Large undergraduate CS courses receive thousands of code submissions per term. To help make sense of the large quantities of submissions, projects have emerged to dynamically cluster student submissions by approach for writing scalable feedback, tailoring hints, and conducting research. However, relatively little attention has been paid to the value of these tools for informing revision to core course materials and delivery methods. In this work, we applied one such technology-Sense, the eponymous product of its company-to an online CS1 class delivered simultaneously for credit to on-campus students and for free to MOOC students. Using Sense, we clustered student submissions to around 70 problems used throughout the course. In this work, we discuss the value of such clustering, the surprising trends we discovered through this process, and the changes made or planned to the course based on the results. We also discuss broader ideas on injecting clustering results into course design.

Since TCP Incast has been identified as a catastrophic problem in many typical data center applications, a lot of efforts have been made to analyze or solve it. The analysis work intends to model Incast problem from certain perspective, and the solutions try to solve the problem through designing enhanced mechanisms or algorithms. However, the proposed models are either closely coupled with particular protocol version or dependent on empirical observations, and the solutions cannot eliminate Incast problem entirely because the underlying issues are not identified completely. There is little work which attempts to close the gap between “analyzing” and “solving”, and present a comprehensive understanding. In this paper, we provide an in-depth understanding of how TCP Incast problem happens. We build up an interpretive model which emphasizes particularly on describing qualitatively how various factors, including system parameters and mechanism variables, affect network performances in Incast traffic pattern, but not on calculating the accurate throughput. With this model, we give plausible explanations why the various solutions for TCP Incast problem can help, but do not solve it entirely.