2026-09-19T03:45:13Zhttps://dspace.mit.edu/server/oai/requestoai:dspace.mit.edu:1721.1/1629762025-10-07T04:14:58Zcom_1721.1_7582com_1721.1_7581col_1721.1_131023
Sharma, Upamanyu
Kaashoek, M. Frans
McMenamy, Josiah
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
2025-10-06T17:37:46Z
2025-10-06T17:37:46Z
2025-05
2025-06-23T14:03:01.765Z
https://hdl.handle.net/1721.1/162976
This thesis aims to provide an intuitive debugging and learning tool for distributed systems that communicate by message passing. Understanding and debugging distributed systems can be challenging and slow to iterate on, so there is a need for tools that can speed up the time it takes to diagnose the root cause of a bug. There exists significant prior work in creating tools that can aid in the visualization and debugging of distributed system executions, such as the ShiViz log visualizer [13]. This work builds on top of these tools to provide more debugging information, handle large log files, and be easily instrumented in existing systems. We demonstrate using the tool to debug issues in an implementation of the Raft consensus algorithm [34].
M.Eng.
Massachusetts Institute of Technology
In Copyright - Educational Use Permitted
Copyright retained by author(s)
https://rightsstatements.org/page/InC-EDU/1.0/
DisViz: Visualizing real-world distributed system logs
with space time diagrams
Thesis
application/pdf
Master
Master of Engineering in Electrical Engineering and Computer Science
Publication
unknown
unknown
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<Abstract>This thesis aims to provide an intuitive debugging and learning tool for distributed systems that communicate by message passing. Understanding and debugging distributed systems can be challenging and slow to iterate on, so there is a need for tools that can speed up the time it takes to diagnose the root cause of a bug. There exists significant prior work in creating tools that can aid in the visualization and debugging of distributed system executions, such as the ShiViz log visualizer [13]. This work builds on top of these tools to provide more debugging information, handle large log files, and be easily instrumented in existing systems. We demonstrate using the tool to debug issues in an implementation of the Raft consensus algorithm [34].</Abstract>
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