Updates the completion code when assigning values to variables and properties so it includes a fallback to type inference when the variable/property has no value assigned.

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Make sure all.h,.cpp,.cs,.ps1 and.psm1 files have the correct copyright header
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MartinGC94 added2 commits

January 23, 2024 19:11

Update variable/property assignment completion so it can fallback to …

a36ce71

…type inference

Fix test and handle user input properly.

06c534d

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This PR has59 quantified lines of changes. In general, a change size of upto200 lines is ideal for the best PR experience!

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Restrict the completion for variable assignments to variables that ha…

152cb96

…ve a type constraint assigned and not just inferred.

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pull-request-quantifier-deprecatedbot commentedJan 29, 2024

This PR has134 quantified lines of changes. In general, a change size of upto200 lines is ideal for the best PR experience!

Quantification details

Label      : MediumSize       : +103 -31Percentile : 46.8%Total files changed: 3Change summary by file extension:.cs : +94 -31.ps1 : +9 -0

Change counts above are quantified counts, based on thePullRequestQuantifier customizations.

Why proper sizing of changes matters

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 thecontext 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 theExcluded section from yourprquantifier.yaml context profile.
- Understand your typical change complexity, drive towards the desired complexity by adjusting the label mapping in yourprquantifier.yaml context profile.
- Only use the labels that matter to you,see context specification to customize yourprquantifier.yaml context profile.
Change your engineering behaviors
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  - 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)
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Actually use the found type constraint

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pull-request-quantifier-deprecatedbot commentedFeb 4, 2024

This PR has134 quantified lines of changes. In general, a change size of upto200 lines is ideal for the best PR experience!

Quantification details

Label      : MediumSize       : +103 -31Percentile : 46.8%Total files changed: 3Change summary by file extension:.cs : +94 -31.ps1 : +9 -0

Change counts above are quantified counts, based on thePullRequestQuantifier customizations.

Why proper sizing of changes matters

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 thecontext 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 theExcluded section from yourprquantifier.yaml context profile.
- Understand your typical change complexity, drive towards the desired complexity by adjusting the label mapping in yourprquantifier.yaml context profile.
- Only use the labels that matter to you,see context specification to customize yourprquantifier.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)
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Merge branch 'PowerShell:master' into CompletionForVarAndPropAssignments

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pull-request-quantifier-deprecatedbot commentedFeb 10, 2024

This PR has134 quantified lines of changes. In general, a change size of upto200 lines is ideal for the best PR experience!

Quantification details

Label      : MediumSize       : +103 -31Percentile : 46.8%Total files changed: 3Change summary by file extension:.cs : +94 -31.ps1 : +9 -0

Change counts above are quantified counts, based on thePullRequestQuantifier customizations.

Why proper sizing of changes matters

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 thecontext 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 theExcluded section from yourprquantifier.yaml context profile.
- Understand your typical change complexity, drive towards the desired complexity by adjusting the label mapping in yourprquantifier.yaml context profile.
- Only use the labels that matter to you,see context specification to customize yourprquantifier.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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microsoft-github-policy-servicebot added the Review - NeededThe PR is being reviewed label

Feb 18, 2024

iSazonov added the CL-GeneralIndicates that a PR should be marked as a general cmdlet change in the Change Log label

Feb 26, 2025

iSazonov self-assigned this

Feb 26, 2025

microsoft-github-policy-servicebot removed the Review - NeededThe PR is being reviewed label

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iSazonov commentedFeb 26, 2025

@MartinGC94 Please resolve merge conflicts and rebase.

MartinGC94and others added2 commits

February 26, 2025 16:14

Merge branch 'master' into CompletionForVarAndPropAssignments

b241b53

Fix merge conflict

d9a5df4

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iSazonov reviewed

Feb 26, 2025

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src/System.Management.Automation/engine/CommandCompletion/CompletionAnalysis.cs OutdatedShow resolvedHide resolved

test/powershell/Host/TabCompletion/TabCompletion.Tests.ps1 OutdatedShow resolvedHide resolved

Address feedback

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iSazonov reviewed

Feb 27, 2025

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src/System.Management.Automation/engine/CommandCompletion/CompletionAnalysis.cs

		return false;
		}

		var values = new SortedSet<string>();

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iSazonovFeb 27, 2025

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It is not mandatory request and it is not critical for the code but it looks sloppy if we don't follow the rule - return null if there are no values, otherwise return non-empty collection.
I'd move the initialization in line 1481 asvalues ??= new SortedSet<string>();
I think about this when I see a null check in the calling code.

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MartinGC94Feb 27, 2025

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return null if there are no values, otherwise return non-empty collection.

But I am following that rule.result is set to null at the beginning so in all the earlyreturn false cases it will return null. Once I assign it an actual collection, I don't return without first checking if it's empty and if so, setting it back to null.