Advanced study in models of computation, programming languages and algorithms with a specific focus on concurrent programming. The course includes models of computation, programming language paradigms ...

Start working toward program admission and requirements right away. Work you complete in the non-credit experience will transfer to the for-credit experience when you ...

Probabilistic programming has emerged as a powerful paradigm that integrates uncertainty directly into computational models. By embedding probabilistic constructs into conventional programming ...

Computers can be used to help solve problems. However, before a problem can be tackled, it must first be understood. Computational thinking helps us to solve problems. Designing, creating and refining ...

Programming Systems & Software Engineering research at Drexel University's College of Computing & Informatics (CCI) focuses on improving the design, construction, and maintenance of software systems, ...

We present an O(√n L)-iteration homogeneous and self-dual linear programming (LP) algorithm. The algorithm possesses the following features: • It solves the linear programming problem without any ...

Over at Dr. Dobbs, Rob Farber writes that, when used correctly, atomic operations can help implement a wide range of generic data structures and algorithms in the massively threaded GPU programming ...

There was a time when embedded system developers didn’t need to worry about graphics. When you have a PIC processor and two-line LCD, there isn’t much to learn. But if you are deploying Linux-based ...

Successive Linear Programming (SLP) algorithms solve nonlinear optimization problems via a sequence of linear programs. They have been widely used, particularly in the oil and chemical industries, ...