DataMock: An Agile Approach for Building Data Models from User Interface Mockups

In modern software development, much time is devoted and much attention is paid to the activity of data modeling and the translation of data models into databases. This has motivated the proposal of different approaches and tools to support this activity, such as semiautomatic approaches that generate data models from requirements artifacts using text analysis and sets of heuristics, among other techniques. However, these approaches still suffer from important limitations, including the lack of support for requirements traceability, the poor support for detecting and solving conflicts in domain-specific requirements, and the considerable effort required for manually checking the generated models. This paper introduces DataMock, an Agile approach that enables the iterative building of data models from requirements specifications, while supporting traceability and allowing inconsistencies detection in data requirements and specifications. The paper also describes how the approach effectively allows improving traceability and reducing errors and effort to build data models in comparison with traditional, state-of-the-art, data modeling approaches

DataMock: An Agile Approach for Building Data Models from User Interface Mockups

In modern software development, much time is devoted and much attention is paid to the activity of data modeling and the translation of data models into databases. This has motivated the proposal of different approaches and tools to support this activity, such as semiautomatic approaches that generate data models from requirements artifacts using text analysis and sets of heuristics, among other techniques. However, these approaches still suffer from important limitations, including the lack of support for requirements traceability, the poor support for detecting and solving conflicts in domain-specific requirements, and the considerable effort required for manually checking the generated models. This paper introduces DataMock, an Agile approach that enables the iterative building of data models from requirements specifications, while supporting traceability and allowing inconsistencies detection in data requirements and specifications. The paper also describes how the approach effectively allows improving traceability and reducing errors and effort to build data models in comparison with traditional, state-of-the-art, data modeling approaches.Laboratorio de Investigación y Formación en Informática Avanzad

Designing the Sakai Open Academic Environment: A distributed cognition account of the design of a large scale software system

Social accounts of technological change make the flexibility and openness of interpretations the starting point of an argument against technological determinism. They suggest that technological change unfolds in the semantic domain, but they focus on the social processes around the interpretations of new technologies, and do not address the conceptual processes of change in interpretations. The dissertation presents an empirically grounded case study of the design process of an open-source online software platform based on the framework of distributed cognition to argue that the cognitive perspective is needed for understanding innovation in software, because it allows us to describe the reflexive and expansive contribution of conceptual processes to new software and the significance of professional epistemic practices in framing the direction of innovation. The framework of distributed cognition brings the social and cognitive perspectives together on account of its understanding of conceptual processes as distributed over time, among people, and between humans and artifacts. The dissertation argues that an evolving open-source software landscape became translated into the open-ended local design space of a new software project in a process of infrastructural implosion, and the design space prompted participants to outline and pursue epistemic strategies of sense-making and learning about the contexts of use. The result was a process of conceptual modeling, which resulted in a conceptually novel user interface. Prototyping professional practices of user-centered design lent directionality to this conceptual process in terms of a focus on individual activities with the user interface. Social approaches to software design under the broad umbrella of human-centered computing have been seeking to inform the design on the basis of empirical contributions about a social context. The analysis has shown that empirical engagement with the contexts of use followed from conceptual modeling, and concern about real world contexts was aligned with the user-centered direction that design was taking. I also point out a social-technical gap in the design process in connection with the repeated performance challenges that the platform was facing, and describe the possibility of a social-technical imagination.Ph.D

Modelom vođena softverska arhitektura za upravljanje metapodacima obrazovnih resursa

Purpose – The purpose of the research is to enable dynamic customization of metadata that describe educational resources in digital repositories.   Design/methodology/approach – Users need to describe educational resources in digital repositories according to the user-specific metadata set. Since users are mostly unskilled to customize the software application manually, our approach relies on the techniques of the model-driven software engineering, which should allow customization of the software application programmatically with no need to develop or order a new software application. In order to verify the proposed solution, we conducted an experiment which evaluated its characteristics.   Findings – A software platform for managing educational resources described by dynamically extendable metadata is proposed. The platform enables creating data models which are programmatically transformed to the web application for the management of educational resources. In this way a user can create their own model of metadata that is relevant in a particular domain. Research limitations / implications – The solution has been verified by users with technical knowledge. We should still explore the appropriateness of the platform for domain experts with little technical knowledge who would define new metadata in their domain. Practical implications – The solution can be used for digital repositories that store diverse educational resources. Each resource could be described using metadata that relates to the domain the resource belongs to. Originality/value – Digital repositories standardly describe educational resources using some general metadata, which are more focused on the physical characteristics of resources rather than their semantics. The proposed solution introduces custom domain-specific semantics into the resources’ description, which improves their retrieval.Cilj – Cilj disertacije je da se omogući dinamičko prilagođavanje metapodataka koji opisuju obrazovne resurse u digitalnim repozitorijumima. Metodologija - Postoji potreba da se u digitalnim repozitorijumima obrazovni resursi opišu putem skupa metapodataka koji je specifičan za određenog korisnika ili domen. Obzirom da korisnici ne mogu samostalno da ručno vrše izmenu softverske aplikacije, pristup predložen u ovoj disertaciji se zasniva na tehnikama modelom vođenog razvoja softvera, koji treba da omogući prilagođavanje softverske aplikacije programski, bez potrebe za razvojem ili naručivanjem nove aplikacije. Da bi se predloženo rešenje verifikovalo, sproveden je eksperiment koji evaluira njegove karakteristike. Rezultati - U disertaciji je predložena softverska platforma za upravljanje obrazovnim resursima opisanim dinamički proširivim skupom metapodataka. Platforma omogućuje kreiranje modela podataka koji se programski transformišu u veb aplikaciju za upravljanje obrazovnim resursima. Na ovaj način, korisnik može da kreira sopstveni model metapodataka koji je odgovarajući u određenom domenu. Ograničenja istraživanja/implikacije – Rešenje verifikovano od strane korisnicima sa određenim tehničkim znanjem. Potrebno je istražiti prikladnost platforme za domenske eksperte sa ograničenim tehničkim znanjem, koji treba da definišu nove skupove metapodataka u svom domenu. Praktične implikacije – Rešenje se može koristiti u digitalnim repozitorijuma koji skladište raznolike obrazovne resurse. Svaki resurs može biti opisan koristeći metapodatke iz domena kojem resurs pripada. Originalnost/vrednost - Digitalni repozitorijumi standardno opisuju obrazovne resurse koristeći neki generalni skup metapodataka, koji je više fokusiran na fizičke karakteristike resursa, umesto na njihovo značenje. Predloženo rešenje uvodi proizvoljnu domenski-zavisnu semantiku u opis resursa, čime se unapređuje njihovo dobavljanje

Interactive analogical retrieval: practice, theory and technology

Analogy is ubiquitous in human cognition. One of the important questions related to understanding the situated nature of analogy-making is how people retrieve source analogues via their interactions with external environments. This dissertation studies interactive analogical retrieval in the context of biologically inspired design (BID). BID involves creative use of analogies to biological systems to develop solutions for complex design problems (e.g., designing a device for acquiring water in desert environments based on the analogous fog-harvesting abilities of the Namibian Beetle). Finding the right biological analogues is one of the critical first steps in BID. Designers routinely search online in order to find their biological sources of inspiration. But this task of online bio-inspiration seeking represents an instance of interactive analogical retrieval that is extremely time consuming and challenging to accomplish. This dissertation focuses on understanding and supporting the task of online bio-inspiration seeking. Through a series of field studies, this dissertation uncovered the salient characteristics and challenges of online bio-inspiration seeking. An information-processing model of interactive analogical retrieval was developed in order to explain those challenges and to identify the underlying causes. A set of measures were put forth to ameliorate those challenges by targeting the identified causes. These measures were then implemented in an online information-seeking technology designed to specifically support the task of online bio-inspiration seeking. Finally, the validity of the proposed measures was investigated through a series of experimental studies and a deployment study. The trends are encouraging and suggest that the proposed measures has the potential to change the dynamics of online bio-inspiration seeking in favor of ameliorating the identified challenges of online bio-inspiration seeking.PhDCommittee Chair: Goel, Ashok; Committee Member: Kolodner, Janet; Committee Member: Maher, Mary Lou; Committee Member: Nersessian, Nancy; Committee Member: Yen, Jeannett

Bioinspired metaheuristic algorithms for global optimization

This paper presents concise comparison study of newly developed bioinspired algorithms for global optimization problems. Three different metaheuristic techniques, namely Accelerated Particle Swarm Optimization (APSO), Firefly Algorithm (FA), and Grey Wolf Optimizer (GWO) are investigated and implemented in Matlab environment. These methods are compared on four unimodal and multimodal nonlinear functions in order to find global optimum values. Computational results indicate that GWO outperforms other intelligent techniques, and that all aforementioned algorithms can be successfully used for optimization of continuous functions

Experimental Evaluation of Growing and Pruning Hyper Basis Function Neural Networks Trained with Extended Information Filter

In this paper we test Extended Information Filter (EIF) for sequential training of Hyper Basis Function Neural Networks with growing and pruning ability (HBF-GP). The HBF neuron allows different scaling of input dimensions to provide better generalization property when dealing with complex nonlinear problems in engineering practice. The main intuition behind HBF is in generalization of Gaussian type of neuron that applies Mahalanobis-like distance as a distance metrics between input training sample and prototype vector. We exploit concept of neuron’s significance and allow growing and pruning of HBF neurons during sequential learning process. From engineer’s perspective, EIF is attractive for training of neural networks because it allows a designer to have scarce initial knowledge of the system/problem. Extensive experimental study shows that HBF neural network trained with EIF achieves same prediction error and compactness of network topology when compared to EKF, but without the need to know initial state uncertainty, which is its main advantage over EKF

An Exploration of Student Reasoning about Undergraduate Computer Science Concepts: An Active Learning Technique to Address Misconceptions

Computer science (CS) is a popular but often challenging major for undergraduates. As the importance of computing in the US and world economies continues to grow, the demand for successful CS majors grows accordingly. However, retention rates are low, particularly for under-represented groups such as women and racial minorities. Computing education researchers have begun to investigate causes and explore interventions to improve the success of CS students, from K-12 through higher education. In the undergraduate CS context, for example; student difficulties with pointers, functions, loops, and control flow have been observed. We and others have utilized student responses to multiple choice questions aimed at determining misconceptions, engaged in retroactive examination of code samples and design artifacts, and conducted interviews in an attempt to understand the nature of these problems. Interventions to address these problems often apply evidenced-based active learning techniques in CS classrooms as a way to engage students and improve learning.In this work, I employ a human-centered approach, one in which the focus of data collection is on the student thought processes as evidenced in their speech and writing. I seek to determine what students are thinking not only through what can be surmised in retrospect from the artifacts they create, but also to gain insight into their thoughts as they engage in the design, implementation,and analysis of those artifacts and as they reflect on those processes and artifacts shortly after. For my dissertation work, I have conducted four studies: 1. a conceptual assessment survey asking students to “Please explain your reasoning” after each answer to code tracing/execution questions followed by task-based interviews with a smaller, different group of students 2. a “coding in the wild” think aloud study that recorded the screen and audio of students as they implemented a simple program and explained their thought process 3. interview analyses of student design diagrams/documentation in a software engineering course, tasking students to explain their designs and comparing what they believed they had designed with what is actually shown from their submitted documentation. These first three studies were formative, leading to some key insights including the benefits students can gain from feedback, students’ tendencies to avoid complexity when programming or encountering concepts they do not fully grasp, the nature of student struggles with the planning stages of problem solving, and insight into the fragile understanding of some key CS concepts that students form. I leverage the benefits of feedback with guided prompts using the misconceptions uncovered in my formative studies to conduct a final, evaluative study. This study seeks to evaluate the benefits that can be gained from a guided feedback intervention for learning introductory programming concepts and compare those benefits and the effort and resource costs associated with each variation, comparing the costs and benefits associated with two forms of feedback. The first is an active learning technique I developed and deem misconception-based feedback (MBF), which has peers working in pairs use prompts based on misconceptions to guide their discussion of a recently completed coding assignment. The second is a human autograder (HAG) group acting as a control. HAG simulates typical autograders, supplying test cases and correct solutions, but utilizes a human stand-in for a computer. In both conditions, one student uses provided prompts to guide the discussion. The other student responds/interacts with their code based on the prompts. I captured screen and audio recordings of these discussions. Participants completed conceptual pre-tests and post-tests that asked them to explain their reasoning. I hypothesized that the MBF intervention will offer avaluable way to increase learning, address misconceptions, and get students more engaged that will be feasible in CS courses of any size and have benefits over the HAG intervention. Results show that for questions involving parameter passing with regards to pass by reference versus pass by value semantics, particularly with pointers, there were significant improvements in learning outcomes for the MBF group but not the HAG group

31th International Conference on Information Modelling and Knowledge Bases

Information modelling is becoming more and more important topic for researchers, designers, and users of information systems.The amount and complexity of information itself, the number of abstractionlevels of information, and the size of databases and knowledge bases arecontinuously growing. Conceptual modelling is one of the sub-areas ofinformation modelling. The aim of this conference is to bring together experts from different areas of computer science and other disciplines, who have a common interest in understanding and solving problems on information modelling and knowledge bases, as well as applying the results of research to practice. We also aim to recognize and study new areas on modelling and knowledge bases to which more attention should be paid. Therefore philosophy and logic, cognitive science, knowledge management, linguistics and management science are relevant areas, too. In the conference, there will be three categories of presentations, i.e. full papers, short papers and position papers