SPF-WCA is a tool for algorithmic complexity analysis based on symbolic execution. It uses history-based guidance policies that enable exploration at large input sizes (e.g., number of elements to be sorted) of the target program.
To cite SPF-WCA, please use the most recent paper that was accepted at ICST 2017 (won the Best Paper Award):
Kasper Luckow, Rody Kersten, Corina Pasareanu, Symbolic Complexity Analysis using Context-preserving Histories, Proceedings of the 10th IEEE International Conference on Software Testing, Verification and Validation (ICST 2017), [pdf] [bibtex].
We provide two ways of installing SPF-WCA:
- Installation on local machine
- Virtual machine with Docker
Before continuing, make sure that jpf-core
and jpf-symbc
are installed.
To install SPF-WCA, update your site.properties
file (usually ~/.jpf/site.properties
) and set the spf-wca
variable to point to the directory of your SPF-WCA installation.
spf-wca=/path/to/spf-wca
Don't add spf-wca
to the extensions
variable.
Make sure you have Ivy
installed on your system. To bootstrap the Ivy ant task, you can run:
$ ant bootstrap
Then, obtain all the dependencies by running:
$ ant resolve
The dependencies will be downloaded to lib/
.
Now SPF-WCA can be built by simply running:
$ ant build
Assuming you have Docker installed, simply run:
$ docker build -t spf-wca .
# Will take some time to build the image...
$ docker run -it spf-wca
Note that, because there is no X11 available, the fitting functions cannot be displayed. However, the results can be checked in the CSV file under verbose/heuristics
in the results folder set by JPF option symbolic.worstcase.outputpath
(see below for more details). To copy the results to the host machine from the Docker container, use:
# Note the container id (CID) from the following command (column CONTAINER ID)
$ docker ps
$ docker cp <CID>:/path/to/csv/file/in/container /destination/on/hostmachine
To get IntelliJ IDEA to work with the library takes a little bit of work. Make sure you first have the Oracle JDK 1.8 installed, and ensure you have already set up jpf-core and jpf-symbc.
- Open the spf-wca root directory in IntelliJ and allow it to finish indexing.
- Open the Project Structure dialog (CMD+; on a Mac).
- Click the Project tab on the left side. Set the Project SDK to be an Oracle JDK 1.8. (You may have to configure this on your own if it hasn't been done already.)
- Click the Modules tab on the left side, then click the Sources tab in the middle.
- Click Add Content Root and locate your jpf-core root directory on your computer. Add it.
- Click Add Content Root and locate your jpf-symbc root directory on your computer. Add it.
- Click the Libraries tab on the left. Click the plus button to add a new library. Find the spf-wca root
directory, then the spf-wca/lib/ directory. Select all of the
.jar
files in the directory and add them. - Click OK.
IntelliJ should now re-index the project. I'd recommend opening some of the source files to ensure all the dependency libraries have been successfully added.
The Java PathFinder shell wcanalysis.WorstCaseAnalyzer
can be used to set up Phase 1 (policy generation) and Phase 2 (guided search) of the analysis.
The analysis can be performed by executing the JPF config file that specifies the parameters of the analysis, the constraint solver, the entry point of the system under analysis etc:
$ ./jpf-core/bin/jpf <path-to-jpf-file>
This will generate a results folder according to the option symbolic.worstcase.outputpath
(see below).
In the results folder, a subfolder verbose/heuristic/
will be generated that contains the constraints found for the analyzed input size. In addition a csv file is produced which summarizes all the results.
Note that consecutive runs of the analysis will produced and new data set that is appended to this file.
The csv file includes various statistics:
- inputSize Current input size to the SUT. It assumes this information is available in the jpf file as the value of the
target.args
property (it is for the examples in benchmarks.heuristic) - wcInstrExec Shows how many instructions were executed on the worst case path
- cfgInputSize Specifies which input size was used for generating the annotated CFG used for the heuristic. This will by default not be added to the .csv file
- analysisTime The analysis time when using the heuristic
- mem The peak memory consumption during heuristic-based exploration
- depth The maximum depth recorded (which constitutes the worst case path)
- paths Number of paths explored with the search heuristic
- resolvedChoicesNum How many decisions that were resolved as a consequence of using the heuristic
- unresolvedChoicesNum How many decisions that could not be resolved by the heuristic
- newChoicesNum New decisions encountered during exploration for which the heuristic has no information
- wcConstraint The constraint recorded for the worst case path. Any solution to this provides test inputs that are guaranteed to exercise worst case behavior of the SUT
In addition, data points <inputSize, depth> (here depth is the notion of worst case for a path) are generated, and the shell will automatically generate a plot showing the raw data, and the various fitted functions based on regression analysis. The user can zoom in on the graph by highlighting a region.
The following must be supplied in jpf file (or imported from another jpf file using the @include
directive):
@using spf-wca
shell=wcanalysis.WorstCaseAnalyzer
classpath=${spf-wca}/build/examples
target=fully.qualified.name.of.target.class
symbolic.worstcase.policy.inputsize=XXX
symbolic.worstcase.input.max=YYY
symbolic.wc.policy.history.size=ZZZ
The classpath
variable should be updated according to the system under test. target
denotes the entry point of the system under test.
Replace XXX
with the input size at which the policy should be obtained. This corresponds to phase 1. Replace YYY
with the maximum input size at which the heuristic search (phase 2) should be run. The heuristic search will run from input size 1-YYY
.
symbolic.wc.policy.history.size
is important because it controls whether the guidance policy produced in phase 1 is memoryless or history-based. By setting this variable to 0, a memoryless policy is used; otherwise, a history with the specified size ZZZ
will be used.
In addition, the user can optionally use the following for the WorstCaseAnalyzer
shell:
-
symbolic.heuristic.measuredmethods=<method desc(s)>
A list (separated by semicolons) that specifies from which method(s), the value for the worst case path should start counting. Default is the value ofsymbolic.method
i.e. the "symbolic target method". -
symbolic.worstcase.verbose=<true | false>
This will generate verbose output e.g. analysis statistics. -
symbolic.worstcase.outputpath=<path>
This will output the constraints for each worst case path and in addition summarize analysis statistics in a csv file. See above. -
symbolic.worstcase.req.maxinputsize=<Number>
Plot the budget input size from the requirement -
symbolic.worstcase.req.maxres=<Number>
Plot the budget max resource size from the requirement -
symbolic.worstcase.predictionmodel.size=<Number>
The maximum plotted domain of the fitting functions. -
symbolic.worstcase.reusepolicy=<true | false>
By setting this to true, a computed policy will be reused if it has been previously computed.
SPF-WCA is Copyright (c) 2017, The ISSTAC Authors and is released under the MIT License. See
the LICENSE
file in the root of this project and the headers of the individual files in the
src/
folder for the details.
SPF-WCA uses benchmarks from the WISE project by Jacob Burnim, Sudeep Juvekar, Koushik Sen. The benchmarks are available here WISE-1.0.tar.gz.
WISE is Copyright (c) 2011, Regents of the University of California,
and is released under an open-source BSD-style license. See the
individual source files under src/examples/wise
for details. A copy of the README
file of
WISE that includes license details can be found in the file licenses/README.WISE
.
Benchmark code in src/examples/wise/*/*.java
is based on the code obtained from the WISE
project. It is
Copyright (c) 2011, Regents of the University of California, and is
released under an open-source BSD-style license.
We repeat here the license details from the README
file (with file paths adjusted) in the WISE
distribution from above:
The code in
src/examples/wise/rbtree/
for red-black trees is by Tuomo Saarni, obtained from:http://users.utu.fi/~tuiisa/Java/index.html
under the following license:
Here's some java sources I've made. Most codes are free to download. If you use some of my sources just remember give me the credits.
The code in src/examples/wise/java15/{util,lang}/ is originally from the Oracle Java (TM) 2 Platform Standard Edition Development Kit 5.0 Update 22, obtained and redistributed under the Java Research License v1.5 -- please see
licenses/JavaResearchLicense.txt
for details. Use and distribution of this technology is subject to the Java Research License included herein.
In addition, SPF-WCA relies on several other libraries:
- Google Guava: Copyright (c) The Guava Authors and is distributed under the Apache License,
Version 2.0. The license for Google Guava can be found in the file
licenses/COPYING.GUAVA
. - Apache Commons Math3, which is distributed under the Apache License, Version 2.0. A copy of the
license can be found in the file
licenses/LICENSE.COMMONS_MATH3
. TheNOTICE
file of Apache Commons Math3 can be found in the filelicenses/NOTICE.COMMONS_MATH3
. - Apache Commons CSV, which is distributed under the Apache License, Version 2.0. A copy of the
license can be found in the file
licenses/LICENSE.COMMONS_CSV
. TheNOTICE
file of Apache Commons CSV can be found in the filelicenses/NOTICE.COMMONS_CSV
. - Apache Commons CLI, which is distributed under the Apache License, Version 2.0. A copy of the
license can be found in the file
licenses/LICENSE.COMMONS_CLI
. TheNOTICE
file of Apache Commons CLI can be found in the filelicenses/NOTICE.COMMONS_CLI
. - Apache Commons Lang, which is distributed under the Apache License, Version 2.0. A copy of the
license can be found in the file
licenses/LICENSE.COMMONS_LANG
. TheNOTICE
file of Apache Commons LANG can be found in the filelicenses/NOTICE.COMMONS_LANG
. - JFreeChart, which is distributed under the GNU Lesser General Public License (LGPL) Version 2.1.
A copy of the license can be found in the file
licenses/LICENSE.JFREECHART
.