ZIP Code business counts data for Maptitude mapping software are from Caliper Corporation and contain aggregated ZIP Code Business Patterns (ZBP) data and Rural-Urban Commuting Area (RUCA) data.

Business location data for Maptitude mapping software are from Caliper Corporation and contain point locations for businesses.

US Postal Service Zone Improvement Plan (ZIP) Codes are used throughout the United States to improve mail delivery. There are 479 unique 5-digit ZIP Codes in Oregon all starting with 97. All ZIP Codes are assigned and managed exclusively by the US Postal Service. There are three main categories of ZIP Codes - 1) Standard, 2) PO Box Only, 3) Unique for large commercial and government customers.Each ZIP Code is assigned a preferred city name by the US Postal Service. NOTE - these city names may not correspond with the city limits or other jurisdiction boundaries of incorporated cities. There are other acceptable city names listed that may be used for mailing addresses for some ZIP Codes. There are also other city names to avoid using for mailing addresses. To verify the preferred, acceptable, or city names to avoid enter the ZIP Code in this tool from the US Postal Service - https://tools.usps.com/zip-code-lookup.htm?citybyzipcodeThis is not a product of the US Postal Service. It was compiled by checking all numbers from 97000 - 97999 with the ZIP Code Lookup tool.Most Standard and some PO Box Only ZIP Codes may also be listed as Census ZIP Code Tabulation Areas (ZTCA). NOTE - The ZTCA is only an approximation of a ZIP Code area based on the predominate ZIP Code of all housing units in each Census block. ZIP Codes actually follow lines of travel along letter carrier routes and are not polygons as shown by the ZTCA.

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Address ranges describe a label given to a unique collection of addresses that fall along a road or path. Address ranges provide a way of locating homes and businesses based on their street addresses when no other location information is available.Using a house number, street name, street side and ZIP code, address ranges can locate the address to the geographic area associated to that side of the street. Once geocoded, the U.S. Census Bureau can assign the address to a field assignment area or tabulate the data for that address. In addition, academics, researchers, professionals and government agencies outside of the Census Bureau use MAF/TIGER address ranges to transform tabular addresses into geographical datasets for decision-making and analytical purposes.Address ranges must be unique to geocode addresses to the correct location and avoid geocoding conflicts. Multiple elements in MAF/TIGER are required to make an address range unique including street names, address house numbers and street feature geometries, such as street centerlines. The address range data model is designed to maximize geocoding matches with their correct geographic areas in MAF/TIGER by allowing an unlimited number of address range-to-street feature relationships.The Census Bureau’s Geography Division devises numerous operations and processes to build and maintain high quality address ranges so that:Address ranges accurately describe the location of addresses on the ground.Address All possible city-style addresses are geocoded.Address ranges can handle all known address and street name variations.Address ranges conform with current U.S. Postal Service ZIP codes.Address ranges are reliable and free from conflicts.Automated software continually updates existing address ranges, builds new address ranges and corrects errors. An automated operation links address location points and tabular address information to street feature edges with matching street names in the same block to build and modify address ranges.Many business rules and legal value checks ensure quality address range data in MAF/TIGER. For example, business rules prevent adding or modifying address ranges that overlap another house number range with the same street name and ZIP code. Legal value checks verify that address ranges include mandatory attribute information, valid data types and valid character values.Some of the TIGER/Line products for the public include address ranges and give the public the ability to geocode addresses to MAF/TIGER address ranges for the user’s own purpose. The address range files are available for the nation, Puerto Rico and the U.S. Island Areas at the county level. TIGER/Line files require geographic information system (GIS) software to use.The Census Bureau Geocoder Service is a web service provided to the public. The service accepts up to 1,000 input addresses and, based on Census address ranges, returns the interpolated geocoded location and census geographies. Users can access the service a web interface or a representational state transfer (REST) application program interface (API) web service.Download: https://www2.census.gov/geo/tiger/TGRGDB24/tlgdb_2024_a_us_addr.gdb.zip

Competition Results

This file describes the contents of an archive of the 3rd Competition on Software Testing (Test-Comp 2021).
https://test-comp.sosy-lab.org/2021/

The competition was run by Dirk Beyer, LMU Munich, Germany.
More information is available in the following article:
Dirk Beyer. Status Report on Software Testing: Test-Comp 2021. In Proceedings of the 24th International Conference on Fundamental Approaches to Software Engineering (FASE 2021, Luxembourg, March 27 - April 1), 2021. Springer.

Copyright (C) Dirk Beyer
https://www.sosy-lab.org/people/beyer/

SPDX-License-Identifier: CC-BY-4.0
https://spdx.org/licenses/CC-BY-4.0.html

To browse the competition results with a web browser, there are two options:

• start a local web server using php -S localhost:8000 in order to view the data in this archive, or
• browse https://test-comp.sosy-lab.org/2021/results/ in order to view the data on the Test-Comp web page.

Contents

• index.html: directs to the overview web page
• LICENSE.txt: specifies the license
• README.txt: this file
• results-validated/: results of validation runs
• results-verified/: results of test-generation runs and aggregated results

The folder results-validated/ contains the results from validation runs:

• *.xml.bz2: XML results from BenchExec
• *.logfiles.zip: output from tools
• *.json.gz: mapping from files names to SHA 256 hashes for the file content

The folder results-verified/ contains the results from test-generation runs and aggregated results:

• index.html: overview web page with rankings and score table
• design.css: HTML style definitions
• *.xml.bz2: XML results from BenchExec
• *.merged.xml.bz2: XML results from BenchExec, status adjusted according to the validation results
• *.logfiles.zip: output from tools
• *.json.gz: mapping from files names to SHA 256 hashes for the file content
• *.xml.bz2.table.html: HTML views on the detailed results data as generated by BenchExec’s table generator
• *.All.table.html: HTML views of the full benchmark set (all categories) for each tool
• META_*.table.html: HTML views of the benchmark set for each meta category for each tool, and over all tools
• : HTML views of the benchmark set for each category over all tools

• iZeCa0gaey.html: HTML views per tool

• quantilePlot-*: score-based quantile plots as visualization of the results
• quantilePlotShow.gp: example Gnuplot script to generate a plot

• score*: accumulated score results in various formats

The hashes of the file names (in the files *.json.gz) are useful for

• validating the exact contents of a file and
• accessing the files from the witness store.

Other Archives

Overview over archives from Test-Comp 2021 that are available at Zenodo:

• https://doi.org/10.5281/zenodo.4459466 Witness store (containing the generated test suites)
• https://doi.org/10.5281/zenodo.4459470 Results (XML result files, log files, file mappings, HTML tables)
• https://doi.org/10.5281/zenodo.4459132 Test tasks, version testcomp21
• https://doi.org/10.5281/zenodo.4317433 BenchExec, version 3.6

All benchmarks were executed for Test-Comp 2021 https://test-comp.sosy-lab.org/2021/
by Dirk Beyer, LMU Munich, based on the following components:

• https://gitlab.com/sosy-lab/test-comp/archives-2021 testcomp21-0-gdacd4bf
• https://gitlab.com/sosy-lab/software/sv-benchmarks testcomp21-0-gefea738258
• https://gitlab.com/sosy-lab/software/benchexec 3.6-0-gb278ebbb
• https://gitlab.com/sosy-lab/benchmarking/competition-scripts testcomp21-0-g8339740
• https://gitlab.com/sosy-lab/test-comp/bench-defs testcomp21-0-g9d532c9

Contact

Feel free to contact me in case of questions: https://www.sosy-lab.org/people/beyer/

Test-Comp 2025

Competition Results

This file describes the contents of an archive of the 7th Competition on Software Testing (Test-Comp 2025). https://test-comp.sosy-lab.org/2025/

The competition was organized by Dirk Beyer, LMU Munich, Germany. More information is available in the following article: Dirk Beyer. Advances in Automatic Software Testing: Test-Comp 2025. In Proceedings of the 28th International Conference on Fundamental Approaches to Software Engineering (FASE 2025, Paris, May 3–8), 2025. Springer.

Copyright (C) 2025 Dirk Beyer https://www.sosy-lab.org/people/beyer/

SPDX-License-Identifier: CC-BY-4.0 https://spdx.org/licenses/CC-BY-4.0.html

To browse the competition results with a web browser, there are two options:

• start a local web server using php -S localhost:8000 in order to view the data in this archive, or
• browse https://test-comp.sosy-lab.org/2025/results/ in order to view the data on the Test-Comp web page.

Contents

• index.html: directs to the overview web page
• LICENSE-results.txt: specifies the license
• README-results.txt: this file
• results-validated/: results of validation runs
• results-verified/: results of test-generation runs and aggregated results

The folder results-validated/ contains the results from validation runs:

• *.results.txt: TXT results from BenchExec
• *.xml.bz2: XML results from BenchExec
• *.logfiles.zip: output from tools
• *.json.gz: mapping from files names to SHA 256 hashes for the file content

The folder results-verified/ contains the results from test-generation runs and aggregated results:

• index.html: overview web page with rankings and score table

• design.css: HTML style definitions

• *.results.txt: TXT results from BenchExec

• *.xml.bz2: XML results from BenchExec

• *.fixed.xml.bz2: XML results from BenchExec, status adjusted according to the validation results

• *.logfiles.zip: output from tools

• *.json.gz: mapping from files names to SHA 256 hashes for the file content

• *.xml.bz2.table.html: HTML views on the detailed results data as generated by BenchExec’s table generator

• : HTML views of the full benchmark set (all categories) for each tester

• META_*.table.html: HTML views of the benchmark set for each meta category for each tester, and over all testers

• : HTML views of the benchmark set for each category over all testers

• *.xml: XML table definitions for the above tables

• results-per-tool.php: List of results for each tool for review process in pre-run phase

• : List of results for a tool in HTML format with links

• quantilePlot-*: score-based quantile plots as visualization of the results

• quantilePlotShow.gp: example Gnuplot script to generate a plot

• score*: accumulated score results in various formats

The hashes of the file names (in the files *.json.gz) are useful for

• validating the exact contents of a file and
• accessing the files from the witness store.

Related Archives

Overview of archives from Test-Comp 2025 that are available at Zenodo:

• https://doi.org/10.5281/zenodo.15034431 Test Suites from Test-Comp 2025 Test-Generation Tools. Store of coverage witnesses (containing the generated test suites)
• https://doi.org/10.5281/zenodo.15055359 Testers and Validators: FM-Tools Data Set for Test-Comp 2025. Metadata snapshot of the evaluated tools (DOIs, options, etc.)
• https://doi.org/10.5281/zenodo.15034433 Results of the 7th Intl. Competition on Software Testing (Test-Comp 2025). Results (XML result files, log files, file mappings, HTML tables)
• https://doi.org/10.5281/zenodo.15034421 SV-Benchmarks: Benchmark Set of Test-Comp 2025. Test-generation tasks, version testcomp25
• https://doi.org/10.5281/zenodo.15007216 BenchExec, version 3.29. Benchmarking framework
• https://doi.org/10.5281/zenodo.11193690 CoVeriTeam, version 1.2.1. Remote execution and continuous integration of testers

All benchmarks were executed for Test-Comp 2025 https://test-comp.sosy-lab.org/2025/ by Dirk Beyer, LMU Munich, based on the following components:

• https://gitlab.com/sosy-lab/benchmarking/fm-tools 2.2
• https://gitlab.com/sosy-lab/benchmarking/sv-benchmarks testcomp25
• https://gitlab.com/sosy-lab/test-comp/bench-defs testcomp25
• https://gitlab.com/sosy-lab/software/benchexec 3.29
• https://gitlab.com/sosy-lab/software/benchcloud 1.3.0
• https://gitlab.com/sosy-lab/software/fm-weck 1.4.5
• https://gitlab.com/sosy-lab/benchmarking/competition-scripts testcomp25
• https://gitlab.com/sosy-lab/test-comp/test-format testcomp25
• https://gitlab.com/sosy-lab/software/coveriteam 1.2.1

Contact

Feel free to contact me in case of questions: https://www.sosy-lab.org/people/beyer/

Summary

Geojson files used to visualize geospatial layers relevant to identifying and assessing trucking fleet decarbonization opportunities with the MIT Climate & Sustainability Consortium's Geospatial Trucking Industry Decarbonization Explorer (Geo-TIDE) tool.

Relevant Links

Link to the online version of the tool (requires creation of a free user account).

Link to GitHub repo with source code to produce this dataset and deploy the Geo-TIDE tool locally.

Funding

This dataset was produced with support from the MIT Climate & Sustainability Consortium.

Original Data Sources

These geojson files draw from and synthesize a number of different datasets and tools. The original data sources and tools are described below:

Filename(s) Description of Original Data Source(s) Link(s) to Download Original Data License and Attribution for Original Data Source(s)

faf5_freight_flows/*.geojson

trucking_energy_demand.geojson

highway_assignment_links_*.geojson

infrastructure_pooling_thought_experiment/*.geojson

Regional and highway-level freight flow data obtained from the Freight Analysis Framework Version 5. Shapefiles for FAF5 region boundaries and highway links are obtained from the National Transportation Atlas Database. Emissions attributes are evaluated by incorporating data from the 2002 Vehicle Inventory and Use Survey and the GREET lifecycle emissions tool maintained by Argonne National Lab.

Shapefile for FAF5 Regions

Shapefile for FAF5 Highway Network Links

FAF5 2022 Origin-Destination Freight Flow database

FAF5 2022 Highway Assignment Results

Attribution for Shapefiles: United States Department of Transportation Bureau of Transportation Statistics National Transportation Atlas Database (NTAD). Available at: https://geodata.bts.gov/search?collection=Dataset.

License for Shapefiles: This NTAD dataset is a work of the United States government as defined in 17 U.S.C. § 101 and as such are not protected by any U.S. copyrights. This work is available for unrestricted public use.

Attribution for Origin-Destination Freight Flow database: National Transportation Research Center in the Oak Ridge National Laboratory with funding from the Bureau of Transportation Statistics and the Federal Highway Administration. Freight Analysis Framework Version 5: Origin-Destination Data. Available from: https://faf.ornl.gov/faf5/Default.aspx. Obtained on Aug 5, 2024. In the public domain.

Attribution for the 2022 Vehicle Inventory and Use Survey Data: United States Department of Transportation Bureau of Transportation Statistics. Vehicle Inventory and Use Survey (VIUS) 2002 [supporting datasets]. 2024. https://doi.org/10.21949/1506070

Attribution for the GREET tool (original publication): Argonne National Laboratory Energy Systems Division Center for Transportation Research. GREET Life-cycle Model. 2014. Available from this link.

Attribution for the GREET tool (2022 updates): Wang, Michael, et al. Summary of Expansions and Updates in GREET® 2022. United States. https://doi.org/10.2172/1891644

grid_emission_intensity/*.geojson

Emission intensity data is obtained from the eGRID database maintained by the United States Environmental Protection Agency.

eGRID subregion boundaries are obtained as a shapefile from the eGRID Mapping Files database.

eGRID database

Shapefile with eGRID subregion boundaries

Attribution for eGRID data: United States Environmental Protection Agency: eGRID with 2022 data. Available from https://www.epa.gov/egrid/download-data. In the public domain.

Attribution for shapefile: United States Environmental Protection Agency: eGRID Mapping Files. Available from https://www.epa.gov/egrid/egrid-mapping-files. In the public domain.

US_elec.geojson

US_hy.geojson

US_lng.geojson

US_cng.geojson

US_lpg.geojson

Locations of direct current fast chargers and refueling stations for alternative fuels along U.S. highways. Obtained directly from the Station Data for Alternative Fuel Corridors in the Alternative Fuels Data Center maintained by the United States Department of Energy Office of Energy Efficiency and Renewable Energy.

US_elec.geojson

US_hy.geojson

US_lng.geojson

US_cng.geojson

US_lpg.geojson

Attribution: U.S. Department of Energy, Energy Efficiency and Renewable Energy. Alternative Fueling Station Corridors. 2024. Available from: https://afdc.energy.gov/corridors. In the public domain.

These data and software code ("Data") are provided by the National Renewable Energy Laboratory ("NREL"), which is operated by the Alliance for Sustainable Energy, LLC ("Alliance"), for the U.S. Department of Energy ("DOE"), and may be used for any purpose whatsoever.

daily_grid_emission_profiles/*.geojson

Hourly emission intensity data obtained from ElectricityMaps.

Original data can be downloaded as csv files from the ElectricityMaps United States of America database

Shapefile with region boundaries used by ElectricityMaps

License: Open Database License (ODbL). Details here: https://www.electricitymaps.com/data-portal

Attribution for csv files: Electricity Maps (2024). United States of America 2022-23 Hourly Carbon Intensity Data (Version January 17, 2024). Electricity Maps Data Portal. https://www.electricitymaps.com/data-portal.

Attribution for shapefile with region boundaries: ElectricityMaps contributors (2024). electricitymaps-contrib (Version v1.155.0) [Computer software]. https://github.com/electricitymaps/electricitymaps-contrib.

gen_cap_2022_state_merged.geojson

trucking_energy_demand.geojson

Grid electricity generation and net summer power capacity data is obtained from the state-level electricity database maintained by the United States Energy Information Administration.

U.S. state boundaries obtained from this United States Department of the Interior U.S. Geological Survey ScienceBase-Catalog.

Annual electricity generation by state

Net summer capacity by state

Shapefile with U.S. state boundaries

Attribution for electricity generation and capacity data: U.S. Energy Information Administration (Aug 2024). Available from: https://www.eia.gov/electricity/data/state/. In the public domain.

electricity_rates_by_state_merged.geojson

Commercial electricity prices are obtained from the Electricity database maintained by the United States Energy Information Administration.

Electricity rate by state

Attribution: U.S. Energy Information Administration (Aug 2024). Available from: https://www.eia.gov/electricity/data.php. In the public domain.

demand_charges_merged.geojson

demand_charges_by_state.geojson

Maximum historical demand charges for each state and zip code are derived from a dataset compiled by the National Renewable Energy Laboratory in this this Data Catalog.

Historical demand charge dataset

The original dataset is compiled by the National Renewable Energy Laboratory (NREL), the U.S. Department of Energy (DOE), and the Alliance for Sustainable Energy, LLC ('Alliance').

Attribution: McLaren, Joyce, Pieter Gagnon, Daniel Zimny-Schmitt, Michael DeMinco, and Eric Wilson. 2017. 'Maximum demand charge rates for commercial and industrial electricity tariffs in the United States.' NREL Data Catalog. Golden, CO: National Renewable Energy Laboratory. Last updated: July 24, 2024. DOI: 10.7799/1392982.

eastcoast.geojson

midwest.geojson

la_i710.geojson

h2la.geojson

bayarea.geojson

saltlake.geojson

northeast.geojson

Highway corridors and regions targeted for heavy duty vehicle infrastructure projects are derived from a public announcement on February 15, 2023 by the United States Department of Energy.

The shapefile with Bay area boundaries is obtained from this Berkeley Library dataset.

The shapefile with Utah county boundaries is obtained from this dataset from the Utah Geospatial Resource Center.

Shapefile for Bay Area country boundaries

Shapefile for counties in Utah

Attribution for public announcement: United States Department of Energy. Biden-Harris Administration Announces Funding for Zero-Emission Medium- and Heavy-Duty Vehicle Corridors, Expansion of EV Charging in Underserved Communities (2023). Available from https://www.energy.gov/articles/biden-harris-administration-announces-funding-zero-emission-medium-and-heavy-duty-vehicle.

Attribution for Bay area boundaries: San Francisco (Calif.). Department Of Telecommunications and Information Services. Bay Area Counties. 2006. In the public domain.

Attribution for Utah boundaries: Utah Geospatial Resource Center & Lieutenant Governor's Office. Utah County Boundaries (2023). Available from https://gis.utah.gov/products/sgid/boundaries/county/.

License for Utah boundaries: Creative Commons 4.0 International License.

incentives_and_regulations/*.geojson

State-level incentives and regulations targeting heavy duty vehicles are collected from the State Laws and Incentives database maintained by the United States Department of Energy's Alternative Fuels Data Center.

Data was collected manually from the State Laws and Incentives database.

Attribution: U.S. Department of Energy, Energy Efficiency and Renewable Energy, Alternative Fuels Data Center. State Laws and Incentives. Accessed on Aug 5, 2024 from: https://afdc.energy.gov/laws/state. In the public domain.

These data and software code ("Data") are provided by the National Renewable Energy Laboratory ("NREL"), which is operated by the Alliance for Sustainable Energy, LLC ("Alliance"), for the U.S. Department of Energy ("DOE"), and may be used for any purpose whatsoever.

costs_and_emissions/*.geojson

diesel_price_by_state.geojson

trucking_energy_demand.geojson

Lifecycle costs and emissions of electric and diesel trucking are evaluated by adapting the model developed by Moreno Sader et al., and calibrated to the Run on Less dataset for the Tesla Semi collected from the 2023 PepsiCo Semi pilot by the North American Council for Freight Efficiency.

In

Competition Results

This file describes the contents of an archive of the 10th Competition on Software Verification (SV-COMP 2021).
https://sv-comp.sosy-lab.org/2021/

The competition was run by Dirk Beyer, LMU Munich, Germany.
More information is available in the following article:
Dirk Beyer. Software Verification: 10th Comparative Evaluation (SV-COMP 2021). In Proceedings of the 27th International Conference on Tools and Algorithms for the Construction and Analysis of Systems (TACAS 2021, Luxembourg, March 27 - April 1), 2021. Springer.

Copyright (C) Dirk Beyer
https://www.sosy-lab.org/people/beyer/

SPDX-License-Identifier: CC-BY-4.0
https://spdx.org/licenses/CC-BY-4.0.html

To browse the competition results with a web browser, there are two options:

• start a local web server using php -S localhost:8000 in order to view the data in this archive, or
• browse https://sv-comp.sosy-lab.org/2021/results/ in order to view the data on the SV-COMP web page.

Contents

• index.html: directs to the overview web page
• LICENSE.txt: specifies the license
• README.txt: this file
• results-validated/: results of validation runs
• results-verified/: results of verification runs and aggregated results

The folder results-validated/ contains the results from validation runs:

• *.xml.bz2: XML results from BenchExec
• *.logfiles.zip: output from tools
• *.json.gz: mapping from files names to SHA 256 hashes for the file content

The folder results-verified/ contains the results from verification runs and aggregated results:

• index.html: overview web page with rankings and score table
• *.xml.bz2: XML results from BenchExec
• *.merged.xml.bz2: XML results from BenchExec, status adjusted according to the validation results
• *.logfiles.zip: output from tools
• *.json.gz: mapping from files names to SHA 256 hashes for the file content
• *.xml.bz2.table.html: HTML views on the detailed results data as generated by BenchExec’s table generator
• *.All.table.html: HTML views of the full benchmark set (all categories) for each tool
• META_*.table.html: HTML views of the benchmark set for each meta category for each tool, and over all tools
• : HTML views of the benchmark set for each category over all tools
• iZeCa0gaey.html: HTML views per tool

• validatorStatistics.html: Statictics of the validator runs

• quantilePlot-*: score-based quantile plots as visualization of the results
• quantilePlotShow.gp: example Gnuplot script to generate a plot

• score*: accumulated score results in various formats

The hashes of the file names (in the files *.json.gz) are useful for

• validating the exact contents of a file and
• accessing the files from the witness store.

Other Archives

Overview over archives from SV-COMP 2021 that are available at Zenodo:

• https://doi.org/10.5281/zenodo.4459196 Witness store (containing the generated verification witnesses)
• https://doi.org/10.5281/zenodo.4458215 Results (XML result files, log files, file mappings, HTML tables)
• https://doi.org/10.5281/zenodo.4459126 Verification tasks, version svcomp21
• https://doi.org/10.5281/zenodo.4317433 BenchExec, version 3.6

All benchmarks were executed for SV-COMP 2021 https://sv-comp.sosy-lab.org/2021/
by Dirk Beyer, LMU Munich, based on the following components:

• https://gitlab.com/sosy-lab/sv-comp/archives-2021 svcomp21-0-g08c7a98
• https://gitlab.com/sosy-lab/software/sv-benchmarks svcomp21-0-g4cc6b6d96a
• https://gitlab.com/sosy-lab/software/benchexec 3.6-0-gb278ebbb
• https://gitlab.com/sosy-lab/benchmarking/competition-scripts svcomp21-0-g8339740
• https://gitlab.com/sosy-lab/sv-comp/bench-defs svcomp21-0-ga57fe48

Contact

Feel free to contact me in case of questions: https://www.sosy-lab.org/people/beyer/

Test-Comp 2022

Competition Results

This file describes the contents of an archive of the 4th Competition on Software Testing (Test-Comp 2022).
https://test-comp.sosy-lab.org/2022/

The competition was run by Dirk Beyer, LMU Munich, Germany.
More information is available in the following article:
Dirk Beyer. Advances in Automatic Software Testing: Test-Comp 2022. In Proceedings of the 25th International Conference on Fundamental Approaches to Software Engineering (FASE 2022, Munich, April 2 - 7), 2021. Springer.

Copyright (C) Dirk Beyer
https://www.sosy-lab.org/people/beyer/

SPDX-License-Identifier: CC-BY-4.0
https://spdx.org/licenses/CC-BY-4.0.html

To browse the competition results with a web browser, there are two options:

• start a local web server using php -S localhost:8000 in order to view the data in this archive, or
• browse https://test-comp.sosy-lab.org/2022/results/ in order to view the data on the Test-Comp web page.

Contents

• index.html: directs to the overview web page
• LICENSE.txt: specifies the license
• README.txt: this file
• results-validated/: results of validation runs
• results-verified/: results of test-generation runs and aggregated results

The folder results-validated/ contains the results from validation runs:

• *.xml.bz2: XML results from BenchExec
• *.logfiles.zip: output from tools
• *.json.gz: mapping from files names to SHA 256 hashes for the file content

The folder results-verified/ contains the results from test-generation runs and aggregated results:

• index.html: overview web page with rankings and score table

• design.css: HTML style definitions

• *.xml.bz2: XML results from BenchExec

• *.merged.xml.bz2: XML results from BenchExec, status adjusted according to the validation results

• *.logfiles.zip: output from tools

• *.json.gz: mapping from files names to SHA 256 hashes for the file content

• *.xml.bz2.table.html: HTML views on the detailed results data as generated by BenchExec’s table generator

• *.All.table.html: HTML views of the full benchmark set (all categories) for each tool

• META_*.table.html: HTML views of the benchmark set for each meta category for each tool, and over all tools

• : HTML views of the benchmark set for each category over all tools

• iZeCa0gaey.html: HTML views per tool

• quantilePlot-*: score-based quantile plots as visualization of the results

• quantilePlotShow.gp: example Gnuplot script to generate a plot

• score*: accumulated score results in various formats

The hashes of the file names (in the files *.json.gz) are useful for

• validating the exact contents of a file and
• accessing the files from the witness store.

Other Archives

Overview over archives from Test-Comp 2022 that are available at Zenodo:

• https://doi.org/10.5281/zenodo.5831010 Test Suites from Test-Comp 2022 Test-Generation Tools. Witness store (containing the generated test suites)
• https://doi.org/10.5281/zenodo.5831012 Results of the 4th Intl. Competition on Software Testing (Test-Comp 2022). Results (XML result files, log files, file mappings, HTML tables)
• https://doi.org/10.5281/zenodo.5831003 SV-Benchmarks: Benchmark Set of SV-COMP 2022 and Test-Comp 2022. Test tasks, version testcomp22
• https://doi.org/10.5281/zenodo.5720267 BenchExec, version 3.10. Benchmarking framework

All benchmarks were executed for Test-Comp 2022 https://test-comp.sosy-lab.org/2022/ by Dirk Beyer, LMU Munich, based on the following components:

• https://gitlab.com/sosy-lab/test-comp/archives-2022 testcomp22 c211efbc
• https://gitlab.com/sosy-lab/benchmarking/sv-benchmarks testcomp22 ad265d07
• https://gitlab.com/sosy-lab/test-comp/bench-defs testcomp22 93f581b9
• https://gitlab.com/sosy-lab/software/benchexec 3.10 4e8716bd
• https://gitlab.com/sosy-lab/benchmarking/competition-scripts testcomp22 2022c698
• https://gitlab.com/sosy-lab/test-comp/test-format testcomp22 2895be41

Contact

Feel free to contact me in case of questions: https://www.sosy-lab.org/people/beyer/

(Link to Metadata) EmergencyE911_RDS was originally derived from RDSnn (now called TransRoad_RDS). "Zero-length ranges" in the ROADS layer pertain to grand-fathered towns that have not yet provided the Enhanced 9-1-1 Board road segment range information. RDSnn was originally developed using a combination of paper and RC Kodak RF 5000 orthophotos (visual image interpretation and manual digitizing of centerlines). Road attributes (RTNO and CLASS) were taken from the official VT Agency of Transportation (VTrans) highway maps. New roads not appearing on the photos were digitized with locations approximated from the VTrans highway maps. State Forest maps were used to determine both location and attributes of state forest roads. Some data updates have used RF 2500 or RF 1250 orthophotos and GPS, or other means for adding new roads and improving road locations. The Enhanced E911 program added new roads from GPS and orthos between 1996-1998. Also added road name and address geocoding. VCGI PROCESSING (Tiling and Added items); E911 provides the EmergencyE911_RDS data to VCGI in a statewide format. It lacks FIPS6 coding, making it difficult to extract data on the basis of town/county boundaries. As a result, VCGI has added FIPS6 to the attribute table. This field was originally populated by extracting MCODE value from RDNAME and relating to TBPOLY.PAT to bring over matching MCODE values. FIPS6 problems along the interstates and "Gores & Grants" in the Northeast Kingdom, were corrected. All features with an MCODE equal to 200 or 579 were assigned a FIPS6 equal to 0. The center point of these arcs were then intersected with BoundaryTown_TBHASH to assign a FIPS6 value. This information was then transfered back into the RDS.AAT file via a relate. A relate was established between the ROADNAMES.DBF file (road name lookup table) and the RDS.AAT file. The RDFLNAME attribute was populated by transfering the NAME value in the ROADNAMES.DBF table. The RDFLNAME item was then parsed into SUF.DIR, STREET.NAME, STREET.TYPE, and PRE.DIR, making addressing matching functions a little easier. See the "VT Road Centerline Data FAQ" for more information about TransRoad_RDS and EmergencyE911_RDS. https://vcgi.vermont.gov/techres/?page=./white_papers/default_content.cfmField Descriptions:OBJECTID: Internal feature number, automatically generated by Esri software.SEGMENTID: Unique segment ID.ARCID: Arc identifier, unique statewide. The ARCID is a unique identifier for every ARC in the EmergencyE911_RDS data layer.PD: Prefix Direction, previously name PRE.DIR.PT: Prefix Type.SN: Street Name. Previously named STREET.ST: Street Type.SD: Suffix Direction, i.e., W for West, E for East, etc.GEONAMEID: Unique ID for each road name.PRIMARYNAME: Primary name.ALIAS1: Alternate road name 1.ALIAS2: Alternate road name 2.ALIAS3: Alternate road name 3.ALIAS4: Alternate road name 4.ALIAS5: Alternate road name 5.COMMENTS: Free text field for miscellaneous comments.ONEWAY: One-way street. Uses the Oneway domain*.NO_MSAG:MCODE: Municipal code.LESN: Left side of road Emergency Service Number.RESN: Right side of road Emergency Service Number.LTWN: Left side of road town.RTWN: Right side of road town.LLO_A: Low address for left side of road.RLO_A: Low address for right side of road.LHI_A: High address for left side of road.RHI_A: High address for right side of road.LZIP: Left side of road zip code.RZIP: Right side of road zip code.LLO_TRLO_TLHI_TRHI_TRTNAME: Route name.RTNUMBER: Route number.HWYSIGN: Highway sign.RPCCLASSAOTCLASS: Agency of Transportation class. Uses AOTClass domain**.ARCMILES: ESRI ArcGIS miles.AOTMILES: Agency of Transportation miles.AOTMILES_CALC:UPDACT:SCENICHWY: Scenic highway.SCENICBYWAY: Scenic byway.FORMER_RTNAME: Former route name.PROVISIONALYEAR: Provisional year.ANCIENTROADYEAR: Ancient road year.TRUCKROUTE: Truck route.CERTYEAR:MAPYEAR:UPDATEDATE: Update date.GPSUPDATE: Uses GPSUpdate domain***.GlobalID: GlobalID.STATE: State.GAP: Gap.GAPMILES: Gap miles.GAPSTREETID: Gap street ID.FIPS8:FAID_S:RTNUMBER_N:LCOUNTY:RCOUNTY:PRIMARYNAME1:SOURCEOFDATA: Source of data.COUNTRY: Country.PARITYLEFT:PARITYRIGHT:LFIPS:RFIPS:LSTATE:RSTATE:LESZ:RESZ:SPEED_SOURCE: Speed source.SPEEDLIMIT: Speed limit.MILES: Miles.MINUTES: Minutes.Shape: Feature geometry.Shape_Length: Length of feature in internal units. Automatically computed by Esri software.*Oneway Domain:N: NoY: Yes - Direction of arcX: Yes - Opposite direction of arc**AOTClass Domain:1: Town Highway Class 1 - undivided2: Town Highway Class 2 - undivided3: Town Highway Class 3 - undivided4: Town Highway Class 4 - undivided5: State Forest Highway6: National Forest Highway7: Legal Trail. Legal Trail Mileage Approved by Selectboard after the enactment of Act 178 (July 1, 2006). Due to the introduction of Act 178, the Mapping Unit needed to differentiate between officially accepted and designated legal trail versus trails that had traditionally been shown on the maps. Towns have until 2015 to map all Class 1-4 and Legal Trails, based on new changes in VSA Title 19.8: Private Road - No Show. Private road, but not for display on local maps. Some municipalities may prefer not to show certain private roads on their maps, but the roads may need to be maintained in the data for emergency response or other purposes.9: Private road, for display on local maps10: Driveway (put in driveway)11: Town Highway Class 1 - North Bound12: Town Highway Class 1 - South Bound13: Town Highway Class 1 - East Bound14: Town Highway Class 1 - West Bound15: Town Highway Class 1 - On/Off Ramp16: Town Highway Class 1 - Emergency U-Turn20: County Highway21: Town Highway Class 2 - North Bound22: Town Highway Class 2 - South Bound23: Town Highway Class 2 - East Bound24: Town Highway Class 2 - West Bound25: Town Highway Class 2 - On/Off Ramp30: State Highway31: State Highway - North Bound32: State Highway - South Bound33: State Highway - East Bound34: State Highway - West Bound35: State Highway - On/Off Ramp40: US Highway41: US Highway - North Bound42: US Highway - South Bound43: US Highway - East Bound44: US Highway - West Bound45: US Highway - On/Off Ramp46: US Highway - Emergency U-Turn47: US Highway - Rest Area50: Interstate Highway51: Interstate Highway - North Bound52: Interstate Highway - South Bound53: Interstate Highway - East Bound54: Interstate Highway - West Bound55: Interstate Highway - On/Off Ramp56: Interstate Highway - Emergency U-Turn57: Interstate Highway - Rest Area59: Interstate Highway - Other65: Ferry70: Unconfirmed Legal Trail71: Unidentified Corridor80: Proposed Highway Unknown Class81: Proposed Town Highway Class 182: Proposed Town Highway Class 283: Proposed Town Highway Class 384: Proposed State Highway85: Proposed US Highway86: Proposed Interstate Highway87: Proposed Interstate Highway - Ramp88: Proposed Non-Interstate Highway - Ramp89: Proposed Private Road91: New - Class Unknown92: Military - no public access93: Public - Class Unknown95: Class Under Review96: Discontinued Road97: Discontinued Now Private98: Not a Road99: Unknown***GPSUpdate Domain:Y: Yes - Needs GPS UpdateN: No - Does not need GPS UpdateG: GPS Update CompleteV: GPS Update Complete - New RoadX: Unresolved Segment

SV-COMP 2025

Competition Results

This file describes the contents of an archive of the 14th Competition on Software Verification (SV-COMP 2025). https://sv-comp.sosy-lab.org/2025/

The competition was organized by Dirk Beyer, LMU Munich, Germany and Jan Strejček, Masaryk University, Czechia. More information is available in the following article: Dirk Beyer and Jan Strejček. Improvements in Software Verification and Witness Validation: SV-COMP 2025. In Proceedings of the 31st International Conference on Tools and Algorithms for the Construction and Analysis of Systems (TACAS 2025, Hamilton, Canada, May 3–8), 2024. Springer.

Copyright (C) 2025 Dirk Beyer and Jan Strejček https://www.sosy-lab.org/people/beyer/ https://www.fi.muni.cz/~xstrejc/

SPDX-License-Identifier: CC-BY-4.0 https://spdx.org/licenses/CC-BY-4.0

To browse the competition results with a web browser, there are two options:

• start a local web server using php -S localhost:8000 in order to view the data in this archive, or
• browse https://sv-comp.sosy-lab.org/2025/results/ in order to view the data on the SV-COMP web page.

Contents

• index.html: directs to the overview web pages of the verification and validation track
• LICENSE-results.txt: specifies the license
• README-results.txt: this file
• results-validated/: results of validation runs
• results-verified/: results of verification runs

The folder results-validated/ contains the results from validation runs:

• index.html: overview web page with rankings and score table

• design.css: HTML style definitions

• *.results.txt: TXT results from BenchExec

• *.xml.bz2: XML results from BenchExec

• *.fixed.xml.bz2: XML results from BenchExec, status adjusted according to the validation results

• *.logfiles.zip: output from tools

• *.json.gz: mapping from files names to SHA 256 hashes for the file content

• : HTML views of the full benchmark set (all categories) for each validator

• : HTML views of the benchmark set for each category over all validators

• *.xml: XML table definitions for the above tables

• validators.*: Statistics of the validator runs (obsolete)

• correctness: Infix for validation of correctness witnesses

• violation: Infix for validation of violation witnesses

• 1.0: Infix for validation of v1.0 witnesses

• 2.0: Infix for validation of v2.0 witnesses

• quantilePlot-*: score-based quantile plots as visualization of the results

• quantilePlotShow.gp: example Gnuplot script to generate a plot

• score*: accumulated score results in various formats

• witness-database.csv: data base of all witnesses

• witness-classification.csv: data base of all witnesses with their classification into correct, wrong, unknown

The folder results-verified/ contains the results from verification runs and aggregated results:

• index.html: overview web page with rankings and score table

• design.css: HTML style definitions

• *.results.txt: TXT results from BenchExec

• *.xml.bz2: XML results from BenchExec

• *.fixed.xml.bz2: XML results from BenchExec, status adjusted according to the validation results

• *.logfiles.zip: output from tools

• *.json.gz: mapping from files names to SHA 256 hashes for the file content

• *.xml.bz2.table.html: HTML views on the detailed results data as generated by BenchExec’s table generator

• : HTML views of the full benchmark set (all categories) for each verifier

• META_*.table.html: HTML views of the benchmark set for each meta category for each verifier, and over all verifiers

• : HTML views of the benchmark set for each category over all verifiers

• *.xml: XML table definitions for the above tables

• results-per-tool.php: List of results for each tool for review process in pre-run phase

• : List of results for a tool in HTML format with links

• quantilePlot-*: score-based quantile plots as visualization of the results

• quantilePlotShow.gp: example Gnuplot script to generate a plot

• score*: accumulated score results in various formats

The hashes of the file names (in the files *.json.gz) are useful for

• validating the exact contents of a file and
• accessing the files from the witness store.

Related Archives

Overview of archives from SV-COMP 2025 that are available at Zenodo:

• https://doi.org/10.5281/zenodo.15012077 Verification Witnesses from SV-COMP 2025 Verification Tools. Witness store (containing the generated verification witnesses)
• https://doi.org/10.5281/zenodo.15055359 Verifiers and Validators: FM-Tools Data Set for SV-COMP 2025. Metadata snapshot of the evaluated tools (DOIs, options, etc.)
• https://doi.org/10.5281/zenodo.15012085 Results of the 14th Intl. Competition on Software Verification (SV-COMP 2025). Results (XML result files, log files, file mappings, HTML tables)
• https://doi.org/10.5281/zenodo.15012096 SV-Benchmarks: Benchmark Set of SV-COMP 2025. Verification tasks, version svcomp24
• https://doi.org/10.5281/zenodo.15007216 BenchExec, version 3.29. Benchmarking framework

All benchmarks were executed for SV-COMP 2025 https://sv-comp.sosy-lab.org/2025/ by Dirk Beyer, LMU Munich, based on the following components:

• https://gitlab.com/sosy-lab/benchmarking/fm-tools 2.2
• https://gitlab.com/sosy-lab/benchmarking/sv-benchmarks svcomp25
• https://gitlab.com/sosy-lab/sv-comp/bench-defs svcomp25
• https://gitlab.com/sosy-lab/software/benchexec 3.29
• https://gitlab.com/sosy-lab/software/benchcloud 1.3.0
• https://gitlab.com/sosy-lab/benchmarking/sv-witnesses 2.0.3
• https://gitlab.com/sosy-lab/software/coveriteam 1.2.1
• https://gitlab.com/sosy-lab/benchmarking/competition-scripts svcomp25

Contact

Feel free to contact me in case of questions: https://www.sosy-lab.org/people/beyer/