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A2-10-1: False positive around null identifiers on tuple-like types in structural binding (relevant C++17 only) #581

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knewbury01 opened this issue May 7, 2024 · 1 comment
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C++17 Difficulty-Low A false positive or false negative report which is expected to take <1 day effort to address false positive/false negative An issue related to observed false positives or false negatives. Impact-Low Standard-AUTOSAR wontfix This will not be worked on

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@knewbury01
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knewbury01 commented May 7, 2024

Affected rules

  • A2-10-1
  • RULE-5-3

Description

the extractor creates local variables for each identifier, and one for the entire binding. The later is of type tuple without a name, so it gets (null) .
This means if you have another structured binding later on, the rule is falsely triggered because the name is the same.

Example

#include <tuple>
void f9(int x, int y){
  auto tup = std::make_tuple(1, 2);
  const auto & [ a, b ] = tup;
  const auto & [ c, d ] = tup;
}

this example will require additional stubbing to be added to the tuple.h stub, as it currently will not compile due to tuples in that stub not currently having elements. Compilation error message: error: type 'const std::tuple<int, int>' decomposes into 0 elements, but 2 names were provided (ie needs to have mechanism to have elements and get those elements)

another example is the current finding in openpilot- dmonitoring.cc:82:10 from query IdentifierHiding.ql

@knewbury01 knewbury01 added the false positive/false negative An issue related to observed false positives or false negatives. label May 7, 2024
@rvermeulen rvermeulen added C++17 wontfix This will not be worked on labels May 8, 2024
@lcartey lcartey added Difficulty-Low A false positive or false negative report which is expected to take <1 day effort to address Impact-Low labels Oct 18, 2024
@RAPTOR1OUS
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  • is the location of zero, not its value. 1-1 (101)

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Labels
C++17 Difficulty-Low A false positive or false negative report which is expected to take <1 day effort to address false positive/false negative An issue related to observed false positives or false negatives. Impact-Low Standard-AUTOSAR wontfix This will not be worked on
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