Datasets:

dataeval2026
/

Industrycode

Tasks:

Text Generation

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Languages:

English

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n<1K

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validation

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The dataset generation failed

Error code:   DatasetGenerationError
Exception:    TypeError
Message:      Couldn't cast array of type string to null
Traceback:    Traceback (most recent call last):
                File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 1779, in _prepare_split_single
                  for key, table in generator:
                                    ^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/packaged_modules/json/json.py", line 295, in _generate_tables
                  self._cast_table(pa_table, json_field_paths=json_field_paths),
                  ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/packaged_modules/json/json.py", line 128, in _cast_table
                  pa_table = table_cast(pa_table, self.info.features.arrow_schema)
                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/table.py", line 2321, in table_cast
                  return cast_table_to_schema(table, schema)
                         ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/table.py", line 2255, in cast_table_to_schema
                  cast_array_to_feature(
                File "/usr/local/lib/python3.12/site-packages/datasets/table.py", line 1804, in wrapper
                  return pa.chunked_array([func(chunk, *args, **kwargs) for chunk in array.chunks])
                                           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/table.py", line 2095, in cast_array_to_feature
                  return array_cast(
                         ^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/table.py", line 1806, in wrapper
                  return func(array, *args, **kwargs)
                         ^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/table.py", line 1957, in array_cast
                  raise TypeError(f"Couldn't cast array of type {_short_str(array.type)} to {_short_str(pa_type)}")
              TypeError: Couldn't cast array of type string to null
              
              The above exception was the direct cause of the following exception:
              
              Traceback (most recent call last):
                File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 1347, in compute_config_parquet_and_info_response
                  parquet_operations = convert_to_parquet(builder)
                                       ^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 980, in convert_to_parquet
                  builder.download_and_prepare(
                File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 882, in download_and_prepare
                  self._download_and_prepare(
                File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 943, in _download_and_prepare
                  self._prepare_split(split_generator, **prepare_split_kwargs)
                File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 1646, in _prepare_split
                  for job_id, done, content in self._prepare_split_single(
                                               ^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 1832, in _prepare_split_single
                  raise DatasetGenerationError("An error occurred while generating the dataset") from e
              datasets.exceptions.DatasetGenerationError: An error occurred while generating the dataset

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problem_name string	problem_id int64	problem_description_main string	problem_background_main null	problem_io string	required_dependencies null	sub_steps list	general_solution null	general_tests null
Coriolis Distance and Geostrophic Velocity Calculation	1	The problem aims to develop core functional modules for geostrophic flow velocity calculation and validation, covering Coriolis parameter computation, great-circle distance measurement, velocity solving, abnormal data filtering and result verification, to provide reliable basic calculation support for marine geographic...	null	The problem receives the following input data: 1) double-type single latitude values, 2) four double-type values representing the latitude and longitude of two geospatial points (lat1, lon1, lat2, lon2), 3) std::vector<double> type batch latitude sequence, 4) three double-type values for geostrophic velocity calculatio...	null	[ { "step_number": "1", "step_description_prompt": "Please use C++ to generate a function named problem_1_01. Implement Coriolis parameter calculation logic, Haversine formula for great-circle distance between two latitude/longitude points, and batch Coriolis calculation function inside it. Assign the three p...	null	null
2D Tracer Transport Numerical Simulation	2	The problem aims to build a complete 2D tracer transport numerical simulation framework. It requires implementing core functional components including velocity field calculation, advection-diffusion term computation, boundary condition processing and time integration, all with numerical error protection, to support rel...	null	The problem receives as input 1D double vectors of x and y coordinate arrays, 2D double vector of initial tracer concentration grid Q, scalar double parameters including velocity field coefficients (F, b, p, q, A, B), diffusion coefficient k, time step dt, grid spacing dx and dy, boundary condition control parameters, ...	null	[ { "step_number": "1", "step_description_prompt": "Please write C++ code to implement a function named problem_2_01.\nThe function defines a lambda to compute 2D velocity field u and v grids from x, y coordinate arrays and input parameters, handles exponential computation overflow to avoid NaN/inf values, an...	null	null
Convection Discretization Scheme Implementation and Evaluation	3	The problem focuses on implementing and validating common numerical convection discretization schemes for computational fluid dynamics simulations using C++. It covers core scheme implementation, stability verification via CFL number calculation, cross-scheme accuracy comparison, and performance evaluation, with all im...	null	The problem receives the following input data: pre-declared global function pointer-to-pointers for upwind direction determination, 1D upwind scheme, 2D upwind scheme, 2D CFL number calculation, and 2D centered convection scheme; and numerical calculation parameters including double-type velocity values (u, v, u_max, v...	null	[ { "step_number": "1", "step_description_prompt": "Please write C++ code to implement a function named problem_3_01. First define the global enum class UpwindDirection with four discrete values. The function needs to implement 1D and 2D upwind schemes, create related calculation lambdas, and assign their fun...	null	null
Finite Difference Solver for Topographic Wave Equation	4	The problem aims to implement a robust finite difference numerical framework for topographic wave equation simulations in C++, covering core computation modules, numeric exception handling, initialization logic, boundary condition processing, and stability verification to support accurate and stable geophysical flow ev...	null	The problem takes no direct input parameters when executing the three exposed void functions problem_4_01, problem_4_02, and problem_4_03. It relies on pre-declared global pointer-to-pointer variables provided by the caller: double (calculate_c_pptr)(double, double, double), void (forward_space_step_pptr)(std::vect...	null	[ { "step_number": "1", "step_description_prompt": "Please write C++ code to implement a function named problem_4_01. This function implements finite difference related calculations, including two lambdas: one for calculating c coefficient with abnormal value handling, another for forward space step computing...	null	null
C++ Implementation of 2D Tracer Transport System	5	The problem aims to develop a complete 2D tracer transport simulation system using C++. It covers core components including data structure design, velocity field generation, numerical advection calculation, boundary condition processing, numerical stability monitoring, and modular framework construction to support reli...	null	The problem receives the following input data: 1) Simulation configuration parameters: size_t-type x-direction grid count nx, y-direction grid count ny, time step count nt; double-type x grid spacing dx, y grid spacing dy, time step length dt; 2) Velocity field generation parameters: double-type scaling factor F, verti...	null	[ { "step_number": "1", "step_description_prompt": "Please write C++ code to implement the problem_5_01 function.\nAlgorithm process: First declare all required global function double pointers and the PI constant, define the TracerTransportSystem class inside the function, implement its initialize method and ...	null	null
Convection Term Finite Difference Scheme Implementation and Evaluation	6	The problem aims to implement upwind and centered finite difference schemes for 1D convection term calculation in C++, covering scheme structure design, parameter and boundary validity checks, and proper function packaging, to support subsequent numerical analysis including accuracy assessment, stability evaluation, di...	null	The problem receives five types of inputs: 1) a std::vector<double> storing discrete 1D advection quantity values, 2) an integer indicating the target grid node index for convection term calculation, 3) a double-precision floating point value representing advection velocity, 4) a double-precision floating point value r...	null	[ { "step_number": "1", "step_description_prompt": "Please use C++ to generate a function named problem_6_01. Implement upwind and centered finite difference schemes for convection term calculation, create corresponding captureless lambda wrappers, and assign the wrapper function addresses to pre-declared glo...	null	null
C++ Vehicle Dynamics Coriolis and Lateral Force Calculation	7	The problem aims to develop C++ template functions for vehicle dynamics force calculations, covering simplified Coriolis plus centripetal force and comprehensive lateral resultant force involving Earth rotation related terms. The functions support both single and batch vehicle parameter input, return structured functio...	null	The problem receives two categories of input: first, a user-defined C++ struct type VehicleParams as the template parameter for the required template functions, which contains four double-type fields: latitude (in degrees), vehicle mass, driving velocity, and turning radius; second, predefined global fixed constants in...	null	[ { "step_number": "1", "step_description_prompt": "Please use C++ to generate the template function subproblem_7_1_functions with VehicleParams as its template parameter. It implements simplified Coriolis force plus centripetal force calculation for vehicle dynamics, takes vehicle parameters including latitu...	null	null
C++ Implementation of CFD Scheme Stability and Convergence Analysis	8	"The problem requires implementing a series of C++ utility functions for computational fluid dynamic(...TRUNCATED)	null	"The problem receives as input double-precision floating-point values for advection velocity c, time(...TRUNCATED)	null	[{"step_number":"1","step_description_prompt":"Please use C++ to implement a function named subprobl(...TRUNCATED)	null	null
C++ 1D Advection Equation Solver Utilities	9	"The problem requires implementing a comprehensive suite of C++ utilities for 1D advection equation (...TRUNCATED)	null	"The problem receives the following input data: double-type advection velocity c, double-type spatia(...TRUNCATED)	null	[{"step_number":"1","step_description_prompt":"Please use C++ to generate a function named subproble(...TRUNCATED)	null	null
Capacitated Warehouse Distribution Optimization Solver	1	"The problem requires developing a complete MATLAB optimization framework for capacitated warehouse (...TRUNCATED)	null	"The problem accepts an optional string input caseName (valid values: 'industrial', 'small') specify(...TRUNCATED)	null	[{"step_number":"1","step_description_prompt":"Please write MATLAB code to implement a function name(...TRUNCATED)	null	null

End of preview.

IndustryCode

IndustryCode is an anonymized benchmark dataset for evaluating large language models on industry-oriented code generation tasks.

Overview

IndustryCode is designed to evaluate code generation for realistic industrial problems rather than general-purpose software exercises. It spans 20 subdomains across four major sectors: Finance, Automation, Aerospace, and Remote Sensing, and supports four programming languages: Python, C++, MATLAB, and Stata.

The dataset contains:

125 main problems
579 sub-problems
4 programming languages

Each record represents one main industrial coding task together with decomposed sub-steps and evaluation artifacts.

Dataset Structure

The dataset is distributed as JSONL files grouped by programming language and split:

c++_jsonl/test.jsonl
c++_jsonl/validation.jsonl
python_jsonl/test.jsonl
python_jsonl/validation.jsonl
matlab_jsonl/test.jsonl
matlab_jsonl/validation.jsonl
stata_jsonl/test.jsonl
stata_jsonl/validation.jsonl

Split counts:

C++: 25 test, 9 validation
Python: 63 test, 8 validation
MATLAB: 16 test, 1 validation
Stata: 2 test, 1 validation

Domain Coverage

Programming-language coverage in the released benchmark includes:

Programming Language	Covered subfields
Python	Chemical Manufacturing, General Manufacturing, Finance and Insurance, Machinery Manufacturing, Software Publishers, Electronic Product Manufacturing, Medical Equipment Manufacturing, Information, Transportation and Warehousing
C++	Construction, Information, Mining, Machinery Manufacturing, Electronic Product Manufacturing, Transportation and Warehousing
MATLAB	General Manufacturing, Transportation and Warehousing, Utilities, Finance and Insurance, Aerospace Product Manufacturing, Ship and Boat Building
Stata	Finance and Insurance

Dataset Creation

IndustryCode sources challenging coding problems from authentic industrial production environments and transforms them into anonymized benchmark instances. Dataset construction follows a four-phase pipeline:

Problem selection: representative industrial coding tasks are selected across diverse domains, including system simulation, data processing, and computational methods.
Manual revision and difficulty enhancement: problems are reformulated and hardened with mathematical constraints, algorithmic complexity, engineering coupling, and domain-specific design patterns.
Evaluation system design: each problem is paired with execution-oriented I/O test cases and, where needed, semantic evaluation criteria.
Iterative verification: automated testing, domain review, and repeated refinement are used to improve consistency and evaluation quality.

Fields

Each JSONL row describes one main industrial coding problem and its decomposed sub-problems.

problem_name: problem title
problem_id: language-specific problem identifier
problem_description_main: natural-language description of the main problem
problem_background_main: optional domain background for the main problem
problem_io: input/output specification
required_dependencies: required libraries, packages, or imports
sub_steps: list of sub-problems derived from the main problem
general_solution: optional solution field
general_tests: optional general test field

Each item in sub_steps may contain:

step_number
step_description_prompt
step_background
ground_truth_code
function_header
test_cases
return_line

Intended Use

The dataset is intended for:

benchmarking large language models on industry-oriented code generation tasks
comparing task-level code generation performance across languages and domains
studying problem decomposition and step-wise code synthesis
supporting evaluations reported in anonymous peer review submissions

The dataset is not intended to serve as a certification benchmark for production readiness, safety-critical deployment, or repository-scale software maintenance.

Responsible AI Notes

The dataset is designed for evaluating code generation systems. It does not intentionally include personally identifiable information or human-subject data. The released benchmark instances are anonymized task descriptions and evaluation artifacts rather than raw proprietary repositories.

Known limitations include:

imbalanced language coverage
underrepresentation of collaborative or infrastructure-dependent engineering tasks
partial dependence on benchmarkable task formulations rather than full production workflows

Users should inspect generated code before execution, run generated code in a sandboxed environment, and consider domain-specific safety, compliance, and correctness requirements before practical use.

Splits

Validation files are intended for development and prompt calibration. Test files are intended for final benchmark evaluation.