| 1. |
- Abdeen, Waleed
(author)
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Reducing the Distance Between Requirements Engineering and Verification
- 2022
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Licentiate thesis (other academic/artistic)abstract
- Background Requirements engineering and verification (REV) processes play es-sential roles in software product development. There are physical and non-physicaldistances between entities (actors, artifacts, and activities) in these processes. Cur-rent practices that reduce the distances, such as automated testing and alignmentof document structure and tracing only partially close the above mentioned gap.Objective The aim of this thesis is to investigate solutions w.r.t their abilityto reduce the distances between requirements engineering and verification. Twotechniques that are explored in this thesis are automated testing (model-basedtesting, MBT) and alignment of document structure and tracing (traceability).Method The research methods used in this thesis are systematic mapping, soft-ware requirements mining, case study, literature survey, validation study, and de-sign science.Results MBT and traceability are effective in reducing the distance between re-quirements and verification. However, both activities have some shortcoming thatneeds to be addressed when used for that purpose. Current MBT techniques inthe context of software performance do not attain all the goals of MBT: 1) require-ments validation, 2) checking the testability of requirements, and 3) the generationof an efficient test suite. These goals are essential to reduce the distance. We de-veloped and assessed performance requirements verification and test environmentgeneration approach to tackle these shortcomings. Also, traceability between re-quirements and verification suffers from the low granularity of trace links and doesnot support the verification of all requirements. We propose the use of taxonomictrace links to trace and align the structure of requirements specifications and ver-ification artifacts. The results from the validation study show that the solution isfeasible in practice. However, this comes with challenges that need to be addressed.Conclusion MBT and improved traceability reduce multiple distances betweenactors, artifacts, and activities in the requirements engineering and verificationprocess. MBT is most effective in reducing the distances when the model used isbuilt from the requirements. Traceability is essential in easing access to relevantinformation when needed and should not be seen as an overhead. When creatingtrace links, we need to consider the difference in the abstraction, structure, andtime between the linked artifacts
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| 2. |
- Abghari, Shahrooz
(author)
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Data Modeling for Outlier Detection
- 2018
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Licentiate thesis (other academic/artistic)abstract
- This thesis explores the data modeling for outlier detection techniques in three different application domains: maritime surveillance, district heating, and online media and sequence datasets. The proposed models are evaluated and validated under different experimental scenarios, taking into account specific characteristics and setups of the different domains.Outlier detection has been studied and applied in many domains. Outliers arise due to different reasons such as fraudulent activities, structural defects, health problems, and mechanical issues. The detection of outliers is a challenging task that can reveal system faults, fraud, and save people's lives. Outlier detection techniques are often domain-specific. The main challenge in outlier detection relates to modeling the normal behavior in order to identify abnormalities. The choice of model is important, i.e., an incorrect choice of data model can lead to poor results. This requires a good understanding and interpretation of the data, the constraints, and the requirements of the problem domain. Outlier detection is largely an unsupervised problem due to unavailability of labeled data and the fact that labeled data is expensive.We have studied and applied a combination of both machine learning and data mining techniques to build data-driven and domain-oriented outlier detection models. We have shown the importance of data preprocessing as well as feature selection in building suitable methods for data modeling. We have taken advantage of both supervised and unsupervised techniques to create hybrid methods. For example, we have proposed a rule-based outlier detection system based on open data for the maritime surveillance domain. Furthermore, we have combined cluster analysis and regression to identify manual changes in the heating systems at the building level. Sequential pattern mining for identifying contextual and collective outliers in online media data have also been exploited. In addition, we have proposed a minimum spanning tree clustering technique for detection of groups of outliers in online media and sequence data. The proposed models have been shown to be capable of explaining the underlying properties of the detected outliers. This can facilitate domain experts in narrowing down the scope of analysis and understanding the reasons of such anomalous behaviors. We have also investigated the reproducibility of the proposed models in similar application domains.
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| 3. |
- Acevedo Peña, Carlos Gonzalo
(author)
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Developing Inclusive Innovation Processes and Co-Evolutionary Approaches in Bolivia
- 2015
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Licentiate thesis (other academic/artistic)abstract
- The concept of National Innovation Systems (NIS) has been widely adopted in developing countries, particularly in Latin American countries, for the last two decades. The concept is used mainly as an ex-ante framework to organize and increase the dynamics of those institutions linked to science, technology and innovation, for catching-up processes of development. In the particular case of Bolivia, and after several decades of social and economic crisis, the promise of a national innovation system reconciles a framework for collaboration between the university, the government and the socio-productive sectors. Dynamics of collaboration generated within NIS can be a useful tool for the pursuit of inclusive development ambitions. This thesis is focused on inclusive innovation processes and the generation of co-evolutionary processes between university, government and socio-productive sectors. This is the result of 8 years of participatory action research influenced by Mode 2 knowledge-production and Technoscientific approaches. The study explores the policy paths the Bolivian government has followed in the last three decades in order to organize science, technology and innovation. It reveals that Bolivia has an emerging national innovation system, where its demand-pulled innovation model presents an inclusive approach. Innovation policy efforts in Bolivia are led by the Vice-Ministry of Science and Technology (VCyT). Moreover, NIS involves relational and collaborative approaches between institutions, which imply structural and organizational challenges, particularly for public universities, as they concentrate most of the research capabilities in the country. These universities are challenged to participate in NIS within contexts of weak demanding sectors. This research focuses on the early empirical approaches and transformations at Universidad Mayor de San Simón (UMSS) in Cochabamba. The aim to strengthen internal innovation capabilities of the university and enhance the relevance of research activities in society by supporting socio-economic development in the framework of innovation systems is led by the Technology Transfer Unit (UTT) at UMSS. UTT has become a recognized innovation facilitator unit, inside and outside the university, by proposing pro-active initiatives to support emerging innovation systems. Because of its complexity, the study focuses particularly on cluster development promoted by UTT. Open clusters are based on linking mechanisms between the university research capabilities, the socio-productive actors and government. Cluster development has shown to be a practical mechanism for the university to meet the demanding sector (government and socio-productive actors) and to develop trust-based inclusive innovation processes. The experiences from cluster activities have inspired the development of new research policies at UMSS, with a strong orientation to foster research activities towards an increased focus on socio-economic development. The experiences gained at UMSS are discussed and presented as a “developmental university” approach. Inclusive innovation processes with co-evolutionary approaches seem to constitute an alternative path supporting achievement of inclusive development ambitions in Bolivia.
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| 4. |
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| 5. |
- Aeddula, Omsri, 1993-
(author)
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Data-Driven Decision Support Systems for Product Development - A Data Exploration Study Using Machine Learning
- 2021
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Licentiate thesis (other academic/artistic)abstract
- Modern product development is a complex chain of events and decisions. The ongoing digital transformation of society, increasing demands in innovative solutions puts pressure on organizations to maintain, or increase competitiveness. As a consequence, a major challenge in the product development is the search for information, analysis, and the build of knowledge. This is even more challenging when the design element comprises complex structural hierarchy and limited data generation capabilities. This challenge is even more pronounced in the conceptual stage of product development where information is scarce, vague, and potentially conflicting. The ability to conduct exploration of high-level useful information using a machine learning approach in the conceptual design stage would hence enhance be of importance to support the design decision-makers, where the decisions made at this stage impact the success of overall product development process.The thesis aims to investigate the conceptual stage of product development, proposing methods and tools in order to support the decision-making process by the building of data-driven decision support systems. The study highlights how the data can be utilized and visualized to extract useful information in design exploration studies at the conceptual stage of product development. The ability to build data-driven decision support systems in the early phases facilitates more informed decisions.The thesis presents initial descriptive study findings from the empirical studies, showing the capabilities of the machine learning approaches in extracting useful information, and building data-driven decision support systems. The thesis initially describes how the linear regression model and artificial neural networks extract useful information in design exploration, providing support for the decision-makers to understand the consequences of the design choices through cause-and-effect relationships on a detailed level. Furthermore, the presented approach also provides input to a novel visualization construct intended to enhance comprehensibility within cross-functional design teams. The thesis further studies how the data can be augmented and analyzed to extract the necessary information from an existing design element to support the decision-making process in an oral healthcare context.
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| 6. |
- Afzal, Wasif
(author)
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Search-based approaches to software fault prediction and software testing
- 2009
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Licentiate thesis (other academic/artistic)abstract
- Software verification and validation activities are essential for software quality but also constitute a large part of software development costs. Therefore efficient and cost-effective software verification and validation activities are both a priority and a necessity considering the pressure to decrease time-to-market and intense competition faced by many, if not all, companies today. It is then perhaps not unexpected that decisions related to software quality, when to stop testing, testing schedule and testing resource allocation needs to be as accurate as possible. This thesis investigates the application of search-based techniques within two activities of software verification and validation: Software fault prediction and software testing for non-functional system properties. Software fault prediction modeling can provide support for making important decisions as outlined above. In this thesis we empirically evaluate symbolic regression using genetic programming (a search-based technique) as a potential method for software fault predictions. Using data sets from both industrial and open-source software, the strengths and weaknesses of applying symbolic regression in genetic programming are evaluated against competitive techniques. In addition to software fault prediction this thesis also consolidates available research into predictive modeling of other attributes by applying symbolic regression in genetic programming, thus presenting a broader perspective. As an extension to the application of search-based techniques within software verification and validation this thesis further investigates the extent of application of search-based techniques for testing non-functional system properties. Based on the research findings in this thesis it can be concluded that applying symbolic regression in genetic programming may be a viable technique for software fault prediction. We additionally seek literature evidence where other search-based techniques are applied for testing of non-functional system properties, hence contributing towards the growing application of search-based techniques in diverse activities within software verification and validation.
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| 7. |
- Ahmadi Mehri, Vida, 1980-
(author)
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Towards Secure Collaborative AI Service Chains
- 2019
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Licentiate thesis (other academic/artistic)abstract
- At present, Artificial Intelligence (AI) systems have been adopted in many different domains such as healthcare, robotics, automotive, telecommunication systems, security, and finance for integrating intelligence in their services and applications. The intelligent personal assistant such as Siri and Alexa are examples of AI systems making an impact on our daily lives. Since many AI systems are data-driven systems, they require large volumes of data for training and validation, advanced algorithms, computing power and storage in their development process. Collaboration in the AI development process (AI engineering process) will reduce cost and time for the AI applications in the market. However, collaboration introduces the concern of privacy and piracy of intellectual properties, which can be caused by the actors who collaborate in the engineering process. This work investigates the non-functional requirements, such as privacy and security, for enabling collaboration in AI service chains. It proposes an architectural design approach for collaborative AI engineering and explores the concept of the pipeline (service chain) for chaining AI functions. In order to enable controlled collaboration between AI artefacts in a pipeline, this work makes use of virtualisation technology to define and implement Virtual Premises (VPs), which act as protection wrappers for AI pipelines. A VP is a virtual policy enforcement point for a pipeline and requires access permission and authenticity for each element in a pipeline before the pipeline can be used. Furthermore, the proposed architecture is evaluated in use-case approach that enables quick detection of design flaw during the initial stage of implementation. To evaluate the security level and compliance with security requirements, threat modeling was used to identify potential threats and vulnerabilities of the system and analyses their possible effects. The output of threat modeling was used to define countermeasure to threats related to unauthorised access and execution of AI artefacts.
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| 8. |
- Andreasson, Eskil
(author)
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Realistic Package Opening Simulations : An Experimental Mechanics and Physics Based Approach
- 2015
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Licentiate thesis (other academic/artistic)abstract
- A finite element modeling strategy targeting package opening simulations is the final goal with this work. The developed simulation model will be used to proactively predict the opening compatibility early in the development process of a new opening device and/or a new packaging material. To be able to create such a model, the focus is to develop a combined and integrated physical/virtual test procedure for mechanical characterization and calibration of thin packaging materials. Furthermore, the governing mechanical properties of the materials involved in the opening performance needs to be identified and quantified with experiments. Different experimental techniques complemented with video recording equipment were refined and utilized during the course of work. An automatic or semi-automatic material model parameter identification process involving video capturing of the deformation process and inverse modeling is proposed for the different packaging material layers. Both an accurate continuum model and a damage material model, used in the simulation model, were translated and extracted from the experimental test results. The results presented show that it is possible to select constitutive material models in conjunction with continuum material damage models, adequately predicting the mechanical behavior of intended failure in thin laminated packaging materials. A thorough material mechanics understanding of individual material layers evolution of microstructure and the micro mechanisms involved in the deformation process is essential for appropriate selection of numerical material models. Finally, with a slight modification of already available techniques and functionalities in the commercial finite element software AbaqusTM it was possible to build the suitable simulation model. To build a realistic simulation model an accurate description of the geometrical features is important. Therefore, advancements within the experimental visualization techniques utilizing a combination of video recording, photoelasticity and Scanning Electron Microscopy (SEM) of the micro structure have enabled extraction of geometries and additional information from ordinary standard experimental tests. Finally, a comparison of the experimental opening and the virtual opening, showed a good correlation with the developed finite element modeling technique. The advantage with the developed modeling approach is that it is possible to modify the material composition of the laminate. Individual material layers can be altered and the mechanical properties, thickness or geometrical shape can be changed. Furthermore, the model is flexible and a new opening device i.e. geometry and load case can easily be adopted in the simulation model. Therefore, this type of simulation model is a useful tool and can be used for decision support early in the concept selection of development projects.
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| 9. |
- Ankre, Rosemarie
(author)
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Understanding the visitor : A prerequisite for coastal zone planning
- 2007
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Licentiate thesis (other academic/artistic)abstract
- Planning for tourism and outdoor recreation in coastal areas could be improved with knowledge of visitors´ attitudes, experiences, activities and geographical dispersion. The purpose of this thesis is to examine the knowledge of visitors in planning for tourism and outdoor recreation. The Luleå archipelago in Northern Sweden was used as a case study.
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| 10. |
- Ayers, James, 1983-
(author)
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Educational contexts and designs for cultivating leaders capable of addressing the wicked issues of sustainability transitions.
- 2020
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Licentiate thesis (other academic/artistic)abstract
- The ongoing sustainability crisis offer numerous, multifaced societal challenges as a result of the ongoing degradation of socio-ecological systems by human activity causing massive ecological damage and human suffering. Overcoming these difficulties begs for the rapid transition of society towards sustainability. This desire for urgent action has been hindered by the lack of coordinated global leadership focused on addressing these challenges and implementing a transition towards a sustainable future. The sustainability crisis and its manifestations, which include for example climate change, air and water pollution, deforestation and social segregation, are interconnected and volatile issues whose parts influence and impact each other causing the crisis to worsen. The earth system is pushed towards tipping points from beyond which it may become impossible to maintain the human civilization. The failure of leadership to address the wicked nature of these crises means humanity has been left ill-equipped to deal with the complex problems of sustainability. This thesis considers the role of Education for Sustainable Development (ESD) in overcoming these issues and operating as a leverage point towards sustainability. It focuses on investigating how the development of sustainability leadership education in Higher Education can contribute to addressing the sustainability crisis. It looks at the role that educators can play in designing learning environments that ensure leaders and leadership capable of addressing wicked problems posed by global unsustainability. The aim of this research is to investigate what educators should consider when designing learning environments that promote the qualities needed for leading in complexity towards sustainability. It does this by examining a number of ESD programs as case studies to investigate the efficacy of those programs at creating sustainability outcomes within their students. It also undertakes a literature review to describe and articulate the unique challenges faced by sustainability leaders from a personal and professional perspective. The study is situated closely to the ongoing ESD discussion regarding competencies-based learning for sustainability and the research aims to provide some contribution to that dialogue. It does this through the investigation of competencies acquisition and the discussion of emerging areas of leadership that may hold beneficial outcomes for the development and practice of sustainability leaders. The results of the thesis suggest a number of outcomes for consideration by educators and include a number of main findings. Firstly, educational programs can be capable of achieving the acquisition of ‘sustainability’ competencies within their students, but if these competencies are not taught within a larger sustainability contextualization, then students can fail to see the purpose of the competencies ‘for’ sustainability. Secondly, reflective practices, developed as the result of reflective pedagogies, can provide beneficial qualities in students as future sustainability leaders and require distinct pedagogical structures in order to guide reflective practices towards sustainability outcomes. Finally, a number of unique personal and professional challenges to sustainability leadership exist and need to be overcome if the domain of sustainability is to ensure the ongoing resilience and wellbeing of individuals and groups acting as sustainability leaders. This research suggests a novel contribution to a number of areas within ESD research, including creating knowledge within the competencies discussion regarding emerging areas of study that may influence the future of defined sustainability competencies. It also highlights the need for educators to consider the role of wellbeing and resilience in current and future sustainability leaders.
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