Scheduling Algorithms for Multiprogramming in a Hard-Real-Time Environment
Journal of the ACM (JACM)
Diagnosing and correcting student's misconceptions in an educational computer algebra system
Proceedings of the 2001 international symposium on Symbolic and algebraic computation
Boolean satisfiability from theoretical hardness to practical success
Communications of the ACM - A Blind Person's Interaction with Technology
Beaver: Engineering an Efficient SMT Solver for Bit-Vector Arithmetic
CAV '09 Proceedings of the 21st International Conference on Computer Aided Verification
Mutation testing from probabilistic and stochastic finite state machines
Journal of Systems and Software
An introductory textbook on cyber-physical systems
WESE '10 Proceedings of the 2010 Workshop on Embedded Systems Education
Hard Real-Time Computing Systems: Predictable Scheduling Algorithms and Applications
Hard Real-Time Computing Systems: Predictable Scheduling Algorithms and Applications
Teaching embedded systems the Berkeley way
Proceedings of the Workshop on Embedded and Cyber-Physical Systems Education
Teaching embedded systems the Berkeley way
Proceedings of the Workshop on Embedded and Cyber-Physical Systems Education
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The advent of massively open online courses (MOOCs) poses several technical challenges for educators. One of these challenges is the need to automate, as much as possible, the generation of problems, creation of solutions, and grading, in order to deal with the huge number of students. We collectively refer to this challenge as automated exercise generation. In this paper, we present a step towards tackling this challenge for an embedded systems course. We present a template-based approach to classifying problems in a recent textbook by Lee and Seshia, and outline approaches to problem and solution generation based on mutation and satisfiability solving. Several directions for future work are also outlined.