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Bump ua-parser-js from 0.7.32 to 0.7.33

Open dependabot[bot] opened this issue 2 years ago • 3 comments

Bumps ua-parser-js from 0.7.32 to 0.7.33.

Changelog

Sourced from ua-parser-js's changelog.

Version 0.7.32 / 1.0.32

  • Add new browser : DuckDuckGo, Huawei Browser, LinkedIn
  • Add new OS : HarmonyOS
  • Add some Huawei models
  • Add Sharp Aquos TV
  • Improve detection Xiaomi Mi CC9
  • Fix Sony Xperia 1 III misidentified as Acer tablet
  • Fix Detect Sony BRAVIA as SmartTV
  • Fix Detect Xiaomi Mi TV as SmartTV
  • Fix Detect Galaxy Tab S8 as tablet
  • Fix WeGame mistakenly identified as WeChat
  • Fix included commas in Safari / Mobile Safari version
  • Increase UA_MAX_LENGTH to 350

Version 0.7.33 / 1.0.33

  • Add new browser : Cobalt
  • Identify Macintosh as an Apple device
  • Fix ReDoS vulnerability

Version 0.8

Version 0.8 was created by accident. This version is now deprecated and no longer maintained, please update to version 0.7 / 1.0.

Commits

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dependabot[bot] avatar Jan 27 '23 17:01 dependabot[bot]

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CLAassistant avatar Jan 27 '23 17:01 CLAassistant

This PR has 0 quantified lines of changes. In general, a change size of upto 200 lines is ideal for the best PR experience!


Quantification details

Label      : No Changes
Size       : +0 -0
Percentile : 0%

Total files changed: 1

Change summary by file extension:
.lock : +0 -0

Change counts above are quantified counts, based on the PullRequestQuantifier customizations.

Why proper sizing of changes matters

Optimal pull request sizes drive a better predictable PR flow as they strike a balance between between PR complexity and PR review overhead. PRs within the optimal size (typical small, or medium sized PRs) mean:

  • Fast and predictable releases to production:
    • Optimal size changes are more likely to be reviewed faster with fewer iterations.
    • Similarity in low PR complexity drives similar review times.
  • Review quality is likely higher as complexity is lower:
    • Bugs are more likely to be detected.
    • Code inconsistencies are more likely to be detected.
  • Knowledge sharing is improved within the participants:
    • Small portions can be assimilated better.
  • Better engineering practices are exercised:
    • Solving big problems by dividing them in well contained, smaller problems.
    • Exercising separation of concerns within the code changes.

What can I do to optimize my changes

  • Use the PullRequestQuantifier to quantify your PR accurately
    • Create a context profile for your repo using the context generator
    • Exclude files that are not necessary to be reviewed or do not increase the review complexity. Example: Autogenerated code, docs, project IDE setting files, binaries, etc. Check out the Excluded section from your prquantifier.yaml context profile.
    • Understand your typical change complexity, drive towards the desired complexity by adjusting the label mapping in your prquantifier.yaml context profile.
    • Only use the labels that matter to you, see context specification to customize your prquantifier.yaml context profile.
  • Change your engineering behaviors
    • For PRs that fall outside of the desired spectrum, review the details and check if:
      • Your PR could be split in smaller, self-contained PRs instead
      • Your PR only solves one particular issue. (For example, don't refactor and code new features in the same PR).

How to interpret the change counts in git diff output

  • One line was added: +1 -0
  • One line was deleted: +0 -1
  • One line was modified: +1 -1 (git diff doesn't know about modified, it will interpret that line like one addition plus one deletion)
  • Change percentiles: Change characteristics (addition, deletion, modification) of this PR in relation to all other PRs within the repository.


Was this comment helpful? :thumbsup:  :ok_hand:  :thumbsdown: (Email) Customize PullRequestQuantifier for this repository.