Picire

Parallel Delta Debugging Framework

Picire (pronounced as /pitsirE/) is a Python implementation of the Delta Debugging algorithm supporting parallelization and further configuration options. It can be used either as a command line tool or as a library.

Just like the original algorithm, Picire automatically reduces "interesting" tests while keeping their "interesting" behaviour. A common use case is minimizing failing tests so that they still reproduce the original failure.

The tool (and the algorithm) works iteratively. As a first step, it splits up the input into n chunks either by lines or characters. Then, iteratively, it inspects smaller test cases composed of these chunks whether they are still interesting. The selection of chunks can happen two ways: either a small subset of the chunks is kept (subset-based reduce), or that small subset is removed and everything else is kept (complement-based reduce). If a new interesting test case is found, it becomes the input of the next iteration. The iterations stop if removing any further chunks would make the test uninteresting (e.g. the test is 1-minimal).

Requirements

• Python >= 3.6

Install

To use Picire in another project, it can be added to setup.cfg as an install requirement (if using setuptools with declarative config):

[options]
install_requires =
    picire

To install Picire manually, e.g., into a virtual environment, use pip:

pip install picire

The above approaches install the latest release of Picire from PyPI. Alternatively, for the development version, clone the project and perform a local install:

pip install .

Usage

Picire has two mandatory command line arguments: one that defines the input test case to be reduced (--input) and another describing an executable tester script or program (--test) that can decide about the interestingness of an arbitrary input. This will be run in every iteration to check a test case.

Common settings

• --parallel: Enables Picire to run in multiprocess mode. (Otherwise, the original single-process variant will run.)
• -j <num>: Defines the maximum number of parallel jobs.
• --combine-loops: The base algorithm had a dependency between subset and complement-based reduce loops, but because of the sequential nature of its implementation, it had no effect on efficiency. However, in parallel mode, this separation becomes a potential sub-optimality. With this option, the two reduce loops run combined for additional performance. Further details about the algorithm variants are available in the cited papers.
• --complement-first: For some input types, subset-based reduce is not as effective as the complement-based one (sometimes, aggressively removing too big parts of the input eliminates the interestingness as well). By default, Picire performs subset-based reduce before complement-based reduce, which can result in many superfluous checks for such inputs. This flag forces to start with complement checks.
• --subset-iterator / --complement-iterator: Guide the iteration strategies of the subset and complement-based reduce loops.
  • forward: Start investigating subsets (or complements) from the beginning of the input.
  • backward: Start investigating subsets (or complements) from the end of the input. The goal is to reduce the number of semantic violations (assuming that definitions - like variable declarations - appear before uses).
  • skip: Completely avoids the subset or complement checks (mostly used with --subset-iterator).

For the detailed options, see picire --help.

Tester script

The tester script is expected to take one command line argument, the path of a test case, and it has to exit with 0 if the test is interesting and with non-zero otherwise. An example tester script that runs an arbitrary target application and checks if it fails on an assertion might look like the one below:

#! /bin/bash
timeout --foreground 10 <path/to/the/target/application> $1 2>&1 | grep -q "Assertion failed";

Remarks:

• The <path/to/the/target/application> should either be an absolute path to the target application or the application should be on the search path (i.e., $PATH).
• $1 is the single and mandatory command line argument containing the path of a test case.
• If the target application is not guaranteed to exit, then it's worth running it with timeout to limit the amount of time waiting for producing the expected behaviour.
• If the target is run with timeout then the --foreground flag can also be useful as it allows forwarding the KILL signals (used by the parallel implementation) through the timeout's process group. This enables us to stop all alive parallel processes when a new interesting configuration is found already.
• If the interestingness decision is based on the content of the output then using grep (perhaps with -q or --quiet) might be a right choice, since it returns 0 if the pattern was found and 1 if not. Exactly the return value Picire expects.

A common form of Picire's usage:

picire --input=<path/to/the/input> --test=<path/to/the/tester> \
       --parallel --subset-iterator=skip --complement-iterator=backward

Compatibility

Picire was tested on:

• Linux (Ubuntu 14.04 / 16.04 / 18.04 / 20.04)
• OS X / macOS (10.11 / 10.12 / 10.13 / 10.14 / 10.15 / 11)
• Windows (Server 2012 R2 / Server version 1809 / Windows 10)

Acknowledgement and Citations

This software uses the delta debugging algorithm as described in:

• Andreas Zeller. Yesterday, My Program Worked. Today, It Does Not. Why? In Proceedings of the 7th European Software Engineering Conference Held Jointly with the 7th ACM SIGSOFT Symposium on the Foundations of Software Engineering (ESEC/FSE '99), volume 1687 of Lecture Notes in Computer Science (LNCS), pages 253-267, Toulouse, France, September 1999. Springer. https://doi.org/10.1007/3-540-48166-4_16
• Ralf Hildebrandt and Andreas Zeller. Simplifying Failure-Inducing Input. In Proceedings of the 2000 ACM SIGSOFT International Symposium on Software Testing and Analysis (ISSTA '00), pages 135-145, Portland, Oregon, USA, August 2000. ACM. https://doi.org/10.1145/347324.348938

Further improvements are described in:

• Renata Hodovan and Akos Kiss. Practical Improvements to the Minimizing Delta Debugging Algorithm. In Proceedings of the 11th International Joint Conference on Software Technologies (ICSOFT 2016) - Volume 1: ICSOFT-EA, pages 241-248, Lisbon, Portugal, July 2016. SciTePress. https://doi.org/10.5220/0005988602410248
• Renata Hodovan, Akos Kiss, and Tibor Gyimothy. Tree Preprocessing and Test Outcome Caching for Efficient Hierarchical Delta Debugging. In Proceedings of the 12th IEEE/ACM International Workshop on Automation of Software Testing (AST 2017), pages 23-29, Buenos Aires, Argentina, May 2017. IEEE. https://doi.org/10.1109/AST.2017.4
• Akos Kiss. Generalizing the Split Factor of the Minimizing Delta Debugging Algorithm. IEEE Access, 8:219837-219846, December 2020. IEEE. https://doi.org/10.1109/ACCESS.2020.3043027

Copyright and Licensing

Licensed under the BSD 3-Clause License.