and long-term results, with increasing survival benefit at 7 years and fewer reoperations by 12 years. We recommend this procedure for experienced surgical teams

Welcome from the Workshop Chairs

Over the last decade, the Information Technology industry has become ever more interested in evaluating Requirements Engineering (RE) approaches, techniques and tools and comparing their usefulness, effectiveness and utility in specific practical contexts. The increasing interest in empirical evaluation resulted in a growing number of industry-university collaborations in the RE community, that have been instrumental to generating empirical data through experiments, surveys, case studies, and action research studies. As empirical studies are recognized as indispensable and valuable ways to assess the actual benefits and cost of applying the RE methods and tools proposed in the RE community, the conversation on adopting systematic research methods and evaluation practices intensified. The overall objective of the EmpiRE workshop series at the annual RE conference is to increase the cross-fertilization of Empirical Software Engineering (ESE) methods and RE by actively encouraging the exchange of knowledge and ideas between the communities of ESE and RE. Since its launch at RE’11 in Trento, the EmpiRE workshop has been serving as the platform promoting the use of new evaluation techniques from ESE in the area of RE as well as the discussion on new domains and problems in RE where involving ESE will make a great difference. Some outcomes of the past editions of EmpiRE include the identification of open research problems and the possible solutions to these problems regarding: (i) the aspects of RE approaches that can be evaluated; (ii) the factors, criteria, and metrics that are appropriate for empirical evaluation purposes; (iii) the replication of empirical RE studies; (iv) the role of the users’ perspectives in empirical RE

Welcome from the Workshop Chairs

Welcome to the fifth International Workshop on Empirical Requirements Engineering (EmpiRE 2015) at RE’15!\ud In the past few years, some important developments in the Information Technology Services marketplace as well as in the software industry in particular fueled the debate on the evaluation of Requirements Engineering (RE) approaches, techniques and tools and the comparison of their usefulness, effectiveness and utility in specific practical contexts. Examples of such market trends include, among many others, the increased interest in collaborative and just-in-time application of RE techniques and the use of software analytics techniques for mining requirements repositories.Also, existing RE technology is more and more being applied in the context of new areas, such as Internet of Things, software ecosystems, green and Cloud computing, to name a few. This increased interest in empirical evaluation is precipitating a growing number of industry-university collaborations in the RE community, which, in turn, is instrumental in generating empirical data through case studies, action research studies, experiments, and surveys. As empirical studies are recognized as invaluable for assessing the actual benefits and cost of applying the RE methods and tools proposed in the RE community, the conversation on adopting these and on evaluation practices intensifies even further