Update variable/property assignment completion so it can fallback to type inference #21134

MartinGC94 · 2024-01-23T18:13:33Z

PR Summary

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.

PR Context

PR Checklist

…type inference

pull-request-quantifier-deprecated · 2024-01-23T21:51:35Z

This PR has 59 quantified lines of changes. In general, a change size of upto 200 lines is ideal for the best PR experience!

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Label      : Small
Size       : +53 -6
Percentile : 23.6%

Total files changed: 2

Change summary by file extension:
.cs : +44 -6
.ps1 : +9 -0

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…ve a type constraint assigned and not just inferred.

pull-request-quantifier-deprecated · 2024-01-29T16:29:36Z

This PR has 134 quantified lines of changes. In general, a change size of upto 200 lines is ideal for the best PR experience!

Quantification details

Label      : Medium
Size       : +103 -31
Percentile : 46.8%

Total files changed: 3

Change summary by file extension:
.cs : +94 -31
.ps1 : +9 -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.

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pull-request-quantifier-deprecated · 2024-02-04T00:29:43Z

This PR has 134 quantified lines of changes. In general, a change size of upto 200 lines is ideal for the best PR experience!

Quantification details

Label      : Medium
Size       : +103 -31
Percentile : 46.8%

Total files changed: 3

Change summary by file extension:
.cs : +94 -31
.ps1 : +9 -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.

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pull-request-quantifier-deprecated · 2024-02-10T17:23:04Z

This PR has 134 quantified lines of changes. In general, a change size of upto 200 lines is ideal for the best PR experience!

Quantification details

Label      : Medium
Size       : +103 -31
Percentile : 46.8%

Total files changed: 3

Change summary by file extension:
.cs : +94 -31
.ps1 : +9 -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.

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iSazonov · 2025-02-26T13:30:44Z

@MartinGC94 Please resolve merge conflicts and rebase.

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

test/powershell/Host/TabCompletion/TabCompletion.Tests.ps1

iSazonov · 2025-02-27T05:58:55Z

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

+                return false;
+            }
+
+            var values = new SortedSet<string>();


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 as values ??= new SortedSet<string>();
I think about this when I see a null check in the calling code.

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 early return 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.

iSazonov · 2025-02-27T09:18:21Z

/azp run

azure-pipelines · 2025-02-27T09:18:35Z

Azure Pipelines successfully started running 2 pipeline(s).

microsoft-github-policy-service · 2025-02-27T09:34:54Z

📣 Hey @MartinGC94, how did we do? We would love to hear your feedback with the link below! 🗣️

🔗 https://aka.ms/PSRepoFeedback

Microsoft Forms

MartinGC94 added 2 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

pull-request-quantifier-deprecated bot added the Small label Jan 23, 2024

Restrict the completion for variable assignments to variables that ha…

152cb96

…ve a type constraint assigned and not just inferred.

pull-request-quantifier-deprecated bot added Medium and removed Small labels Jan 29, 2024

Actually use the found type constraint

6514880

Merge branch 'PowerShell:master' into CompletionForVarAndPropAssignments

bea85a5

microsoft-github-policy-service bot added the Review - Needed The PR is being reviewed label Feb 18, 2024

iSazonov added the CL-General Indicates 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-service bot removed the Review - Needed The PR is being reviewed label Feb 26, 2025

MartinGC94 and others added 2 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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iSazonov approved these changes Feb 27, 2025

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iSazonov enabled auto-merge (squash) February 27, 2025 09:19

iSazonov merged commit 7290494 into PowerShell:master Feb 27, 2025
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MartinGC94 deleted the CompletionForVarAndPropAssignments branch February 28, 2025 10:39

Update variable/property assignment completion so it can fallback to type inference #21134

Update variable/property assignment completion so it can fallback to type inference #21134

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MartinGC94 commented Jan 23, 2024

PR Summary

PR Context

PR Checklist

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