First name / Family name Efi Papatheocharous

Context: Traditionally, embedded systems (ES) are tightly linked to physical products, and closed both for communication to the surrounding world and to additions or modifications by third parties. New technical solutions are however emerging that allow addition of plug-in software, as well as external communication for both software installation and data exchange. These mechanisms in combination will allow for the construction of Federated Embedded Systems (FES). Expected benefits of this are the possibility of third party actors developing add-on functionality; a shorter time to market for new functions; and the ability to upgrade existing products in the field. This will however require not only new technical solutions, but also a transformation of the software ecosystems for ES. Objective: This paper aims at providing an initial characterization of the mechanisms that need to be present to make a FES ecosystem successful. This includes identification of the actors, the possible business models, the effects on product development processes, methods and tools, as well as on the product architecture. Method: The research was carried out as an explorative case study based on interviews with 15 senior staff members at 9 companies related to ES that represent different roles in a future ecosystem for FES. The interview data was analyzed and the findings were mapped according to the Business Model Canvas. ABCDE Scientific Report 4/8 Results: The findings from the study describe the main characteristics of a FES ecosystem, and identify the challenges for future research and practice. Conclusions: The case study indicates that new actors exist in the FES ecosystem compared to a traditional supply chain, and that their roles and relations are affected. The business models include new revenue streams and services, but also create the need for trade-offs between, e.g., openness and dependability in the architecture, as well as new ways of working. Reference Status Submitted, conditionally accepted (major revision submitted) Title A Multivariate Statistical Framework for the Analysis of Software Effort Phase Distribution Author(s) Chatzipetrou Panagiota, Papatheocharous Efi, Angelis Lefteris, Andreou S. Andreas Abstract One of the most challenging problems in software project management for mitigating the project risks is to effectively decide how to distribute resources among the various project activities. Project success depends on how effectively work effort is allocated among the project phases. Properly distributed effort for a project will ultimately lead to more productive teams satisfying project constraints of quality, budget and schedule, as well as other product requirements. This paper firstly investigates the various forms of effort distribution suggested in the relevant literature, and also compares the effort distributions reported in around 1,500 software projects of the ISBSG R11 repository. Secondly, it obtains useful visual information regarding the correlation of the composition of effort attributed in phases starting from their representation as vectors of proportions and continuing with their subsequent analysis using a number of multivariate statistical methodologies based on Compositional Data Analysis (CoDA). Empirical effort distribution is thus compared to theoretical propositions found in literature and examined with respect to primary project attributes, such as organisation type, language type and size. Among the main findings is the identification of significant workload on specific phases for different types of projects. The proposed framework aims to provide a beneficial set of statistical methods for analysing software project data, towards better allocation of the available resources and formation of a basis for accurate cost estimation.One of the most challenging problems in software project management for mitigating the project risks is to effectively decide how to distribute resources among the various project activities. Project success depends on how effectively work effort is allocated among the project phases. Properly distributed effort for a project will ultimately lead to more productive teams satisfying project constraints of quality, budget and schedule, as well as other product requirements. This paper firstly investigates the various forms of effort distribution suggested in the relevant literature, and also compares the effort distributions reported in around 1,500 software projects of the ISBSG R11 repository. Secondly, it obtains useful visual information regarding the correlation of the composition of effort attributed in phases starting from their representation as vectors of proportions and continuing with their subsequent analysis using a number of multivariate statistical methodologies based on Compositional Data Analysis (CoDA). Empirical effort distribution is thus compared to theoretical propositions found in literature and examined with respect to primary project attributes, such as organisation type, language type and size. Among the main findings is the identification of significant workload on specific phases for different types of projects. The proposed framework aims to provide a beneficial set of statistical methods for analysing software project data, towards better allocation of the available resources and formation of a basis for accurate cost estimation. Reference Status Submitted, Under review Title Modeling Users on the World Wide Web based on Cognitive Factors, Navigation Behavior and Clustering Techniques Author(s) Belk Marios, Papatheocharous Efi, Germanakos Panagiotis, Samaras George Abstract This paper focuses on modeling users’ cognitive styles based on a set of Web usage mining techniques on navigation patterns and clickstream data. Main aim is to investigate whether specific clustering techniques can group users of particular cognitive style using measures obtained from psychometric tests and content navigation behavior. Three navigation metrics are proposed and used to find identifiable groups of users that have similar navigation patterns in relation to their cognitive style. The proposed work has been evaluated with two user studies which entail a psychometricbased survey for extracting the users’ cognitive styles, combined with a real usage scenario of users navigating in a controlled Web 2.0 environment. A total of 106 participants of age between 17 and 25 participated in the study providing interesting insights with respect to cognitive styles and navigation behavior of users. Studies like the reported one can be useful for assisting adaptive Web 2.0 environments to organize and present information andThis paper focuses on modeling users’ cognitive styles based on a set of Web usage mining techniques on navigation patterns and clickstream data. Main aim is to investigate whether specific clustering techniques can group users of particular cognitive style using measures obtained from psychometric tests and content navigation behavior. Three navigation metrics are proposed and used to find identifiable groups of users that have similar navigation patterns in relation to their cognitive style. The proposed work has been evaluated with two user studies which entail a psychometricbased survey for extracting the users’ cognitive styles, combined with a real usage scenario of users navigating in a controlled Web 2.0 environment. A total of 106 participants of age between 17 and 25 participated in the study providing interesting insights with respect to cognitive styles and navigation behavior of users. Studies like the reported one can be useful for assisting adaptive Web 2.0 environments to organize and present information and ABCDE Scientific Report 5/8 functionalities in an adaptive format to diverse user groups. Reference Belk M., Papatheocharous E., Germanakos P., and Samaras G. (2013). “Modeling Users on the World Wide Web based on Cognitive Factors, Navigation Behavior and Clustering Techniques”, Journal of Systems and Software (JSS), Special Issue on Web 2.0 Engineering: New Practices and Emerging Challenges, Elsevier, Available Online May 7, doi: 10.1016/j.jss.2013.04.029.