CS2013-final-report

Table B-4: New and Expanded Core Learning Outcomes in CS2013
KA
AL
AR
Core Learning Outcomes as described in CS2013
Core-Tier1:
• Explain what is meant by “best”, “expected”, and “worst” case behavior of an
algorithm.
• In the context of specific algorithms, identify the characteristics of data and/or
other conditions or assumptions that lead to different behaviors.
• Perform empirical studies to validate hypotheses about runtime stemming from
mathematical analysis. Run algorithms on input of various sizes and compare
performance.
• Give examples that illustrate time-space trade-offs of algorithms.
• Use dynamic programming to solve an appropriate problem.
• Explain how tree balance affects the efficiency of various binary search tree
operations.
Core-Tier2:
• Define the classes P and NP.
• Explain the significance of NP-completeness.
• Discuss factors other than computational efficiency that influence the choice of
algorithms, such as programming time, maintainability, and the use of
application-specific patterns in the input data.
Core-Tier2:
• Comprehend the trend of modern computer architectures towards multi-core and
that parallelism is inherent in all hardware systems.
• Explain the implications of the “power wall” in terms of further processor
performance improvements and the drive towards harnessing parallelism.
• Design the basic building blocks of a computer: arithmetic-logic unit (gate-level),
registers (gate-level), central processing unit (register transfer-level), and
memory (register transfer-level).
• Use CAD tools for capture, synthesis, and simulation to evaluate simple building
blocks (e.g., arithmetic-logic unit, registers, movement between registers) of a
simple computer design.
• Evaluate the functional and timing diagram behavior of a simple processor
implemented at the logic circuit level.
• Compute Average Memory Access Time under a variety of cache and memory
configurations and mixes of instruction and data references.
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