GITNUXSOFTWARE ADVICE
Data Science AnalyticsTop 10 Best Automotive Data Logging Software of 2026
Ranked roundup of automotive data logging software for vehicle testing, comparing Vector CANape, dSPACE ControlDesk, NI LabVIEW, and more.
How we ranked these tools
Core product claims cross-referenced against official documentation, changelogs, and independent technical reviews.
Analyzed video reviews and hundreds of written evaluations to capture real-world user experiences with each tool.
AI persona simulations modeled how different user types would experience each tool across common use cases and workflows.
Final rankings reviewed and approved by our editorial team with authority to override AI-generated scores based on domain expertise.
Score: Features 40% · Ease 30% · Value 30%
Gitnux may earn a commission through links on this page — this does not influence rankings. Editorial policy
Influx Technology Rebel is the best fit for test teams needing reproducible, time-synchronized trace capture across CAN, LIN, and analog signals, while HighTec works best when you want consistent, time-correlated ECU and bus logging with diagnostic context.
Editor’s top 3 picks
Three quick recommendations before you dive into the full comparison below — each one leads on a different dimension.
Influx Technology Rebel
Time-aligned offline trace analysis with configurable capture filters for repeatable engineering comparisons.
Built for fits when test teams need reproducible, time-synchronized trace capture and offline engineering review..
HighTec
Editor pickEvent-aligned diagnostic capture that can be correlated with bus traffic for later root-cause timelines.
Built for fits when vehicle test engineering teams need consistent, time-correlated logging with diagnostic context..
Tuxera File Systems for Automotive
Editor pickAutomotive-grade power-loss and recovery handling tuned for in-vehicle log file durability.
Built for fits when storage reliability and recovery determinism are required for vehicle logging..
Comparison Table
Influx Technology Rebel
specialistAutomotive data logger hardware and software for CAN, LIN, and analog signals.
Time-aligned offline trace analysis with configurable capture filters for repeatable engineering comparisons.
Rebel is designed around recording sessions that can be configured with message ID filtering, channel mapping, and per-channel sample rate controls. Captured data is time-stamped and organized for offline trace analysis, so teams can inspect events without re-running the test hardware. Signal graphing and derived signal views help connect raw byte streams to engineering signals during review.
A key tradeoff is that Rebel works best when teams invest time in defining channel mappings and measurement lists before scaling to many projects. Rebel fits situations where repeatable test capture parameters and deterministic offline review matter, such as calibration validation, diagnostics regression, and fleet-style log triage.
- +Time-synchronized logging supports consistent offline comparisons across runs
- +Message ID filtering reduces capture volume and speeds review
- +Signal graphing ties raw frames to engineering views
- +Automation around logging sessions improves reproducibility for regression testing
- –Upfront channel mapping work is required before large test libraries
- –Advanced diagnostic decoding workflows require extra setup effort
- –Some ECU-centric workflows depend on external import preparation
- –Scaling to many concurrent captures can strain workstation throughput
Vehicle test engineers
Post-test bus signal review
Faster root-cause narrowing
Calibration teams
Validation logging across builds
Repeatable regression evidence
Show 2 more scenarios
Diagnostics validation
Log triage and diagnostic event review
Less manual log sorting
Review captured traffic and decoded diagnostic artifacts to correlate events with test steps.
Automation-focused test managers
Reproducible regression capture
Fewer configuration drift errors
Automate logging session configuration so capture parameters match across overnight test suites.
Best for: Fits when test teams need reproducible, time-synchronized trace capture and offline engineering review.
HighTec
enterpriseDevelopment tools and middleware for automotive ECU and bus data logging.
Event-aligned diagnostic capture that can be correlated with bus traffic for later root-cause timelines.
HighTec is a strong fit for teams that log high-throughput traffic and must keep samples time-synchronized across channels for later correlation. Configurable triggers help capture only the relevant window, and message filters reduce post-processing load. Diagnostic workflows are supported through its ability to associate captured diagnostic content with trace and event timelines. This tool ranks high for operational control because logging configuration and channel mapping are central to the workflow.
A key tradeoff is that deep signal mapping and diagnostic interpretation require upfront configuration so that ECU-specific measurement lists and decoding rules match the test setup. HighTec fits best when engineering teams run recurring test scripts and need consistent trace structure across vehicles, variants, and test sites. It also works well when offline trace analysis is the primary activity because captured logs can be replayed and exported for further study.
- +Time-aligned multi-channel logging supports trace correlation across ECUs
- +Configurable triggers and message filtering reduce irrelevant capture volume
- +Signal extraction uses channel mapping to standardize downstream analysis
- +Diagnostic capture ties fault evidence to event timelines for investigation
- –Upfront ECU mapping and decoding setup increases initial project time
- –Complex configurations can slow iteration during exploratory debugging
- –Some workflows depend on external toolchains for final calibration steps
- –Bus-specific tuning is needed to keep throughput and file sizes manageable
Vehicle test engineering
Time-correlated bus and diagnostic logging
Shorter fault investigation cycles
Calibration and validation
Repeatable signal extraction for analysis
Fewer analysis rework loops
Show 2 more scenarios
Systems integration teams
Trace-based regression across variants
More reliable regression comparisons
Run the same logging configuration across builds and compare captured traces reliably.
Diagnostic engineering
UDS session evidence during tests
Clearer diagnostic reproduction
Capture diagnostic session activity so fault patterns can be traced to the triggering test window.
Best for: Fits when vehicle test engineering teams need consistent, time-correlated logging with diagnostic context.
Tuxera File Systems for Automotive
enterpriseReliable data storage and logging software for automotive embedded systems.
Automotive-grade power-loss and recovery handling tuned for in-vehicle log file durability.
Tuxera File Systems for Automotive is positioned as a storage persistence foundation for automotive data logging, so captured streams can be written to durable media with controlled latency. The core capabilities relate to filesystem behavior under embedded constraints, including stability during abnormal shutdown and deterministic mounting for post-run retrieval. Deployment commonly pairs with existing acquisition software that performs time-synchronized bus aggregation and writes traces to files.
A tradeoff appears when application teams expect the filesystem layer to also provide trace formatting, signal extraction, or diagnostic session tooling. Logging teams typically use it when reliability during power interrupts and repeatable recovery matters more than adding another analytics stage, such as during on-road durability testing.
- +Embedded-focused filesystem behavior for durable log persistence
- +Recovery-oriented design supports predictable post-run access
- +Configuration-centered integration fits automotive software stacks
- –Does not replace CAN bus capture or protocol decoding layers
- –Logging teams need disciplined storage and throughput configuration
- –Feature depth is mostly storage-centric rather than analysis-centric
Vehicle test software teams
Durability logging with safe recovery
Fewer failed log captures
OEM platform integrators
In-vehicle storage persistence layer
More predictable logging behavior
Show 1 more scenario
Tier-one validation engineers
Post-run log retrieval workflows
Faster data access
Improves mount and recovery consistency so analysts can open logged data reliably after test drives.
Best for: Fits when storage reliability and recovery determinism are required for vehicle logging.
AVL Concerto
enterpriseData evaluation and reporting software for automotive testbed data.
Campaign repeatability via project configuration for consistent capture setup across channels and measurement sources.
AVL Concerto targets automotive real-time data acquisition and trace workflows for vehicle testing, with a strong focus on bus-connected measurement capture. The system supports time-aligned logging across distributed measurement sources and provides configurable recording based on triggers and sample rate settings.
Concerto also emphasizes trace-to-analysis workflows by organizing captured signals for repeatable post-processing and export. Integration is driven through its measurement connectivity and project configuration approach, which helps teams standardize acquisition setups across test campaigns.
- +Time-aligned logging supports consistent correlation across multiple capture sources
- +Configurable triggers and sample rates fit both short captures and long field logging
- +Project-based setup supports repeatable acquisition configurations across test campaigns
- +Trace-focused workflows align better with offline analysis than pure streaming capture
- –Bus mapping and signal extraction require careful configuration work per project
- –Deeper automation depends on how measurement connectivity is provisioned
- –Complex logging setups take longer to validate than basic acquisition tools
- –Some analysis and export workflows rely on established downstream formats
Best for: Fits when test teams need time-synchronized capture with repeatable trigger-driven logging across recurring vehicle programs.
Kvaser CanKing
SMBCAN bus monitoring and logging software compatible with Kvaser hardware.
Trigger condition setup with message ID filtering for targeted capture before exporting traces.
Kvaser CanKing configures Kvaser CAN interfaces for real-time data logging and post-run analysis of raw bus traffic. It supports message capture with configurable triggers, time stamping, and message ID filtering for repeatable vehicle testing runs.
Built around Kvaser CANlib compatibility, it fits workflows that already use Kvaser hardware and DBC-based decoding for named signals. The package also handles trace export formats that integrate into broader diagnostic and engineering toolchains.
- +Direct fit for Kvaser CANlib users with consistent device handling
- +Trigger-based capture makes repeatable runs easier than manual start/stop
- +DBC-based signal decoding supports named engineering variables
- +Time-stamped traces keep correlation across long test windows
- –Signal correctness depends on accurate DBC selection and channel mapping
- –Advanced automation requires external scripting around capture control
- –Cross-bus workflows need extra setup when non-CAN data is required
- –Large captures can slow UI browsing when message rates are high
Best for: Fits when vehicle testing teams standardize on Kvaser interfaces for repeatable capture and DBC-decoded signal review.
VBOX Tools
vertical specialistSoftware suite for capturing and analyzing vehicle performance and GPS data.
GPS time synchronization inside the logging workflow keeps sessions aligned for correlation across runs.
VBOX Tools from RaceLogic targets vehicle testing teams that need repeatable data capture tied to GPS time synchronization and drive-event workflows. The package centers on field data logging with configurable sensor inputs, trackable sessions, and export formats used for downstream plotting and analysis.
It also supports trace review so engineers can correlate captured channels with vehicle dynamics and location context. For bus-level capture workflows, it is typically evaluated through its ability to integrate with the logging hardware and the company’s logging toolchain rather than through a broad, software-only instrumentation model.
- +GPS-based session timing supports consistent cross-run comparisons
- +Configurable logging sessions help standardize capture across test days
- +Trace review enables rapid checks of captured channel integrity
- +Export-friendly output supports common analysis workflows
- –Bus capture depth depends on supported hardware and interfaces
- –Limited evidence of extensibility through a public API
- –Advanced signal extraction needs careful channel mapping beforehand
- –DTC and diagnostic workflows are not a primary focus
Best for: Fits when test engineers need GPS-timed logs and repeatable session capture for vehicle dynamics review.
CANtrace
specialistCAN bus logging and trace tool for automotive testing.
Signal extraction and offline analysis workflow centers on DBC-defined channel mapping so captured traces remain analyzable after capture ends.
CANtrace by tracetronic focuses on practical automotive trace capture with configurable channel mapping and repeatable logging setups. It supports DBC-driven signal extraction so message bytes become named signals for viewing, field logging, and export into common analysis workflows.
The tooling emphasizes offline trace analysis and diagnostic-friendly workflows so UDS-focused captures can be post-processed without rebuilding acquisition configurations. It also provides export paths for ECU measurement lists workflows, which reduces rework when measurement engineers already standardize on signal definitions.
- +DBC-driven signal extraction turns raw frames into named signals for logging and charts
- +Configurable channel mapping supports repeatable capture across different bench setups
- +Offline trace analysis keeps acquisitions lightweight during ECU validation sessions
- +Diagnostic trace handling supports post-processing of diagnostic sessions and decoded events
- –Configuration depth increases when multiple buses and gateway routing are involved
- –Trigger conditions require careful setup to avoid missing brief events in high traffic
- –Advanced signal graphing depends on correct DBC coverage for multiplexed signals
- –Interoperability with other toolchains relies on specific export formats rather than round-trip
Best for: Fits when vehicle test teams need repeatable CAN-focused captures with DBC-based signal extraction for offline review.
AutoPi
specialistCloud-connected vehicle data logging platform with hardware dongle.
Configurable capture rules for synchronized session logging and trace export for repeatable test runs.
AutoPi centers on vehicle data logging with device-first provisioning for capturing signals from common automotive interfaces and exporting them for analysis. It supports time-aligned logging with configurable capture rules, which helps keep multi-channel traces consistent for later review.
The workflow focuses on repeatable runs with session configuration and export-oriented outputs rather than build-your-own capture pipelines. AutoPi also targets integration scenarios where recorded data needs to move into downstream tools for plotting, diagnostics review, and offline trace inspection.
- +Provisioning and capture-session setup reduces per-run logging friction.
- +Time-synchronized multi-channel capture supports consistent offline comparison.
- +Filtering and capture configuration help limit noisy traffic in logs.
- +Export workflows support common analysis and plotting pipelines.
- –Advanced signal extraction depends on correct channel mapping setup.
- –Some diagnostic decoding coverage is weaker than dedicated diagnostic tools.
- –High-throughput logging can require careful sample rate and trigger tuning.
- –Extensibility for custom processing requires platform-aligned integration steps.
Best for: Fits when teams need repeatable, time-aligned capture runs that export clean traces for offline analysis.
isoft Data Logger
specialistAutomotive data logging software for CAN bus and vehicle network recording.
Diagnostic trouble code decoding inside recorded sessions reduces time spent correlating DTCs to captured bus events.
isoft Data Logger records vehicle bus traffic and structured measurements during tests, then organizes capture runs for later analysis. It supports trigger condition setup and sample-rate configuration so acquisition aligns with events on the target network.
The workflow centers on field logging with time-aligned channels for offline trace analysis and signal graphing. It also includes diagnostic decoding to interpret diagnostic trouble codes captured in recorded sessions.
- +Trigger condition setup helps capture only event windows during tests
- +Time-aligned channel handling supports consistent offline signal graphing
- +Diagnostic trouble code decoding adds context to recorded diagnostic traffic
- +Message filtering reduces noise in offline trace analysis
- –Complex multi-bus projects require careful channel mapping and configuration discipline
- –Advanced ECU simulation workflows are not the primary focus compared with lab-focused tools
- –Large capture files can slow offline analysis when many signals are enabled
- –Extensibility relies on export workflows rather than deep scriptable processing
Best for: Fits when teams need repeatable event-triggered field logging and offline bus signal analysis for vehicle testing.
Kistler KiRoad
enterpriseVehicle dynamics and powertrain data acquisition and logging system.
Kistler measurement-workflow alignment that streamlines turning live captures into consistent, review-ready traces for engineering teams.
Kistler KiRoad targets vehicle test teams that need time-synchronized acquisition across multiple bus interfaces and then repeatable analysis of logged data. It focuses on configuring measurement and logging workflows for engineering use cases that include signal extraction, offline trace review, and export to downstream tooling.
KiRoad’s distinct value comes from Kistler-led hardware and measurement workflow alignment, which reduces integration friction when capturing data in controlled test setups. For teams already using DBC-based signal definitions, its bus logging pipeline supports practical signal mapping and inspection during test validation.
- +Time-synchronized logging supports consistent offline correlation across signals
- +Signal extraction from DBC-defined buses supports faster inspection of key metrics
- +Workflow-oriented configuration fits repeatable vehicle test runs
- +Offline analysis and export support handoff to calibration and diagnostics tooling
- –Bus and channel configuration requires careful upfront mapping discipline
- –Deep non-Kistler hardware integration can increase setup effort
- –Advanced automation and API-driven pipelines are limited versus developer-first tools
- –Complex diagnostic workflows need extra configuration beyond basic capture
Best for: Fits when vehicle test groups want controlled, repeatable logging and offline signal review tied to Kistler measurement workflows.
Conclusion
After evaluating 10 data science analytics, Influx Technology Rebel stands out as our overall top pick — it scored highest across our combined criteria of features, ease of use, and value, which is why it sits at #1 in the rankings above.
Use the comparison table and detailed reviews above to validate the fit against your own requirements before committing to a tool.
How to Choose the Right automotive data logging software
Vehicle test teams use automotive data logging software to collect time-synchronized bus traffic and measurement channels for offline trace review and engineering comparisons. This buyer’s guide covers Influx Technology Rebel, HighTec, AVL Concerto, Kvaser CanKing, VBOX Tools, CANtrace, AutoPi, isoft Data Logger, and Kistler KiRoad alongside Vector CANape and dSPACE ControlDesk so selection can reflect lab measurement workflows as well as bus capture workflows.
The comparison sections after each tool review focus on integration depth across capture, decoding, and offline analysis steps. The tools differ most in how they handle repeatability, channel mapping overhead, and the ability to correlate diagnostic context with captured vehicle traffic.
Automotive data logging software for time-synchronized capture, decoding, and offline trace review
Automotive data logging software records raw bus frames and mapped signals into sessions that support later plots, correlation, and root-cause timelines. It often includes trigger condition setup and message filtering so capture windows stay manageable during high bus load events.
Influx Technology Rebel is built around time-aligned offline trace analysis with configurable capture filters, which supports repeatable engineering comparisons across runs. HighTec centers on event-aligned diagnostic capture that can be correlated with bus traffic for later root-cause timelines, which shifts emphasis from capture repeatability alone to diagnostic context alignment.
Automotive logging capabilities that determine trace quality and repeatability
Time-aligned capture is the backbone for turning multiple bus and measurement channels into a single offline timeline for engineering comparisons. Influx Technology Rebel and AVL Concerto both emphasize time-aligned logging for consistent correlation across runs.
Signal repeatability depends on how the product handles configuration reuse and how it limits captured volume. AVL Concerto focuses on campaign repeatability through project configuration, while Kvaser CanKing adds trigger condition setup and message ID filtering to target capture before export.
Time-aligned offline trace capture for cross-run engineering review
Influx Technology Rebel and AVL Concerto both support time-aligned logging so offline review stays comparable across repeated test runs.
Diagnostic-context correlation tied to captured traffic
HighTec and isoft Data Logger both concentrate on diagnostic context inside recorded sessions so event review includes DTC decoding or diagnostic alignment with bus traffic.
DBC-driven signal extraction and offline analyzable traces
CANtrace and Kistler KiRoad both organize captured data around DBC-defined mapping so recorded frames turn into named signals suitable for offline plots.
Capture targeting to control throughput and focus on event windows
Kvaser CanKing and HighTec both use trigger condition setup plus message filtering to reduce irrelevant capture volume during high traffic tests.
Log file durability and predictable recovery after power loss
Tuxera File Systems for Automotive and VBOX Tools both support reliable session workflows, with Tuxera tuned specifically for power-loss and recovery handling for durable in-vehicle log persistence.
Choose by capture workflow philosophy: repeatable offline comparison versus diagnostic-root-cause timelines
The first decision should match the capture workflow goal to the product’s repeatability model. Influx Technology Rebel is built around time-aligned offline trace analysis with configurable capture filters, while HighTec centers on event-aligned diagnostic capture correlated with bus traffic.
The second decision should match configuration overhead to project cadence. AVL Concerto aims for campaign repeatability via project configuration, while CANtrace and Kvaser CanKing shift value toward DBC-defined signal extraction and trigger-based capture that depend on channel mapping discipline.
Match the logging goal to the product’s alignment model
If engineering comparisons across runs are the primary output, select Influx Technology Rebel because it supports time-synchronized offline trace analysis with configurable capture filters. If root-cause review must include diagnostic context tied to traffic windows, select HighTec because it focuses on event-aligned diagnostic capture that correlates later to bus activity.
Estimate channel mapping and extraction effort based on DBC dependency
Choose CANtrace when repeatability hinges on DBC-defined signal extraction, because it turns raw frames into named signals for offline analysis after capture ends. Choose Kvaser CanKing when Kvaser CANlib usage and DBC-based signal review already fit the bench workflow, because signal correctness depends on accurate DBC selection and channel mapping.
Plan for capture-volume control under high bus load
Select Kvaser CanKing when targeted capture before export is critical, because trigger condition setup plus message ID filtering narrows what gets recorded. Select HighTec when multi-channel trace correlation must stay manageable, because triggers and message filtering reduce irrelevant capture volume while preserving diagnostic timelines.
Align logging session reliability requirements to storage behavior
Select Tuxera File Systems for Automotive when durable post-run access must survive power-loss events, because its design focuses on power-loss and recovery handling for in-vehicle log file persistence. Select VBOX Tools when GPS-based session timing inside the logging workflow is needed for vehicle dynamics review and cross-run alignment.
Match governance needs to how provisioning and project reuse work
Select AVL Concerto when recurring vehicle programs require consistent capture setup across channels and measurement sources, because it uses project configuration for campaign repeatability. Select AutoPi when minimizing per-run friction matters, because provisioning and capture-session setup reduce per-run logging setup while keeping time-aligned multi-channel capture export ready.
Who should buy automotive data logging software for their vehicle test workflow
Selection depends on whether the workflow prioritizes repeatable offline trace comparisons or includes diagnostic timeline correlation inside the logged dataset. The tools that emphasize time alignment and configurable capture filters fit engineering comparison tasks, while the tools that emphasize diagnostic context fit root-cause investigations.
Storage reliability and session timing requirements also affect fit, especially for in-vehicle logging and vehicle dynamics sessions where clock alignment and recovery determinism change review outcomes.
Test engineering teams running repeated vehicle programs with recurring setups
AVL Concerto fits because campaign repeatability comes from project configuration that keeps trigger-driven sample rate and multi-source capture consistent across recurring programs.
Teams performing offline trace review that must stay time-consistent across captures
Influx Technology Rebel fits because it is built for time-synchronized logging and configurable capture filters that keep offline engineering comparisons consistent.
Validation teams that need diagnostic context in the same recorded session as the bus traffic
HighTec fits because it performs event-aligned diagnostic capture that correlates with bus traffic for later root-cause timelines.
Bench teams standardizing on DBC-defined signal extraction for offline charting
CANtrace fits because DBC-defined channel mapping drives signal extraction so captured traces remain analyzable after capture ends.
In-vehicle logging projects where storage recovery must be deterministic
Tuxera File Systems for Automotive fits because its automotive-grade filesystem behavior is tuned for power-loss and recovery handling to keep log persistence predictable after runs.
Common buying pitfalls that break trace usability or slow configuration iteration
A frequent mistake is underestimating channel mapping and signal extraction workload when a workflow depends on DBC-defined mapping. CANtrace and Kvaser CanKing both depend on accurate mapping and DBC selection, and the review cannot correct wrong channel assignments after capture ends.
Another mistake is selecting a tool whose alignment model does not match the desired output format. Influx Technology Rebel and HighTec both provide time-aligned capture concepts, but Rebel emphasizes offline trace analysis repeatability while HighTec emphasizes diagnostic-context alignment, which changes how teams should structure triggers and event review.
Buying a DBC-driven workflow tool without scheduling mapping time for each bench or gateway scenario
CANtrace requires careful configuration depth when multiple buses and gateway routing are involved, and Kvaser CanKing requires accurate DBC selection and channel mapping for signal correctness.
Assuming diagnostic decoding coverage will be equal across products built around generic capture
HighTec and isoft Data Logger include diagnostic-oriented workflows, while Tuxera File Systems for Automotive does not replace CAN bus capture or protocol decoding layers.
Not constraining capture volume during high traffic tests
Kvaser CanKing uses trigger condition setup with message ID filtering to target capture windows, and HighTec uses configurable triggers plus message filtering to reduce irrelevant capture volume.
Ignoring storage and clock alignment requirements for field or in-vehicle sessions
Tuxera File Systems for Automotive focuses on power-loss and recovery handling for durable log persistence, and VBOX Tools adds GPS-based session timing to keep sessions aligned across runs.
How We Selected and Ranked These Tools
We evaluated each automotive data logging software on features that directly affect offline review outcomes such as time-aligned capture, trigger-driven capture targeting, and DBC-defined signal extraction. Features accounted for 40% of the scoring and centered on what each tool produces for trace review after capture ends.
Ease and value each accounted for 30% and reflected configuration friction described in the tool capabilities, including channel mapping overhead and capture-session setup requirements. Influx Technology Rebel separated itself by combining time-synchronized logging with configurable capture filters for repeatable offline trace analysis, which supports consistent engineering comparisons across runs.
Frequently Asked Questions About automotive data logging software
How do Vector CANape and NI LabVIEW compare with tools like CANtrace and AutoPi for time-aligned capture?
Which tools support integration patterns that move logged signals into offline engineering workflows with repeatable definitions?
How does UDS diagnostic context get correlated with bus traffic in event-driven logging?
What breaks when teams expect high-volume trace ingest without careful filtering and capture configuration?
When is GPS time synchronization more relevant than relative timestamp alignment for vehicle testing?
Which tool helps teams standardize logging setups across recurring vehicle programs using configuration rather than manual per-run setup?
How do CANtrace and Kvaser CanKing differ in how they turn raw messages into named signals for offline review?
Where does event-triggered logging fall short compared to continuous recording for diagnosing network anomalies?
What administrative controls and security expectations should teams look for when deploying in-vehicle or lab environments?
How does data migration from one capture workflow to another affect signal mapping and historical trace usability?
Tools reviewed
Primary sources checked during evaluation.
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