Currently, there is basically just one clang-tidy check to impose
some sanity limits on functions - `clang-tidy-readability-function-size`.
It is nice, allows to limit line count, total number of statements,
number of branches, number of function parameters (not counting
implicit `this`), nesting level.
However, those are simple generic metrics. It is still trivially possible
to write a function, which does not violate any of these metrics,
yet is still rather unreadable.
Thus, some additional, slightly more complicated metric is needed.
There is a well-known [[ https://en.wikipedia.org/wiki/Cyclomatic_complexity | Cyclomatic complexity]], but certainly has its downsides.
And there is a [[ https://www.sonarsource.com/docs/CognitiveComplexity.pdf | COGNITIVE COMPLEXITY by SonarSource ]], which is available for opensource on https://sonarcloud.io/.
This check checks function Cognitive Complexity metric, and flags
the functions with Cognitive Complexity exceeding the configured limit.
The default limit is `25`, same as in 'upstream'.
The metric is implemented as per [[ https://www.sonarsource.com/docs/CognitiveComplexity.pdf | COGNITIVE COMPLEXITY by SonarSource ]] specification version 1.2 (19 April 2017), with two notable exceptions:
* `preprocessor conditionals` (`#ifdef`, `#if`, `#elif`, `#else`,
`#endif`) are not accounted for.
Could be done. Currently, upstream does not account for them either.
* `each method in a recursion cycle` is not accounted for.
It can't be fully implemented, because cross-translational-unit
analysis would be needed, which is not possible in clang-tidy.
Thus, at least right now, i completely avoided implementing it.
There are some further possible improvements:
* Are GNU statement expressions (`BinaryConditionalOperator`) really free?
They should probably cause nesting level increase,
and complexity level increase when they are nested within eachother.
* Microsoft SEH support
* ???
Reviewed By: aaron.ballman, JonasToth, lattner
Differential Revision: https://reviews.llvm.org/D36836
several changes:
- return a structure result in rename API;
- prepareRename now returns more information (main-file occurrences);
- remove the duplicated detecting-touch-identifier code in prepareRename (which is implemented in rename API);
Differential Revision: https://reviews.llvm.org/D88634
It fixes the -Wswitch warning, though we mark it as a fix even if that is off.
This makes it the "recommended" action on an incomplete switch, which seems OK.
Differential Revision: https://reviews.llvm.org/D88726
Intent was a nice idea but it ends up being a bit awkward/heavyweight
without adding much.
In particular, it makes it hard to implement `CodeActionParams.only` properly
(there's an inheritance hierarchy for kinds).
Differential Revision: https://reviews.llvm.org/D88427
Some projects do not use the TEMP_FAILURE_RETRY macro but define their
own one, as not to depend on glibc / Bionic details. By allowing the
user to override the list of macros, these projects can also benefit
from this check.
Differential Revision: https://reviews.llvm.org/D83144
This allows us MSAN to instrument this function. Previous version is not
instrumentable due to it shear volume.
Differential Revision: https://reviews.llvm.org/D88536
This is a tool to simply parse a file as clangd would, and run some
common features (code actions, go-to-definition, hover) in an attempt to
trigger or reproduce crashes, error diagnostics, etc.
This is easier and more predictable than loading the file in clangd, because:
- there's no editor/plugin variation to worry about
- there's no accidental variation of user behavior or other extraneous requests
- we trigger features at every token, rather than guessing
- everything is synchronoous, logs are easier to reason about
- it's easier to (get users to) capture logs when running on the command-line
This is a fairly lightweight variant of this idea.
We could do a lot more with it, and maybe we should.
But I can't in the near future, and experience will tell us if we made
the right tradeoffs and if it's worth investing further.
Differential Revision: https://reviews.llvm.org/D88338
Relative paths received from the server are always in posix style. So
we need to ensure they are relative using that style, and not the native one.
Differential Revision: https://reviews.llvm.org/D88507
In preparation for making moving TweakFilter from ClangdServer::Options to
a ClangdLSPServer option, and letting it vary per-request.
(In order to implement CodeActionParams.only)
Also a general overdue cleanup.
Differential Revision: https://reviews.llvm.org/D88470
Extend the Trivial setter documentation to support cases where the value is moved into a field using `std::move`.
Reviewed By: sammccall, kadircet
Differential Revision: https://reviews.llvm.org/D88297
As @kadircet mentions in D84912#2184144, `findNearbyIdentifier()` traverses the whole file if there is no identifier for the word.
This patch ensures give up after 2^N lines in any case.
Reviewed By: sammccall
Differential Revision: https://reviews.llvm.org/D87891
MSAN build times out for generated DecisionForest inference runtime.
A solution worth trying is splitting the function into 300 smaller
functions and then re-enable msan.
For now we are disabling instrumentation for the generated function.
Differential Revision: https://reviews.llvm.org/D88495
Improve the recently-added PopulateSwitch tweak to work on non-empty switches.
Reviewed By: sammccall
Differential Revision: https://reviews.llvm.org/D88434
Since we have 2 scoring functions (heuristics and decision forest),
renaming the existing evaluate() function to be more descriptive of the
Heuristics being evaluated in it.
Differential Revision: https://reviews.llvm.org/D88431
By default clangd will score a code completion item using heuristics model.
Scoring can be done by Decision Forest model by passing `--ranking_model=decision_forest` to
clangd.
Features omitted from the model:
- `NameMatch` is excluded because the final score must be multiplicative in `NameMatch` to allow rescoring by the editor.
- `NeedsFixIts` is excluded because the generating dataset that needs 'fixits' is non-trivial.
There are multiple ways (heuristics) to combine the above two features with the prediction of the DF:
- `NeedsFixIts` is used as is with a penalty of `0.5`.
Various alternatives of combining NameMatch `N` and Decision forest Prediction `P`
- N * scale(P, 0, 1): Linearly scale the output of model to range [0, 1]
- N * a^P:
- More natural: Prediction of each Decision Tree can be considered as a multiplicative boost (like NameMatch)
- Ordering is independent of the absolute value of P. Order of two items is proportional to `a^{difference in model prediction score}`. Higher `a` gives higher weightage to model output as compared to NameMatch score.
Baseline MRR = 0.619
MRR for various combinations:
N * P = 0.6346, advantage%=2.5768
N * 1.1^P = 0.6600, advantage%=6.6853
N * **1.2**^P = 0.6669, advantage%=**7.8005**
N * **1.3**^P = 0.6668, advantage%=**7.7795**
N * **1.4**^P = 0.6659, advantage%=**7.6270**
N * 1.5^P = 0.6646, advantage%=7.4200
N * 1.6^P = 0.6636, advantage%=7.2671
N * 1.7^P = 0.6629, advantage%=7.1450
N * 2^P = 0.6612, advantage%=6.8673
N * 2.5^P = 0.6598, advantage%=6.6491
N * 3^P = 0.6590, advantage%=6.5242
N * scaled[0, 1] = 0.6465, advantage%=4.5054
Differential Revision: https://reviews.llvm.org/D88281
Replaces the dummy CodeCompletion model with a trained DecisionForest
model.
The features.json needs to be manually curated specifying the features
to be used. This is a one-time cost and does not change if the model
changes until we decide to add/remove features.
Differential Revision: https://reviews.llvm.org/D88071
Add a tweak that populates an empty switch statement of an enumeration type with all of the enumerators of that type.
Before:
```
enum Color { RED, GREEN, BLUE };
void f(Color color) {
switch (color) {}
}
```
After:
```
enum Color { RED, GREEN, BLUE };
void f(Color color) {
switch (color) {
case RED:
case GREEN:
case BLUE:
break;
}
}
```
Reviewed By: sammccall
Differential Revision: https://reviews.llvm.org/D88383
Create targets `check-clang-extra-clang-tidy`, `check-clang-extra-clang-query`
similar to how `check-clang-sema`, `check-clang-parser`, etc. are
auto-generated from the directory structure.
This allows running only a particular sub-tool's tests, not having to wait
through the entire `check-clang-tools` execution.
Differential Revision: http://reviews.llvm.org/D84176
Translating between JSON objects and C++ strutctures is common.
From experience in clangd, fromJSON/ObjectMapper work well and save a lot of
code, but aren't adopted elsewhere at least partly due to total lack of error
reporting beyond "ok"/"bad".
The recently-added error model should be rich enough for most applications.
It requires tracking the path within the root object and reporting local
errors at appropriate places.
To do this, we exploit the fact that the call graph of recursive
parse functions mirror the structure of the JSON itself.
The current path is represented as a linked list of segments, each of which is
on the stack as a parameter. Concretely, fromJSON now looks like:
bool fromJSON(const Value&, T&, Path);
Beyond the signature change, this is reasonably unobtrusive: building
the path segments is mostly handled by ObjectMapper and the vector<T> fromJSON.
However the root caller of fromJSON must now create a Root object to
store the errors, which is a little clunky.
I've added high-level parse<T>(StringRef) -> Expected<T>, but it's not
general enough to be the primary interface I think (at least, not usable in
clangd).
All existing users (mostly just clangd) are updated in this patch,
making this change backwards-compatible is a bit hairy.
Differential Revision: https://reviews.llvm.org/D88103
Current implementation of heuristic-based scoring function also contains
computation of derived signals (e.g. whether name contains a word from
context, computing file distances, scope distances.)
This is an attempt to separate out the logic for computation of derived
signals from the scoring function.
This will allow us to have a clean API for scoring functions that will
take only concrete code completion signals as input.
Differential Revision: https://reviews.llvm.org/D88146
Finds member initializations in the constructor body which can be placed
into the initialization list instead. This does not only improves the
readability of the code but also affects positively its performance.
Class-member assignments inside a control statement or following the
first control statement are ignored.
Differential Revision: https://reviews.llvm.org/D71199
We intend to replace heuristics based code completion ranking with a Decision Forest Model.
This patch introduces a format for representing the model and an inference runtime that is code-generated at build time.
- Forest.json contains all the trees as an array of trees.
- Features.json describes the features to be used.
- Codegen file takes the above two files and generates CompletionModel containing Feature struct and corresponding Evaluate function.
The Evaluate function maps a feature to a real number describing the relevance of this candidate.
- The codegen is part of build system and these files are generated at build time.
- Proposes a way to test the generated runtime using a test model.
- Replicates the model structure in unittests.
- unittest tests both the test model (for correct tree traversal) and the real model (for sanity).
This reverts commit 549e55b3d5.
Aaron Ballman