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Characterizing and optimizing the memory footprint of de novo short read DNA sequence assembly.

, and . ISPASS, page 143-152. IEEE Computer Society, (2009)

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Effect of Discrete and Continuous Parameter Variation on Difficulty in Automatic Item Generation., , , and . AIED (1), volume 11625 of Lecture Notes in Computer Science, page 71-83. Springer, (2019)Haptic Rendering: Programming Touch Interaction with Virtual Objects., , , , and . SI3D, page 123-130. ACM, (1995)Hardware tansactional memory support for lightweight dynamic language evolution., and . OOPSLA Companion, page 998-1008. ACM, (2006)Understanding the backward slices of performance degrading instructions., and . ISCA, page 172-181. IEEE Computer Society, (2000)Targeted Path Profiling: Lower Overhead Path Profiling for Staged Dynamic Optimization Systems., , and . CGO, page 239-250. IEEE Computer Society, (2004)On Students' Ability to Resolve their own Tracing Errors through Code Execution., and . SIGCSE (1), page 251-257. ACM, (2022)Evaluating Large Language Model Code Generation as an Autograding Mechanism for "Explain in Plain English" Questions., and . SIGCSE (2), page 1824-1825. ACM, (2024)Leveraging Second-Chance Testing to Improve Students' Outcomes., , and . ICER (2), page 50-51. ACM, (2023)Students' Perceptions and Behavior Related to Second-Chance Testing., , , , and . FIE, page 1-8. IEEE, (2021)Second-chance Testing Course Policies and Student Behavior., , and . FIE, page 1-7. IEEE, (2019)