[NAE-1381] Public view task loading

[Daniell7]

Description

Set LoadingEmitter while system creating new case

Fixed NAE-1381

Dependencies

none

Third party dependencies

No new dependencies were introduced

Blocking Pull requests

There are no dependencies on other PR

How Has Been This Tested?

Assisted testing + manual testing + front-end tests

Test Configuration

Name	Tested on
OS	Windows 10
Runtime	Node 12.18.3
Dependency Manager	NPM 6.14.6
Framework version	Angular 10
Run parameters
Other configuration

Checklist:

• My code follows the style guidelines of this project
• I have performed a self-review of my own code
• My changes have been checked, personally or remotely, with @camperko
• I have commented my code, particularly in hard-to-understand areas
• I have resolved all conflicts with the target branch of the PR
• I have updated and synced my code with the target branch
• I have added tests that prove my fix is effective or that my feature works
• New and existing tests pass locally with my changes:
  • Lint test
  • Unit tests
  • Integration tests
• I have checked my contribution with code analysis tools:
  • SonarCloud
  • Snyk
• I have made corresponding changes to the documentation:
  • Developer documentation
  • User Guides
  • Migration Guides

[pull-request-quantifier-deprecated]

This PR has 63 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      : Small
Size       : +58 -5
Percentile : 25.2%

Total files changed: 6

Change summary by file extension:
.ts : +58 -5

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 detetcted.
• 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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[sonarqubecloud]

Kudos, SonarCloud Quality Gate passed!   

0 Bugs
0 Vulnerabilities
0 Security Hotspots
0 Code Smells

63.6% Coverage
0.0% Duplication