Browsing Computer Science Doctoral Work by Title
Now showing items 50-67 of 67
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Towards Better Engineering of Enterprise Resource Planning Systems
(North Dakota State University, 2016)In spite of their high implementation failure rate, Enterprise Resource Planning (ERP) software remains a popular choice for most businesses. When it succeeds, ERP software provides effective integration of formerly isolated ... -
Towards Change Propagating Test Models In Autonomic and Adaptive Systems
(North Dakota State University, 2012)The major motivation for self-adaptive computing systems is the self-adjustment of the software according to a changing environment. Adaptive computing systems can add, remove, and replace their own components in response ... -
Towards Improving P300-based Brain-Computer Interfaces: From Desktop to Mobile
(North Dakota State University, 2014)A brain-computer interface (BCI) enables a paralyzed user to interact with an external device through brain signals. A BCI measures identi es patterns within these measured signals, translating such patterns into commands. ... -
Towards Test Focus Selection for Integration Testing Using Software Metrics
(North Dakota State University, 2013)Object-oriented software systems contain a large number of modules which make the unit testing, integration testing, and system testing very difficult and challenging. While the aim of the unit testing is to show that ... -
Tracking Vehicles from Mobile Phone Received Signal Strength Sequences
(North Dakota State University, 2015)We address the problem of tracking vehicles from received signal strength (RSS) sequences generated by mobile phones carried in them. Our main objectives are to provide travel-time estimates for selected roads and provide ... -
Trust and Anti-Autonomy Modelling of Autonomous Systems
(North Dakota State University, 2020)Human trust in autonomous vehicles is built upon their safe and secure operability in the most ethical, law abiding manner possible. Despite the technological advancements that autonomous vehicles are equipped with, their ... -
A Two-phase Security Mechanism for Anomaly Detection in Wireless Sensor Networks
(North Dakota State University, 2013)Wireless Sensor Networks (WSNs) have been applied to a wide range of application areas, including battle fields, transportation systems, and hospitals. The security issues in WSNs are still hot research topics. The constrained ... -
Understanding Contextual Factors in Regression Testing Techniques
(North Dakota State University, 2016)The software regression testing techniques of test case reduction, selection, and prioritization are widely used and well-researched in software development. They allow for more efficient utilization of scarce testing ... -
Understanding the Patterns of Microservice Intercommunication From A Developer Perspective
(North Dakota State University, 2022)Microservices Architecture is the modern paradigm for designing software. Based on the divide-and-conquer strategy, microservices architecture organizes the application by furnishing it with a fine-level granularity. Each ... -
Usability Construct for Mobile Applications: A Clustering based Approach
(North Dakota State University, 2015)The growth of mobile applications that run on cell phones and other handheld devices has introduced a broad range of usability challenges that were not faced by the web and standalone PC environments. The current usability ... -
User-Behavior Trust Modeling in Cloud Security
(North Dakota State University, 2019)With the cloud computing increasing in popularity by providing a massive number of services such as recourses and data center, the number of attacks is increasing. Security is a basic concern in cloud computing, and threats ... -
Using Cyberlearning Environment to Improve Student’s Learning and Engagement in Introductory Computer Programming Courses
(North Dakota State University, 2019)All Computer Science majors are required to take introductory programming (CS1) as a fundamental course which has a high dropout rate. Researchers report that CS1 students lack motivation and need constant resource support. ... -
Using Human Error Models to Improve the Quality of Software Requirements
(North Dakota State University, 2018)Creating high quality software is a primary concern for software development organizations. Researchers have devoted considerable effort in developing quality improvement methods that help software engineers detect faults ... -
Using Information Retrieval to Improve Integration Testing
(North Dakota State University, 2012)Software testing is an important factor of the software development process. Integration testing is an important and expensive level of the software testing process. Unfortunately, since the developers have limited time ... -
Using Learning Styles to Improve Software Requirements Quality: An Empirical Investigation
(North Dakota State University, 2017)The success of a software organization depends upon its ability to deliver a quality software product within time and budget constraints. To ensure the delivery of quality software, software inspections have proven to be ... -
Using Machine Learning and Graph Mining Approaches to Improve Software Requirements Quality: An Empirical Investigation
(North Dakota State University, 2019)Software development is prone to software faults due to the involvement of multiple stakeholders especially during the fuzzy phases (requirements and design). Software inspections are commonly used in industry to detect ... -
Vector-Item Pattern Mining Algorithms and their Applications
(North Dakota State University, 2011)Advances in storage technology have long been driving the need for new data mining techniques. Not only are typical data sets becoming larger, but the diversity of available attributes is increasing in many problem domains. ... -
Virtual-Experiment-Driven Process Model (VEDPM)
(North Dakota State University, 2010)Computer simulations are the last resort for many complex problems such as swarm applications. However, to the best of the author's knowledge, there is no convincing work in proving ''What You Simulate ls What You See'' ...