Doop - Framework for Java Pointer and Taint Analysis (using P/Taint)
This document contains instructions for invoking the main driver of Doop. For an introduction to Datalog, please consult Datalog-101. For a more detailed tutorial on using the results of Doop analyses, please consult Doop-101. For an introduction to pointer analysis using Datalog, you can read a research-level tutorial. For information about Taint Analysis using Doop, please consult our P/Taint paper, or P/Taint tutorial.
At its core, Doop is a collection of various analyses expressed in the form of Datalog rules. The framework has two versions of its rules: one for Soufflé, an open-source Datalog engine for program analysis (which is the default engine used), and another for LogiQL, a Datalog dialect developed by LogicBlox. In order to install an up-to-date version of Soufflé, the best practice is to clone the development Github repo and follow the instructions found on this page. For a LogicBlox engine, you can use PA-Datalog, a port available for academic use, by following the instructions found on this page.
For trouble-free configuration:
DOOP_PLATFORMS_LIBenvironment variable could point to your PLATFORM lib directory (optional, see below).
DOOP_OUTenvironment variable could point to the output files directory (optional, defaults to
DOOP_CACHEenvironment variable could point to the cached facts directory (optional, defaults to
LOGICBLOX_HOMEenvironment variable should point to the
logicbloxdirectory of the engine, if you want to use LogicBlox.
Benchmarks & Platform Lib
For a variety of benchmarks, you could clone (or download) the doop-benchmarks repository.
One important directory in that repository is
JREs. It can be used for the
DOOP_PLATFORMS_LIB environment variable. It contains certain java library files for different JRE versions, necessary for analysis purposes. If you would like to provide a custom DOOP_PLATFORMS_LIB directory (e.g., to run analyses using different minor versions), you should follow the same file structure. For example, in order to analyze with JRE version 1.6, you need a
jre1.6 directory containing at least
rt.jar. In order to run an an analysis on an android apk ideally you could create a link to your android sdk installation. The currently supported structure is Android/Sdk/.
Doop only supports invocations from its home directory. The main options when running Doop are the analysis and the jar(s) options. For example, for a context-insensitive analysis on a jar file we issue:
$ ./doop --platform java_7 -a context-insensitive -i com.example.some.jar
Common command line options
To see the list of available options (and valid argument values in certain cases), issue:
$ ./doop -h
The options will be also shown if you run Doop without any arguments.
The major command line options are the following:
Analysis (-a, --analysis)
Mandatory. The name of the analysis to run.
$ ./doop -a context-insensitive
Input files (-i, --inputs)
Mandatory. The input file(s) to analyse.
The inputs option accepts multiple values and/or can be repeated multiple times.
The value of the input file can be specified in the following manners:
- provide the relative or absolute path to a local input file.
- provide the URL of a remote input file.
- provide the relative or absolute path to a local directory and all its *.jar files will be included.
- provide a maven-style expression to indicate a Jar file from the Maven central repository.
$ ./doop -i ./lib/asm-debug-all-4.1.jar [local file] -i org.apache.ivy:ivy:2.3.0 [maven descriptor] -i ./lib [local directory] -i http://www.example.com/some.jar [remote file] -i one.jar other.jar [multiple files separated with a space]
Optional --- default: java_7. The platform to use for the analysis. The possible Java options are java_N where N is the java version (3, 4, 5, 6, 7 etc.). Java 8 is currently not supported. The android options are android_N_V where N is the Android version (20, 21, 22, 23, 24, 25 etc.) and V is the variant ("stubs" for the Android SDK libraries or "fulljars" for custom built platforms).
$ ./doop -a context-insensitive -i com.example.some.jar --platform java_4 $ ./doop -a context-insensitive -i some-app.apk --platform android_24
Main class (--main)
The main class to use as the entry point. This class must declare a method with signature
public static void main(String ). If not specified, Doop will try to infer this information from the manifest file of the provided jar file(s).
$ ./doop -a context-insensitive -i com.example.some.jar --main com.example.some.Main
Timeout (-t, --timeout)
Specify the analysis execution timeout in minutes.
$ ./doop -a context-insensitive -i com.example.some.jar -t 120
The above analysis will run for a maximum of 2 hours (120 minutes).
Analysis id (-id, --identifier)
The identifier of the analysis.
If the identifier is not specified, Doop will generate one automatically. Use this option if you prefer to provide a human-friendly identifier to your analysis.
$ ./doop -id myAnalysis
The Java packages to treat as application code (not library code), to be exhaustively analyzed.
$ ./doop --regex com.example.package1.*:com.example.package2.*
Properties file (-p, --properties)
You can specify the options of the analysis in a properties file and use the
to process this file, as follows:
$ ./doop -p /path/to/file.properties
You can also override the options from a properties file with options from the command line. For example:
$ ./doop -p /path/to/file.properties -a context-insensitive --platform java_6
Soufflé supports multithreading so you can select the number of threads the analysis will run on by providing the --souffle-jobs argument to doop. For example:
$ ./doop -i ../doop-benchmarks/dacapo-2006/antlr.jar -a context-insensitive --platform java_7 --dacapo --id souffle-antlr --souffle-jobs 12
You can then inspect the analysis results by using the souffle-profile command and providing the profile.txt file produced by Souffle under the output directory of the analysis. In order to inspect the profile.txt of the above doop invocation with --souffle you would use the following command:
$ souffle-profile out/context-insensitive/souffle-antlr/profile.txt
Using LogicBlox as the Datalog engine of choice
In order to use LogicBlox instead of the Soufflé engine you can provide the --lb argument.
$ ./doop -i ../doop-benchmarks/dacapo-2006/antlr.jar -a context-insensitive --platform java_7 --dacapo --id lb-antlr --lb
Running Doop in offline mode
Normally, on each invocation of Doop the underlying build system will check for newer versions of all dependency libraries. Sometimes, it might be desirable to invoke doop in an offline mode. There is an alternative script for this purpose.
$ ./doopOffline --platform java_7 -a context-insensitive -i com.example.some.jar
Building Doop distribution
Optionally, Doop can be built as a binary distribution with the following command:
$ ./gradlew distZip # or distTar
The resulting distribution archive can be found under build/distributions and can be decompressed to a directory. Doop is invoked in that directory with "./bin/doop" instead of "./doop", bypassing Gradle (and its dependency resolution) on each Doop run. This can help with dependency resolution issues due to network connectivity or to avoid Gradle overhead when running Doop in batch mode.
UPL (see LICENSE).
Development on Doop
doop command is a script for Gradle build tasks. If you want to see all available tasks (e.g., how to build stand-alone packages of Doop for offline use), try
./gradlew tasks. Generally, for development and integration instructions, please consult the Doop Developer Guide.