Quality: how to assure it and verify it, and the need for a culture of quality. Avoidance of errors and other quality problems. Inspections and reviews. Testing, verification and validation techniques. Process assurance vs. Product assurance. Quality process standards. Product and process assurance. Problem analysis and reporting. Statistical approaches to quality control.

Software architectural patterns and techniques for building web applications. This course is intended to expose students to theories and principles of web-based user interface design, and a wide variety of client- and server-side technologies for developing web applications.

Project-based course on advanced data visualization techniques. Topics may include: scalable visualization methods, multidimensional data analysis, network visualization, geospatial visualization, and interactive visualization. Ethical issues in data science.

Prerequisites: Completion of three core courses.   Development of a detailed, significant project in computer science under the close supervision of a faculty member, perhaps as one member of a student team. This project may be a software implementation, a design effort, or a theoretical or practical written analysis. Project report with optional oral presentation must be evaluated by three faculty members including the project supervisor.  

Offered as needed to present advanced material to graduate students.