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apache/texera/8dee1c71adfc3a730fe9fd613643cd3bb9123ad5
commit
8dee1c71adfc3a730fe9fd613643cd3bb9123ad5
[log]
author
Xinyuan Lin <xinyual3@uci.edu>
Sun Jul 12 22:44:04 2026 -0700
committer
GitHub <noreply@github.com>
Mon Jul 13 05:44:04 2026 +0000
tree
143fc353b8d711586e04d88bfdf32cb045c34e47
parent
cda063b1bc55794a07dcb0836acc707153a1f1ff [diff]
test(frontend): extend ExecuteWorkflowService coverage (#6371)

### What changes were proposed in this PR?

Extends the `ExecuteWorkflowService` spec (was ~49% covered): the
websocket-event switch (region/region-state/worker-assignment/default),
reconfiguration-event notifications, execution-state transitions, and
request-builder helpers.

### Any related issues, documentation, discussions?

Closes #6368.

### How was this PR tested?

Added 24 tests (now 35), driving the faked WorkflowWebsocketService
event subject; clears sessionStorage in afterEach. Verified locally with
Vitest and CI's `format:ci` gate clean. Test-only change — no production
code is modified.

### Was this PR authored or co-authored using generative AI tooling?

Generated-by: Claude Code (Opus 4.8 [1M context])
1 file changed
tree: 143fc353b8d711586e04d88bfdf32cb045c34e47
  1. .github/
  2. .run/
  3. access-control-service/
  4. agent-service/
  5. amber/
  6. bin/
  7. common/
  8. computing-unit-managing-service/
  9. config-service/
  10. docs/
  11. file-service/
  12. frontend/
  13. licenses/
  14. licenses-3rd-party-code/
  15. notebook-migration-service/
  16. project/
  17. pyright-language-service/
  18. sql/
  19. workflow-compiling-service/
  20. .asf.yaml
  21. .dockerignore
  22. .gitattributes
  23. .gitignore
  24. .jvmopts
  25. .licenserc.yaml
  26. .scalafix.conf
  27. .scalafmt.conf
  28. AGENTS.md
  29. build.sbt
  30. CLAUDE.md
  31. codecov.yml
  32. CONTRIBUTING.md
  33. DISCLAIMER
  34. LICENSE
  35. NOTICE
  36. README.md
  37. SECURITY.md
README.md

Apache Texera (Incubating) is an open-source platform for human-AI collaborative data science using visual workflows. It enables human analysts to construct, execute, and refine data analysis tasks through an intuitive GUI, assisted by AI agents that understand natural-language instructions. Texera is well suited for a wide range of applications, including “AI for Science,” by making advanced AI and data science capabilities accessible to a broader community. It can run on a laptop for local use or be deployed in the cloud to support scalable processing of large datasets.

The platform has the following key features:

  • Natural-language data science through AI agents
  • Intuitive GUI-based workflows for data science
  • Real-time collaboration for workflow editing and execution
  • Runtime debugging and interactive workflow execution
  • Language-agnostic workflow runtime, native support for Python and Java
  • Parallel backend engine for scalable big-data processing
  • Separation of compute and storage for flexible cloud deployment

texera-screenshot

Citation

Please cite Texera as


@article{DBLP:journals/pvldb/WangHNKALLDL24,
  author       = {Zuozhi Wang and
                  Yicong Huang and
                  Shengquan Ni and
                  Avinash Kumar and
                  Sadeem Alsudais and
                  Xiaozhen Liu and
                  Xinyuan Lin and
                  Yunyan Ding and
                  Chen Li},
  title        = {Texera: {A} System for Collaborative and Interactive Data Analytics
                  Using Workflows},
  journal      = {Proc. {VLDB} Endow.},
  volume       = {17},
  number       = {11},
  pages        = {3580--3588},
  year         = {2024},
  url          = {https://www.vldb.org/pvldb/vol17/p3580-wang.pdf},
  timestamp    = {Thu, 19 Sep 2024 13:09:37 +0200},
  biburl       = {https://dblp.org/rec/journals/pvldb/WangHNKALLDL24.bib},
  bibsource    = {dblp computer science bibliography, https://dblp.org}
}