Sergiu M. Dascalu

Unit-level test adequacy criteria for visual dataflow languages and a testing methodology

Visual dataflow languages (VDFLs), which include commercial and research systems, have had a substantial impact on end-user programming. Like any other programming languages, whether visual or textual, VDFLs often contain faults. A desire to provide programmers of these languages with some of the benefits of traditional testing methodologies has been the driving force behind our effort in this work. In this article we introduce, in the context of prograph, a testing methodology for VDFLs based on structural test adequacy criteria and coverage. This article also reports on the results of two empirical studies. The first study was conducted to obtain meaningful information about, in particular, the effectiveness of our all-Dus criteria in detecting a reasonable percentage of faults in VDFLs. The second study was conducted to evaluate, under the same criterion, the effectiveness of our methodology in assisting users to visually localize faults by reducing their search space. Both studies were conducted using a testing system that we have implemented in Prographs IDE.

Interactive Genetic Algorithms for User Interface Design

We attack the problem of user fatigue in using an interactive genetic algorithm to evolve user interfaces in the XUL interface definition language. The interactive genetic algorithm combines computable user interface design metrics with subjective user input to guide evolution. Individuals in our population represent interface specifications and we compute an individuals fitness from a weighted combination of user input and user interface design guidelines. Results from our preliminary study involving three users indicate that users are able to effectively bias evolution towards user interface designs that reflect both user preferences and computed guideline metrics. Furthermore, we can reduce fatigue, defined by the number of choices needing to be made by the human designer, by doing two things. First, asking the user to pick just two (the best and worst) user interfaces from among a subset of nine shown. Second, asking the user to make the choice once every t generations, instead of every single generation. Our goal is to provide interface designers with an interactive tool that can be used to explore innovation and creativity in the design space of user interfaces.

A product-line architecture for web service-based visual composition of web applications

A web service-based web application (WSbWA) is a collection of web services or reusable proven software parts that can be discovered and invoked using standard Internet protocols. The use of these web services in the development process of WSbWAs can help overcome many problems of software use, deployment and evolution. Although the cost-effective software engineering of WSbWAs is potentially a very rewarding area, not much work has been done to accomplish short time to market conditions by viewing and dealing with WSbWAs as software products that can be derived from a common infrastructure and assets with a captured specific abstraction in the domain. Both Product Line Engineering (PLE) and Agile Methods (AMs), albeit with different philosophies, are software engineering approaches that can significantly shorten the time to market and increase the quality of products. Using the PLE approach we built, at the domain engineering level, a WSbWA-specific lightweight product-line architecture and combined it, at the application engineering level, with an Agile Method that uses a domain-specific visual language with direct manipulation and extraction capabilities of web services to perform customization and calibration of a product or WSBWA for a specific customer. To assess the effectiveness of our approach we designed and implemented a tool that we used to investigate the return on investment of the activities related to PLE and AMs. Details of our proposed approach, the related tool developed, and the experimental study performed are presented in this article together with a discussion of planned directions of future work.

Interactive evolution of XUL user interfaces

We attack the problem of user fatigue by using an interactive genetic algorithm to evolve user interfaces in the XUL interface definition language. The interactive genetic algorithm combines a set of computable user interface design metrics with subjective user input to guide the evolution of interfaces. Our goal is to provide user interface designers with a tool that can be used to explore innovation and creativity in the design space of user interfaces and make it easier for end-users to further customize their user interface without programming knowledge. User interface specifications are encoded as individuals in an interactive genetic algorithms population and their fitness is computed from a weighted combination of user interface design guidelines and user input. This paper shows that we can reduce human fatigue in interactive genetic algorithms (the number of choices needing to be made by the designer), by 1) only asking the user to pick two user interfaces from among ten shown on the display and 2) by asking the user to make the choice once every t generations.

A Novel CPU/GPU Simulation Environment for Large-Scale Biologically-Realistic Neural Modeling

Computational Neuroscience is an emerging field that provides unique opportunities to study complex brain structures through realistic neural simulations. However, as biological details are added to models, the execution time for the simulation becomes longer. Graphics Processing Units (GPUs) are now being utilized to accelerate simulations due to their ability to perform computations in parallel. As such, they have shown significant improvement in execution time compared to Central Processing Units (CPUs). Most neural simulators utilize either multiple CPUs or a single GPU for better performance, but still show limitations in execution time when biological details are not sacrificed. Therefore, we present a novel CPU/GPU simulation environment for large-scale biological networks, the NeoCortical Simulator version 6 (NCS6). NCS6 is a free, open-source, parallelizable, and scalable simulator, designed to run on clusters of multiple machines, potentially with high performance computing devices in each of them. It has built-in leaky-integrate-and-fire (LIF) and Izhikevich (IZH) neuron models, but users also have the capability to design their own plug-in interface for different neuron types as desired. NCS6 is currently able to simulate one million cells and 100 million synapses in quasi real time by distributing data across eight machines with each having two video cards.

User-context for adaptive user interfaces

We present results from an empirical user-study with ten users which investigates if information from a users environment helps a user interface to personalize itself to individual users to better meet usability goals and improve user-experience. In our research we use a microphone and a web-camera to collect this information (user-context) from the vicinity of a subjects desktop computer. Sycophant, our context-aware calendaring application and research test-bed uses machine learning techniques to successfully predict a user-preferred alarm type. Discounting user identity and motion information significantly degrades Sycophants performance on the alarm prediction task. Our user study emphasizes the need for user-context for personalizable user interfaces which can better meet effectiveness and utility usability goals. Results from our study further demonstrate that contextual information helps adaptive interfaces to improve user-experience.

ACAT: A Web-Based Software Tool to Facilitate Course Assessment for ABET Accreditation

There are several institutions that accredit educational programs and require documentation to ensure that an educational program regularly meets certain criteria. This paper focuses on ABET program. They require that programs show student achievement and certain course outcomes. Documentation of this requirement is particularly burdensome. There is no standard method of generating these reports, so each institution handles it differently. This might involve manual collection of the data which is time very consuming. A software tool that facilitates this collection of the data and automatically generates the required reports would save institutions time and money. This paper presents such a tool, named ACAT (ABET Course Assessment Tool), it is a web-based application designed to assist in the collecting of data and generation of standardized assessment reports. This paper focuses on design and usability aspects of the proposed ACAT tool and provides implementation and operation details.

Microservice-based architecture for the NRDC

The NSF EPSCOR funded Solar Nexus Project is a collaborative effort between scientists, engineers, educators, and technicians to increase the amount of renewable solar energy in Nevada while eliminating its adverse effects on the surrounding environment and wildlife, and minimizing water consumption. The project seeks to research multiple areas, including water usage at power plants, the effect of power plant construction on the surrounding ecology, alternative wastewater methods to maintain solar panels, and interdisciplinary solutions to improve solar energy in Nevada. In order to organize and analyze this data to produce effective change, Nexus needs a centralized database to store collected data. To this end the Nevada Research Data Center is designed to collect, format, and store data for scientists to view and consider. This paper presents a new architecture solution for the NRDC. Based in microservices, the solution aims to ensure scalability, reliability, and maintainability of this data center. Background on NRDC is provided in the paper, together with details on the proposed solutions software specification, design, and prototype implementation. A discussion of the microservice-based architectures benefits and an outline of planned directions of future work are also included.

Ground Truth Verification Tool (GTVT) for Video Surveillance Systems

As cameras and storage devices have become cheaper, the number of video surveillance systems has also increased. Video surveillance was (and mostly is) done by human operators on a need-to-know basis. The advent of new algorithms from the computer vision community, and increased computational power offered by new CPUs have shown a strong possibility of automating this task. Different approaches have been proposed by computer scientists to solve the difficult problem of content recognition from video data. They use many different videos to prove their usefulness and accuracy. A careful comparison and evaluation needs to be done to find the most suitable method under given conditions. To compare the results given by video surveillance applications, the ground truth needs to be established. In the case of computer vision, the ground truth needs to be provided by humans, making it one of the most time-consuming tasks in the evaluation process. This paper presents a tool (GTVT) that allows the user to establish the ground truth for a given video. GTVT presents a user-friendly interface to perform the cumbersome task of ground truth establishment and verification.

Goal-related navigation of a neuromorphic virtual robot

The field of biologically inspired technology has evolved to the emergence of robots that operate autonomously. Some studies have focused on developing social robots that interact with humans by following social behaviors where other research have centered their efforts on mobile robots with the ability to navigate in their well-known environment. These general-purpose autonomous robots can perform a variety of functions independently, from recognizing people or objects to navigating in a familiar room. As of yet, no humanoid robot has been capable of traveling through a new suburban environment to reproduce goal-related learning and navigational activities. Based on experimental findings, we propose a computational model that is composed of critical interacting brain regions and utilizes fundamental learning mechanisms. It is incorporated in a sophisticated robotic system where a virtual robot navigates through a new environment, learns and recognizes visual landmarks, and consequently makes correct turning decisions to reach a reward. The detailed brain architecture included visual, entorhinal, prefrontal and premotor cortices, as well as the hippocampus. Our microcircuitry replicated some fundamental mammalian dynamics, which were integrated in a robotic loop. This virtual robotic system was designed around a number of components unique to our NeoCortical simulator (NCS) and our Virtual NeuroRobotic (VNR) paradigm. The neural simulation was executed on a remote computing cluster and was networked to the other system components (NCSTools, Webots, Gabor filter) using our Brain Communication Server (BCS), a server developed specifically for integration with NCS. The virtual humanoid was able to navigate through a new virtual environment and reach a reward after a sequence of turning actions. Along the way, it encountered familiar and non-familiar external cues to provide guidance and follow the correct direction. This is the first bio-inspired robot that showed high functionality during navigation while utilizing spiking cortical neurons in a real-time simulation. More importantly, it could take us a step closer to understanding memory impairments in Alzheimer’s patients.