Merge pull request #519 from secure-software-engineering/feature/statisticExport

Feature/statistic export

Author: janniclas

.docker/Dockerfile.devenv

@@ -0,0 +1,19 @@
+FROM ubuntu:22.04
+
+RUN apt -y update && apt -y upgrade && apt install bash  -y
+RUN DEBIAN_FRONTEND=noninteractive apt -y install wget gpg software-properties-common lsb-release git make python3 python3-pip vim -y
+RUN apt -y update && apt -y install cmake clang-14 ninja-build sudo
+
+RUN pip install pre-commit
+
+RUN set -exu; \
+    useradd -p test -s /bin/bash -m vscode; \
+    groupadd docker; \
+    usermod -aG docker vscode; \
+    usermod -aG sudo vscode;
+
+USER vscode
+
+ENV CC "/usr/bin/clang-14"
+ENV CXX "/usr/bin/clang++-14"
+ENV CMAKE_GENERATOR "Ninja"

.docker/config.json

@@ -0,0 +1,3 @@
+{
+  "dockerfile": "Dockerfile.devenv"
+}

Brewfile

@@ -73,31 +73,9 @@ Done!
 
 
 ### Installing PhASAR a MacOS system
-Mac OS 10.13.1 or higher only!
-To install the framework on a Mac we will rely on Homebrew. (https://brew.sh/)
-
-Please follow the instructions down below.
-
-```
-$ brew install boost
-$ brew install python3
-# Install llvm version 10
-$ brew install llvm
-# Setting the paths
-# Use LLVM's Clang rather than Apple's Clang compiler
-$ export CC=/usr/local/opt/llvm/bin/clang
-$ export CXX=/usr/local/opt/llvm/bin/clang++
-# Set PATH env variable to /usr/local/opt/llvm/bin
-# Go to PhASAR directory run the following commands
-$ git submodule init
-$ git submodule update
-$ mkdir build
-$ cd build/
-$ cmake -DCMAKE_BUILD_TYPE=Release ..
-$ make -j $(nproc) # or use a different number of cores to compile it
-$ sudo make install # if you wish a system-wise installation
-```
-
+Due to unfortunate updates to MacOS and the handling of C++, especially on the newer M1 processors, we can't support native development on Mac.
+The easiest solution to develop PhASAR on a Mac right now is to use [dockers development environments](https://docs.docker.com/desktop/dev-environments/). Clone this repository as described in their documentation. Afterwards, you have to login once manually, as a root user by running `docker exec -it -u root <container name> /bin/bash` to complete the rest of the install process as described in this readme (install submodules, run bootstrap.sh, ...).
+Now you can just attach your docker container to VS Code or any other IDE, which supports remote development.
 
 ### Compiling PhASAR (if not already done using the installation scripts)
 Set the system's variables for the C and C++ compiler to clang:

README.md

@@ -49,6 +49,7 @@ enum class AnalysisControllerEmitterOptions : uint32_t {
   EmitPTAAsText = (1 << 11),
   EmitPTAAsDot = (1 << 12),
   EmitPTAAsJson = (1 << 13),
+  EmitStatisticAsJson = (1 << 14),
 };
 
 class AnalysisController {

include/phasar/Controller/AnalysisController.h

@@ -21,6 +21,7 @@
 #include "llvm/IR/PassManager.h"
 #include "llvm/Passes/PassBuilder.h"
 
+#include "nlohmann/json.hpp"
 #include "phasar/Utils/EnumFlags.h"
 
 namespace llvm {
@@ -60,6 +61,8 @@ class ProjectIRDB {
   std::map<std::string, std::unique_ptr<llvm::Module>> Modules;
   // Maps an id to its corresponding instruction
   std::map<std::size_t, llvm::Instruction *> IDInstructionMapping;
+  size_t NumberCallsites;
+  nlohmann::json StatsJson;
 
   void buildIDModuleMapping(llvm::Module *M);
 
@@ -171,12 +174,18 @@ class ProjectIRDB {
     return IDInstructionMapping.size();
   }
 
+  [[nodiscard]] inline std::size_t getNumCallsites() const {
+    return NumberCallsites;
+  }
+
   [[nodiscard]] std::size_t getNumGlobals() const;
 
   [[nodiscard]] llvm::Instruction *getInstruction(std::size_t Id) const;
 
   [[nodiscard]] static std::size_t getInstructionID(const llvm::Instruction *I);
 
+  void printAsJson(llvm::raw_ostream &OS = llvm::outs()) const;
+
   void print() const;
 
   void emitPreprocessedIR(llvm::raw_ostream &OS = llvm::outs(),

include/phasar/DB/ProjectIRDB.h

@@ -19,6 +19,7 @@
 
 #include <set>
 
+#include "nlohmann/json.hpp"
 #include "llvm/IR/PassManager.h"
 
 namespace llvm {
@@ -115,6 +116,7 @@ class GeneralStatistics {
    */
   [[nodiscard]] std::set<const llvm::Instruction *>
   getRetResInstructions() const;
+  [[nodiscard]] nlohmann::json getAsJson() const;
 };
 
 /**

include/phasar/PhasarLLVM/Passes/GeneralStatisticsAnalysis.h

@@ -272,6 +272,16 @@ void AnalysisController::emitRequestedHelperAnalysisResults() {
       ICF.printAsJson();
     }
   }
+
+  if (EmitterOptions & AnalysisControllerEmitterOptions::EmitStatisticAsJson) {
+    if (!ResultDirectory.empty()) {
+      if (auto OFS = openFileStream("/psr-IrStatistic.json")) {
+        IRDB.printAsJson(*OFS);
+      }
+    } else {
+      IRDB.printAsJson();
+    }
+  }
 }
 
 std::unique_ptr<llvm::raw_fd_ostream>

lib/Controller/AnalysisController.cpp

@@ -126,6 +126,8 @@ void ProjectIRDB::preprocessModule(llvm::Module *M) {
   MPM.run(*M, MAM);
   // retrieve data from the GeneralStatisticsAnalysis registered earlier
   auto GSPResult = MAM.getResult<GeneralStatisticsAnalysis>(*M);
+  StatsJson = GSPResult.getAsJson();
+  NumberCallsites = GSPResult.getFunctioncalls();
   auto Allocas = GSPResult.getAllocaInstructions();
   AllocaInstructions.insert(Allocas.begin(), Allocas.end());
   auto ATypes = GSPResult.getAllocatedTypes();
@@ -266,6 +268,10 @@ void ProjectIRDB::print() const {
   }
 }
 
+void ProjectIRDB::printAsJson(llvm::raw_ostream &OS) const {
+  OS << StatsJson.dump(4) << '\n';
+}
+
 void ProjectIRDB::emitPreprocessedIR(llvm::raw_ostream &OS,
                                      bool ShortenIR) const {
   for (const auto &[File, Module] : Modules) {

lib/DB/ProjectIRDB.cpp

@@ -216,4 +216,14 @@ GeneralStatistics::getRetResInstructions() const {
   return RetResInstructions;
 }
 
+nlohmann::json GeneralStatistics::getAsJson() const {
+  nlohmann::json J;
+  J["Instructions"] = getInstructions();
+  J["Functions"] = Functions;
+  J["Alloca Instructions"] = AllocaInstructions.size();
+  J["Call Sites"] = CallSites;
+  J["Global Variables"] = Globals;
+  return J;
+}
+
 } // namespace psr