Bump Microsoft.AspNetCore.Mvc.NewtonsoftJson from 7.0.1 to 7.0.2

[dependabot]

Bumps Microsoft.AspNetCore.Mvc.NewtonsoftJson from 7.0.1 to 7.0.2.

Release notes

Sourced from Microsoft.AspNetCore.Mvc.NewtonsoftJson's releases.

.NET 7.0.2

Release

Commits

• 7c81065 [internal/release/7.0] Update dependencies from dnceng/internal/dotnet-runtime
• da13e9c Merged PR 28023: Fixup mistakenly flowed shas from post-7.0.1
• 5161236 [internal/release/7.0] Update dependencies from dnceng/internal/dotnet-runtime
• 329a604 [internal/release/7.0] Update dependencies from dnceng/internal/dotnet-efcore
• 8cd0f81 Merge in 'release/7.0' changes
• b9e4f66 [release/7.0] Infer parameter source from ElementType for IEnumerable (#45256)
• 197dcfc [internal/release/7.0] Update dependencies from dnceng/internal/dotnet-efcore
• 9193712 [internal/release/7.0] Update dependencies from dnceng/internal/dotnet-efcore
• 212a2bd Merge in 'release/7.0' changes
• 9275bc9 [release/7.0] Use new Arm64 Helix queues (#45121)
• Additional commits viewable in compare view

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[pull-request-quantifier-deprecated]

This PR has 2 quantified lines of changes. In general, a change size of upto 200 lines is ideal for the best PR experience!

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Quantification details

Label      : Extra Small
Size       : +1 -1
Percentile : 0.8%

Total files changed: 1

Change summary by file extension:
.props : +1 -1

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.

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[dependabot]

Superseded by #14.