# This Page Is Under Construction

# Checker Developer Manual

The static analyzer engine performs path-sensitive exploration of the program and relies on a set of checkers to implement the logic for detecting and constructing specific bug reports. Anyone who is interested in implementing their own checker, should check out the Building a Checker in 24 Hours talk (slides video) and refer to this page for additional information on writing a checker. The static analyzer is a part of the Clang project, so consult Hacking on Clang and LLVM Programmer's Manual for developer guidelines and send your questions and proposals to cfe-dev mailing list.

- Getting Started
- Analyzer Overview
- Idea for a Checker
- Checker Registration
- Checker Skeleton
- Exploded Node
- Bug Reports
- AST Visitors
- Testing
- Useful Commands

## Getting Started

- To check out the source code and build the project, follow steps 1-4 of the Clang Getting Started page.
- The analyzer source code is located under the Clang source tree:
  `$ cd llvm/tools/clang`
  See: `include/clang/StaticAnalyzer`, `lib/StaticAnalyzer`, `test/Analysis`.
- The analyzer regression tests can be executed from the Clang's build directory:
  `$ cd ../../../; cd build/tools/clang; TESTDIRS=Analysis make test`
- Analyze a file with the specified checker:
  `$ clang -cc1 -analyze -analyzer-checker=core.DivideZero test.c`
- List the available checkers:
  `$ clang -cc1 -analyzer-checker-help`
- See the analyzer help for different output formats, fine tuning, and debug options:
  `$ clang -cc1 -help | grep "analyzer"`

## Static Analyzer Overview

The analyzer core performs symbolic execution of the given program. All the input values are represented with symbolic values; further, the engine deduces the values of all the expressions in the program based on the input symbols and the path. The execution is path sensitive and every possible path through the program is explored. The explored execution traces are represented with ExplodedGraph object. Each node of the graph is ExplodedNode, which consists of a `ProgramPoint` and a `ProgramState`.

ProgramPoint represents the corresponding location in the program (or the CFG graph). `ProgramPoint` is also used to record additional information on when/how the state was added. For example, `PostPurgeDeadSymbolsKind` kind means that the state is the result of purging dead symbols - the analyzer's equivalent of garbage collection.

ProgramState represents abstract state of the program. It consists of:

- `Environment` - a mapping from source code expressions to symbolic values
- `Store` - a mapping from memory locations to symbolic values
- `GenericDataMap` - constraints on symbolic values

### Interaction with Checkers

Checkers are not merely passive receivers of the analyzer core changes - they actively participate in the `ProgramState` construction through the `GenericDataMap` which can be used to store the checker-defined part of the state. Each time the analyzer engine explores a new statement, it notifies each checker registered to listen for that statement, giving it an opportunity to either report a bug or modify the state. (As a rule of thumb, the checker itself should be stateless.) The checkers are called one after another in the predefined order; thus, calling all the checkers adds a chain to the `ExplodedGraph`.

### Representing Values

During symbolic execution, SVal objects are used to represent the semantic evaluation of expressions. They can represent things like concrete integers, symbolic values, or memory locations (which are memory regions). They are a discriminated union of "values", symbolic and otherwise. If a value isn't symbolic, usually that means there is no symbolic information to track. For example, if the value was an integer, such as `42`, it would be a ConcreteInt, and the checker doesn't usually need to track any state with the concrete number. In some cases, `SVal` is not a symbol, but it really should be a symbolic value. This happens when the analyzer cannot reason about something (yet). An example is floating point numbers. In such cases, the `SVal` will evaluate to UnknownVal. This represents a case that is outside the realm of the analyzer's reasoning capabilities. `SVals` are value objects and their values can be viewed using the `.dump()` method. Often they wrap persistent objects such as symbols or regions.

SymExpr (symbol) is meant to represent abstract, but named, symbolic value. Symbols represent an actual (immutable) value. We might not know what its specific value is, but we can associate constraints with that value as we analyze a path. For example, we might record that the value of a symbol is greater than `0`, etc.

MemRegion is similar to a symbol. It is used to provide a lexicon of how to describe abstract memory. Regions can layer on top of other regions, providing a layered approach to representing memory. For example, a struct object on the stack might be represented by a `VarRegion`, but a `FieldRegion` which is a subregion of the `VarRegion` could be used to represent the memory associated with a specific field of that object. So how do we represent symbolic memory regions? That's what SymbolicRegion is for. It is a `MemRegion` that has an associated symbol. Since the symbol is unique and has a unique name; that symbol names the region.

Let's see how the analyzer processes the expressions in the following example:

      int foo(int x) {
         int y = x * 2;
         int z = x;
         ...
      }

Let's look at how `x*2` gets evaluated. When `x` is evaluated, we first construct an `SVal` that represents the lvalue of `x`, in this case it is an `SVal` that references the `MemRegion` for `x`. Afterwards, when we do the lvalue-to-rvalue conversion, we get a new `SVal`, which references the value currently bound to `x`. That value is symbolic; it's whatever `x` was bound to at the start of the function. Let's call that symbol `$0`. Similarly, we evaluate the expression for `2`, and get an `SVal` that references the concrete number `2`. When we evaluate `x*2`, we take the two `SVals` of the subexpressions, and create a new `SVal` that represents their multiplication (which in this case is a new symbolic expression, which we might call `$1`). When we evaluate the assignment to `y`, we again compute its lvalue (a `MemRegion`), and then bind the `SVal` for the RHS (which references the symbolic value `$1`) to the `MemRegion` in the symbolic store.
The second line is similar. When we evaluate `x` again, we do the same dance, and create an `SVal` that references the symbol `$0`. Note, two `SVals` might reference the same underlying values.

To summarize, MemRegions are unique names for blocks of memory. Symbols are unique names for abstract symbolic values. Some MemRegions represents abstract symbolic chunks of memory, and thus are also based on symbols. SVals are just references to values, and can reference either MemRegions, Symbols, or concrete values (e.g., the number 1).

## Idea for a Checker

Here are several questions which you should consider when evaluating your checker idea:

- Can the check be effectively implemented without path-sensitive analysis? See AST Visitors.
- How high the false positive rate is going to be? Looking at the occurrences of the issue you want to write a checker for in the existing code bases might give you some ideas.
- How the current limitations of the analysis will effect the false alarm rate? Currently, the analyzer only reasons about one procedure at a time (no inter-procedural analysis). Also, it uses a simple range tracking based solver to model symbolic execution.
- Consult the Bugzilla database to get some ideas for new checkers and consider starting with improving/fixing bugs in the existing checkers.

## Checker Registration

All checker implementation files are located in `clang/lib/StaticAnalyzer/Checkers` folder. Follow the steps below to register a new checker with the analyzer.

1. Create a new checker implementation file, for example `./lib/StaticAnalyzer/Checkers/NewChecker.cpp`

       using namespace clang;
       using namespace ento;

       namespace {
       class NewChecker: public Checker< check::PreStmt<CallExpr> > {
       public:
         void checkPreStmt(const CallExpr *CE, CheckerContext &Ctx) const {}
       }
       }
       void ento::registerNewChecker(CheckerManager &mgr) {
         mgr.registerChecker<NewChecker>();
       }

2. Pick the package name for your checker and add the registration code to `./lib/StaticAnalyzer/Checkers/Checkers.td`. Note, all checkers should first be developed as experimental. Suppose our new checker performs security related checks, then we should add the following lines under `SecurityExperimental` package:

       let ParentPackage = SecurityExperimental in {
       ...
       def NewChecker : Checker<"NewChecker">,
         HelpText<"This text should give a short description of the checks performed.">,
         DescFile<"NewChecker.cpp">;
       ...
       } // end "security.experimental"

3. Make the source code file visible to CMake by adding it to `./lib/StaticAnalyzer/Checkers/CMakeLists.txt`.
4. Compile and see your checker in the list of available checkers by running:
   `$clang -cc1 -analyzer-checker-help`

## Checker Skeleton

There are two main decisions you need to make:

- Which events the checker should be tracking. See CheckerDocumentation for the list of available checker callbacks.
- What data you want to store as part of the checker-specific program state. Try to minimize the checker state as much as possible.

## Bug Reports

## AST Visitors

Some checks might not require path-sensitivity to be effective. Simple AST walk might be sufficient. If that is the case, consider implementing a Clang compiler warning. On the other hand, a check might not be acceptable as a compiler warning; for example, because of a relatively high false positive rate. In this situation, AST callbacks `checkASTDecl` and `checkASTCodeBody` are your best friends.

## Testing

Every patch should be well tested with Clang regression tests. The checker tests live in `clang/test/Analysis` folder. To run all of the analyzer tests, execute the following from the `clang` build directory:

        $ TESTDIRS=Analysis make test

## Useful Commands/Debugging Hints

- While investigating a checker-related issue, instruct the analyzer to only execute a single checker:
  `$ clang -cc1 -analyze -analyzer-checker=osx.KeychainAPI test.c`
- To dump AST:
  `$ clang -cc1 -ast-dump test.c`
- To view/dump CFG use `debug.ViewCFG` or `debug.DumpCFG` checkers:
  `$ clang -cc1 -analyze -analyzer-checker=debug.ViewCFG test.c`
- To see all available debug checkers:
  `$ clang -cc1 -analyzer-checker-help | grep "debug"`
- To see which function is failing while processing a large file use `-analyzer-display-progress` option.
- While debugging execute `clang -cc1 -analyze -analyzer-checker=core` instead of `clang --analyze`, as the later would call the compiler in a separate process.
- To view `ExplodedGraph` (the state graph explored by the analyzer) while debugging, goto a frame that has `clang::ento::ExprEngine` object and execute:
  `(gdb) p ViewGraph(0)`
- To see the `ProgramState` while debugging use the following command.
  `(gdb) p State->dump()`
- To see `clang::Expr` while debugging use the following command. If you pass in a SourceManager object, it will also dump the corresponding line in the source code.
  `(gdb) p E->dump()`
- To dump AST of a method that the current `ExplodedNode` belongs to:
  `(gdb) p C.getPredecessor()->getCodeDecl().getBody()->dump() (gdb) p C.getPredecessor()->getCodeDecl().getBody()->dump(getContext().getSourceManager())`