719 research outputs found

    On the real world practice of Behaviour Driven Development

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    Surveys of industry practice over the last decade suggest that Behaviour Driven Development is a popular Agile practice. For example, 19% of respondents to the 14th State of Agile annual survey reported using BDD, placing it in the top 13 practices reported. As well as potential benefits, the adoption of BDD necessarily involves an additional cost of writing and maintaining Gherkin features and scenarios, and (if used for acceptance testing,) the associated step functions. Yet there is a lack of published literature exploring how BDD is used in practice and the challenges experienced by real world software development efforts. This gap is significant because without understanding current real world practice, it is hard to identify opportunities to address and mitigate challenges. In order to address this research gap concerning the challenges of using BDD, this thesis reports on a research project which explored: (a) the challenges of applying agile and undertaking requirements engineering in a real world context; (b) the challenges of applying BDD specifically and (c) the application of BDD in open-source projects to understand challenges in this different context. For this purpose, we progressively conducted two case studies, two series of interviews, four iterations of action research, and an empirical study. The first case study was conducted in an avionics company to discover the challenges of using an agile process in a large scale safety critical project environment. Since requirements management was found to be one of the biggest challenges during the case study, we decided to investigate BDD because of its reputation for requirements management. The second case study was conducted in the company with an aim to discover the challenges of using BDD in real life. The case study was complemented with an empirical study of the practice of BDD in open source projects, taking a study sample from the GitHub open source collaboration site. As a result of this Ph.D research, we were able to discover: (i) challenges of using an agile process in a large scale safety-critical organisation, (ii) current state of BDD in practice, (iii) technical limitations of Gherkin (i.e., the language for writing requirements in BDD), (iv) challenges of using BDD in a real project, (v) bad smells in the Gherkin specifications of open source projects on GitHub. We also presented a brief comparison between the theoretical description of BDD and BDD in practice. This research, therefore, presents the results of lessons learned from BDD in practice, and serves as a guide for software practitioners planning on using BDD in their projects

    AI: Limits and Prospects of Artificial Intelligence

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    The emergence of artificial intelligence has triggered enthusiasm and promise of boundless opportunities as much as uncertainty about its limits. The contributions to this volume explore the limits of AI, describe the necessary conditions for its functionality, reveal its attendant technical and social problems, and present some existing and potential solutions. At the same time, the contributors highlight the societal and attending economic hopes and fears, utopias and dystopias that are associated with the current and future development of artificial intelligence

    A systematic literature review on source code similarity measurement and clone detection: techniques, applications, and challenges

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    Measuring and evaluating source code similarity is a fundamental software engineering activity that embraces a broad range of applications, including but not limited to code recommendation, duplicate code, plagiarism, malware, and smell detection. This paper proposes a systematic literature review and meta-analysis on code similarity measurement and evaluation techniques to shed light on the existing approaches and their characteristics in different applications. We initially found over 10000 articles by querying four digital libraries and ended up with 136 primary studies in the field. The studies were classified according to their methodology, programming languages, datasets, tools, and applications. A deep investigation reveals 80 software tools, working with eight different techniques on five application domains. Nearly 49% of the tools work on Java programs and 37% support C and C++, while there is no support for many programming languages. A noteworthy point was the existence of 12 datasets related to source code similarity measurement and duplicate codes, of which only eight datasets were publicly accessible. The lack of reliable datasets, empirical evaluations, hybrid methods, and focuses on multi-paradigm languages are the main challenges in the field. Emerging applications of code similarity measurement concentrate on the development phase in addition to the maintenance.Comment: 49 pages, 10 figures, 6 table

    The Influence of Neuroendocrine and Genetic Markers of Stress on Cognitive Processing and Intrusive Symptoms

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    This body of research investigated the influence of neuroendocrine and genetic elements of arousal on cognitive processes in the development of intrusive memories and flash-forward intrusions as related to Post-Traumatic Stress Disorder. Specifically, this thesis investigated various mechanisms that may underlie intrusive symptoms as postulated by prevalent theories of PTSD. Study 1 examined the distinctive relationship between peritraumatic dissociation and subsequent re-experiencing symptoms. Network analyses revealed strong positive edges between peritraumatic dissociation and subsequent amnesia, as well as the re-experiencing symptoms of physical reactivity to reminders, flashbacks, intrusions, and dreams, and to a lesser extent emotional numbness and hypervigilance. The finding that peritraumatic dissociation is related to subsequent re-experiencing symptoms is consistent with cognitive models that emphasize the role of dissociative experiences during a traumatic event in the etiology of PTSD re-experiencing symptoms. Study 2 aimed to determine whether peri-traumatic stress, as measured via salivary cortisol and salivary alpha-amylase, as well as pre-existing genetic polymorphisms on the FKBP5 gene increased dissociation and data-driven processing, and subsequently impacted intrusive memories related to a trauma film. The findings revealed that greater noradrenergic arousal predicted less intrusive memory distress in individuals who scored higher on data-driven processing and trait dissociation, and in FKBP5 low-risk carriers. For individuals who reported less data-driven processing and trait dissociation, and in FKBP5 high-risk carriers, as noradrenergic arousal increased, intrusive memory distress increased. This study also showed no association between data-driven processing with memory fragmentation, and fragmentation with intrusive memories. Whilst these findings support some aspect of cognitive models of PTSD as they indicate a role for data-driven processing and dissociation in intrusive symptoms, they highlight a threshold at which these variables stop moderating the relationship between arousal and intrusive memories and suggest that memory fragmentation is not related to intrusive memories. Study 3 examined the role of cognitive control in flash-forward intrusions in the context of an enduring stressor, the COVID-19 pandemic. In line with expectations, results showed that as cognitive control worsened, FKBP5 high-risk carriers reported more flash-forward distress, and low-risk carriers reported less distress. These findings are considered in the context of hippocampal changes and are consistent with emerging theories of PTSD. Lastly, study 4 sought to investigate the role of two neurological processes, pattern separation and pattern completion in intrusive memories in individuals with PTSD compared to trauma exposed controls. Consistent with existing literature, the data indicate that individuals with PTSD reported more data-driven processing, more intrusive symptoms, and demonstrated better behavioural pattern completion than trauma-exposed controls. These findings are in line with current cognitive models of PTSD, as they again indicate a role for data-driven processing in PTSD. However, study 4 found no support for the postulate that deficient pattern separation is a feature of PTSD and found an opposite effect for the role of pattern completion. Whilst these findings are inconsistent with theory, they are in line with existing experimental studies. Overall, the findings from this thesis provide insight into cognitive and biological models of PTSD and shed light on the mechanisms underlying the nature and development of intrusive symptoms

    “Have patients with chronic skin diseases needs been met?”:A thesis on psoriasis and eczema patient care in dermatology service

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    Background: Common chronic skin diseases such as eczema and psoriasis usually require long term medical care. They are often associated with psychological and metabolic comorbidities, which can impact on patient quality of life (QOL) and on the self-management of these diseases. Regular assessment of patient needs, comorbidities and feedback is a critical step in the development of decision-analytic models. Currently, no intervention is available to regularly assess such patients’ needs and comorbidities and support their involvement in the decision-making and self-management of their morbidity and comorbidities. The aim of this research is to involve the patients in decision making of their care and to support their self-management by the use of a paper questionnaire (study tool) at each consultation. Objective: To explore the acceptability and potential of a self-developed paper questionnaire that constituted a study tool for addressing the needs, comorbidities, and feedback of patients with psoriasis and eczema and supporting their involvement in decision making and self-management of their chronic conditions. Method: A mixed method study was conducted and included a postal survey on adult male and female patients with psoriasis and eczema, using the study tool, which is a paper questionnaire and contains the Dermatology Life Quality Index (DLQI) and seven supplementary open-ended questions to capture patients’ views, feedback, comorbidities, coping status and needs. The survey was followed by semi-structured face-to-face interviews with a sample of the patients who had participated in the survey. The aims of the interviews were two-fold: 1. to gain a deeper understanding of their experience of living with and managing their skin disease; and 2. to gather patient feedback on the service they received as well as their views on using the new study tool or any alternative intervention to address and support their self-management. The final study was a pilot which involved presenting a proposal of an online version of the study tool to a group of healthcare experts asking them to critically review the extent to which the online model responded to patients expressed needs. Results: Of the 114 patients who participated in the postal survey 108 (94.7%) of them expressed physical, metabolic and psychological comorbidities. Stress was identified as the dominant disease-triggering factor in 72 (63%) participants. Thirty-three (28.9%) of participants reported that they could not cope with their chronic illness. Eighteen (15.7%) participants suffered from anxiety, and 12 (10.5%) had depression and suicidal thoughts. Twenty-nine (25%) participants addressed their needs for support at home, and 16 (14%) of them asked for support at work. In the patient feedback section, 21 (18.4%) and 9 (7.8%) participants rated the service they received from their general practitioner (GP) and dermatologist as poor, respectively. In the interviews, all the participants 22 (100%) welcomed the use of the study tool on a regular basis to address their needs, comorbidities and feedback. Nineteen (86.3%) of them suggested that they would prefer using an online version of the tool or patient portal system as a convenient way of remote and interactive communication with the healthcare provider, particularly during the worsening of their skin condition. In the final pilot study, the healthcare experts agreed that the proposed online version of the study tool could be a convenient platform for such patients to support their self-management. They discussed the potential importance of such a tool if it provided them with access to supportive services such as patient information on skin diseases and self-management, access to local mental health service and other relevant psoriasis and eczema patients’ support groups and charities. Conclusion: This novel mixed method research identified knowledge gaps in managing patients with psoriasis and eczema. It provided a new tool that has the potential to regularly engage and assess patients’ unmet needs, comorbidities and feedback. The tool can involve patients in decision-making and offers them the autonomy to disclose heterogeneous needs that may support their self-management. All the interviewees welcomed regular use of the study tool and the majority of them suggested that they would prefer using an online version of the tool if it was available. Future research is needed to assess the impact of the study tool in filling important gaps in patient self-management and in health service improvement

    Sensing Collectives: Aesthetic and Political Practices Intertwined

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    Are aesthetics and politics really two different things? The book takes a new look at how they intertwine, by turning from theory to practice. Case studies trace how sensory experiences are created and how collective interests are shaped. They investigate how aesthetics and politics are entangled, both in building and disrupting collective orders, in governance and innovation. This ranges from populist rallies and artistic activism over alternative lifestyles and consumer culture to corporate PR and governmental policies. Authors are academics and artists. The result is a new mapping of the intermingling and co-constitution of aesthetics and politics in engagements with collective orders

    Predicting code refactoring via analyzing the history of quality metrics and code anti-patterns

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    Code refactoring is the process of improving the internal structure of existing code without altering its functionality. Refactoring can help to reduce technical debt, enhance the quality of the code and make the code easy to evolve. However, the manual identification of the proper code refactoring operations to apply can be time-consuming and not scalable. In this thesis, we propose an approach based on data mining and machine learning techniques to analyze historical data and predict refactoring operations that may occur in a future release of a project. The approach uses a combination of techniques to identify patterns in the data and make predictions about which refactoring operations should be applied. In this study, we validated the proposed machine learning based approaches with 13 open-source projects with different releases. We identified the refactoring operations and code smells and extracted the quality metrics for each project release. We used the collected data (e.g. quality metrics and code smells) to predict refactoring operations, and we reported the prediction results based on cross- validation procedures. The proposed research contributes to the field of software quality by providing an efficient and effective approach to refactor the code. The findings of this research will also help developers by suggesting appropriate refactoring operations based on the history of the evolution of software projects. This will ultimately result in improved software quality, reduced technical debt, and enhanced software performance

    THE SEMIOTIC USE OF EMOJIS IN MARKETING COMMUNICATION

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    Despite the emergence of social media as the primary tool for communication in social and business settings, research on effectiveness of communication using of emojis is limited. This project seeks to bridge the gap in understanding the effectiveness of the use of emojis in marketing communication. In particular, the dissertation will focus on an interpretive exploration of the use of emojis in marketing communication as a semiotic that supports persuasion

    Digital agriculture: research, development and innovation in production chains.

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    Digital transformation in the field towards sustainable and smart agriculture. Digital agriculture: definitions and technologies. Agroenvironmental modeling and the digital transformation of agriculture. Geotechnologies in digital agriculture. Scientific computing in agriculture. Computer vision applied to agriculture. Technologies developed in precision agriculture. Information engineering: contributions to digital agriculture. DIPN: a dictionary of the internal proteins nanoenvironments and their potential for transformation into agricultural assets. Applications of bioinformatics in agriculture. Genomics applied to climate change: biotechnology for digital agriculture. Innovation ecosystem in agriculture: Embrapa?s evolution and contributions. The law related to the digitization of agriculture. Innovating communication in the age of digital agriculture. Driving forces for Brazilian agriculture in the next decade: implications for digital agriculture. Challenges, trends and opportunities in digital agriculture in Brazil
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