Probabilistic Graphical Modelling for Software Product Lines: A Frameweork for Modeling and Reasoning under Uncertainty

This work provides a holistic investigation into the realm of feature modeling within software product lines. The work presented identifies limitations and challenges within the current feature modeling approaches. Those limitations include, but not limited to, the dearth of satisfactory cognitive presentation, inconveniency in scalable systems, inflexibility in adapting changes, nonexistence of predictability of models behavior, as well as the lack of probabilistic quantification of model’s implications and decision support for reasoning under uncertainty. The work in this thesis addresses these challenges by proposing a series of solutions. The first solution is the construction of a Bayesian Belief Feature Model, which is a novel modeling approach capable of quantifying the uncertainty measures in model parameters by a means of incorporating probabilistic modeling with a conventional modeling approach. The Bayesian Belief feature model presents a new enhanced feature modeling approach in terms of truth quantification and visual expressiveness. The second solution takes into consideration the unclear support for the reasoning under the uncertainty process, and the challenging constraint satisfaction problem in software product lines. This has been done through the development of a mathematical reasoner, which was designed to satisfy the model constraints by considering probability weight for all involved parameters and quantify the actual implications of the problem constraints. The developed Uncertain Constraint Satisfaction Problem approach has been tested and validated through a set of designated experiments. Profoundly stating, the main contributions of this thesis include the following: • Develop a framework for probabilistic graphical modeling to build the purported Bayesian belief feature model. • Extend the model to enhance visual expressiveness throughout the integration of colour degree variation; in which the colour varies with respect to the predefined probabilistic weights. • Enhance the constraints satisfaction problem by the uncertainty measuring of the parameters truth assumption. • Validate the developed approach against different experimental settings to determine its functionality and performance.

A Scalable Design Framework for Variability Management in Large-Scale Software Product Lines

Variability management is one of the major challenges in software product line adoption, since it needs to be efficiently managed at various levels of the software product line development process (e.g., requirement analysis, design, implementation, etc.). One of the main challenges within variability management is the handling and effective visualization of large-scale (industry-size) models, which in many projects, can reach the order of thousands, along with the dependency relationships that exist among them. These have raised many concerns regarding the scalability of current variability management tools and techniques and their lack of industrial adoption. To address the scalability issues, this work employed a combination of quantitative and qualitative research methods to identify the reasons behind the limited scalability of existing variability management tools and techniques. In addition to producing a comprehensive catalogue of existing tools, the outcome form this stage helped understand the major limitations of existing tools. Based on the findings, a novel approach was created for managing variability that employed two main principles for supporting scalability. First, the separation-of-concerns principle was employed by creating multiple views of variability models to alleviate information overload. Second, hyperbolic trees were used to visualise models (compared to Euclidian space trees traditionally used). The result was an approach that can represent models encompassing hundreds of variability points and complex relationships. These concepts were demonstrated by implementing them in an existing variability management tool and using it to model a real-life product line with over a thousand variability points. Finally, in order to assess the work, an evaluation framework was designed based on various established usability assessment best practices and standards. The framework was then used with several case studies to benchmark the performance of this work against other existing tools.

Live Work: The Impact of Direct Encounters in Statutory Child and Family Social Wor

The aim of this research project was to examine the impact of direct work on practitioners in the field of statutory child protection. The author’s premise was that this work was anything but straightforward and that surprisingly, given the intense scrutiny on Children’s Services following a child death, there was little research into the day-to-day practice of front line staff. The aim was to explore whether psychoanalytic theory could be useful in understanding and making sense of the social work task. Data was collected through observation and semi-structured interviews in one Local Authority Child in Need team over a period of six months. The findings indicated that practitioners experienced direct work with some individuals and families as profoundly disturbing and that this affected them physiologically as well as psychologically. These effects persisted over time and appeared very difficult for the workers to process or articulate. This could be expressed through embodied or non-verbal communication in the interview. Practitioners appeared to be ‘inhabited’ by particular clients, suggesting phenomena such as projective identification were in operation. The intensity and persistence of the impact on the practitioners appears to be directly related to the quality, nature and intensity of the psychic defences functioning for the particular client. Significantly, the research indicated that when practitioners were dealing with the negative and disturbing projections from the (adult) clients it seemed from the data that the focus on the child would slip so that the child appeared to recede from view. Symptoms experienced by the practitioners were akin to trauma and research and theory on primary and secondary trauma were considered. Other issues raised included shame, which affects the clients, practitioners and the organisation and the meaning and implications of this are explored. Links between neuroscience and projective identification are addressed as well as the role of the organisation, particularly as a container for these toxic and disturbing encounters.