loggrad's Introduction

LogGrad

Quantitative Assessment of Log Quality in Large-Scale Software.

Introduction

LogGrad is a light weight log-quality assessment tool, which is based on Clang. Given a set of projects, LogGrad can automatically rank them by log quality. The basic idea of ranking is that to what extent the given project misses logs. The missing logs are classified into 3 types, including project-specific logs, intra-domain important logs and inter-domain important logs.

Usage

Compile

Change directory to Clang tools directory.

cd path/to/llvm-source-tree/tools/clang/tools

Download source code.

git clone https://github.com/ZhouyangJia/LogGrad.git

Add add_subdirectory(LogGrad) to CMakeList.txt.

echo "add_subdirectory(LogGrad)" >> CMakeLists.txt

Recompile Clang and try following command to test.

ls path/to/llvm-build/Release/bin/clang-loggrad

Analyze log information

Generate compile_commands.json. More information about compile_commands.json.

cd test/
tar zxvf bftpd-3.2.tar
cd bftpd/
./configure
bear make

Generate compiled_files.def, This file has all names of compiled source files.

../../script/extract_command.pl compile_commands.json

Generate function_rule_model.out. Each line includes a 3-tuple, namely function name, called time and logged time.

cat compiled_files.def | xargs clang-loggrad -log-grade

Rename the output file. Other output files are in script/results.

mv function_rule_model.out bftpd.out

Assessment

Each output file represents one project followed by a domain name.

cd ../../script/
python loggrad.py results/httpd.out httpd results/nginx.out httpd results/lighttpd.out httpd results/mongrel2.out httpd results/mysql.out database results/postgresql.out database results/berkeleydb.out database results/monetdb.out database

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