Visualizing Distributed System Executions

Abstract

Distributed systems pose unique challenges for software developers. Understanding the system’s communication topology and reasoning about concurrent activities of system hosts can be difficult. The standard approach, analyzing system logs, can be a tedious and complex process that involves reconstructing a system log from multiple hosts’ logs, reconciling timestamps among hosts with non-synchronized clocks, and understanding what took place during the execution encoded by the log. This article presents a novel approach for tackling three tasks frequently performed during analysis of distributed system executions: (1) understanding the relative ordering of events, (2) searching for specific patterns of interaction between hosts, and (3) identifying structural similarities and differences between pairs of executions. Our approach consists of XVector , which instruments distributed systems to capture partial ordering information that encodes the happens-before relation between events, and ShiViz , which processes the resulting logs and presents distributed system executions as interactive time-space diagrams. Two user studies with a total of 109 students and a case study with 2 developers showed that our method was effective, helping participants answer statistically significantly more system-comprehension questions correctly, with a very large effect size.

Visual Analysis of Hyperproperties for Understanding Model Checking Results

“…Visualizing Parallel Executions Research on distributed systems has examined how to visualize multiple, parallel executions of a system. Two examples are ODDITY [63,87] and SHIVIS [2,8]. Oddity consists of an interactive visual debugger and is part of the DSLABS framework, which also includes a model checker for distributed systems.…”

Better state pictures facilitating state machine characteristic conjecture

“…ShiViz [5] is a tool to visualize logs generated by distributed systems. Logs in this context are basically sequences of events, hosts that carry out the events and timestamps when the hosts carried out the events.…”

DeLag: Detecting Latency Degradation Patterns in Service-based Systems

“…Other studies on software diagnosis rely on visualization techniques. Beschastnikh et al [42] introduced ShiViz, which presents distributed system executions as interactive timespace diagrams to help diagnosis and debugging of software issues. Zhou et al [7] used ShiViz to conduct an empirical study to investigate the effectiveness of existing industrial debugging practices compared to those of state-of-the-art tracing and visualization techniques for distributed systems, thus showing that the current industrial practices of debugging can be improved by employing proper tracing and visualization techniques.…”