cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.25921/fsyw-4803
title: Variability of surface water fCO2 during seasonal upwelling in the equatorial Atlantic Ocean as observed by a drifting buoy from 1997-06-19 to 1997-09-16 (NCEI Accession 0157739)

description: This dataset includes Surface underway, chemical, meteorological, optical and physical data collected from a buoy in the North Atlantic Ocean and South Atlantic Ocean as part of the CARIOCA project from 1997-06-19 to 1997-09-16. These data include BAROMETRIC PRESSURE, FLUORESCENCE, Partial pressure (or fugacity) of carbon dioxide - water and SEA SURFACE TEMPERATURE. The instruments used to collect these data include Carbon dioxide (CO2) gas analyzer and Micro-porous membrane equilibrator.

These data were collected by Jacqueline Boutin of Universite Pierre et Marie Curie; Laboratoire d'Océanographie Dynamique et de Climatologie (LODYC) and Dorothee C. E. Bakker of University of East Anglia; School of Environmental Sciences as part of the CARIOCA Buoy 1997 fCO2 Data dataset. CDIAC associated the following cruise ID(s) with this dataset: CARIOCA_1997
DOI: 10.15468/dl.qgpa3q
title: Occurrence Download

description: A dataset containing 56593 species occurrences available in GBIF matching the query:
{
 "and" : [
 "PublishingOrg is 5f2df235-914f-4cc9-b247-08fb981e8b8a",
 "TaxonKey is Animalia"
 ]
}

 The dataset includes 56593 records from 9 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0011742-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.25921/1whg-4j10
title: Mangrove study examining seasonal and spatial variation in fish taxonomic composition and diversity in North Atlantic Ocean from 1998-08-17 to 2023-09-01 (NCEI Accession 0159580)

description: This data contains seasonal and spatial variation in fish taxonomic composition and diversity as well as variation in the frequency of occurrence, density and size structure of dominant fish taxa that occupy these mangrove lined shorelines.
DOI: 10.7289/v57942wc
title: Oceanographic data and ROV dive-related multimedia and information collected during the EX1608 (FY17 Ship and ROV Shakedown) expedition on NOAA Ship OKEANOS EXPLORER in the North Pacific Ocean from 2016-12-01 to 2016-12-08 (NCEI Accession 0159849)

description: This dataset contains oceanographic data collected in Honolulu, Hawaii. This cruise included shakedown and engineering tests for both the ship and the Office of Ocean Exploration and Research (OER), and Global Foundation and Ocean Exploration (GFOE) ROV and telepresence systems. Operations used the ship’s deep water mapping system (Kongsberg EM302 multibeam sonar, EK60 split-beam fisheries sonars, ADCPs, and Knudsen 3260 chirp sub-bottom profiler sonar), NOAA’s two-body 6000m remotely operated vehicles (ROVs Deep Discoverer and Seirios, and the ship’s high-bandwidth satellite connection for real-time ship to shore communications. The ship conducted 24-hour operations consisting of daytime ROV dives, with ship shakedown items and evening/nighttime mapping operations and DP testing.
DOI: 10.5281/zenodo.17735859
title: IJIM Dataset & Experimental Results

description: This repository contains the experimental data and analysis for a research study demonstrating how **Test-Driven Prompting (TDP)** significantly improves AI code generation across multiple programming languages and difficulty levels. All experimental data, statistical analysis, and qualitative comparisons are included.


## What is Test-Driven Prompting?


Instead of just asking an AI to write code, Test-Driven Prompting includes example test cases in the prompt. This helps the AI understand exactly what the code should do, similar to how human programmers use test-driven development.


![alt text](methodology_overview.png)


## Key Findings


Our study tested 4 different AI models (GPT-4, Claude, Qwen) on Android (Java) and iOS (Swift) and found:


- 🎯 First mobile evaluation: While TDP has mainly been studied for Python, this is the first empirical study of TDP in mobile development (Java, Swift).

- 🔬 Scope & scale: 8,704 evaluations across 544 programming tasks (HumanEval, MBPP), comparing two prompting strategies (base, test-driven) and four LLMs (GPT-4o, GPT-4o-mini, Qwen 14B, Qwen 32B).

- 📈 Measured effect: Average accuracy increase of +2.22 percentage points (pp) over baseline for TDP (95% CI [1.22–3.23 pp], p < 0.001, d = 0.3974).

- 📉 Platform differences: LLMs perform worse on mobile languages (66.85%–88.87%) than on Python (86.90%–91.30%), and exhibit reduced responsiveness to TDP in mobile development.

- ⚖️ Practical guidance: We provide recommendations for choosing trade-offs (max accuracy vs. budget vs. self-hosted) and offer platform-specific suggestions for applying TDP.


TDP is a reliable, low-overhead prompt engineering method for mobile app development that integrates smoothly with existing test-driven workflows; we recommend researchers and practitioners adopt TDP as a standard part of LLM-assisted mobile development.


## Authors


**Muhammad Rizqullah** (<mrizqullah@stu.kau.edu.sa>) and **Emad Albassam** (<ealbassam@kau.edu.sa>)

Computer Science Department, King Abdulaziz University, Jeddah, Saudi Arabia


*Corresponding author: Muhammad Rizqullah. Any enquiries about the research should be directed to him.*


## Repository Structure


- `datasets/` - Programming problems and test cases from HumanEval, MBPP, and Code Contests

- `raw_results/` - Complete experimental results for each AI model and dataset combination

- `results/` - Statistical analysis and comparison reports
DOI: 10.5281/zenodo.17735860
title: IJIM Dataset & Experimental Results

description: This repository contains the experimental data and analysis for a research study demonstrating how **Test-Driven Prompting (TDP)** significantly improves AI code generation across multiple programming languages and difficulty levels. All experimental data, statistical analysis, and qualitative comparisons are included.


## What is Test-Driven Prompting?


Instead of just asking an AI to write code, Test-Driven Prompting includes example test cases in the prompt. This helps the AI understand exactly what the code should do, similar to how human programmers use test-driven development.


![alt text](methodology_overview.png)


## Key Findings


Our study tested 4 different AI models (GPT-4, Claude, Qwen) on Android (Java) and iOS (Swift) and found:


- 🎯 First mobile evaluation: While TDP has mainly been studied for Python, this is the first empirical study of TDP in mobile development (Java, Swift).

- 🔬 Scope & scale: 8,704 evaluations across 544 programming tasks (HumanEval, MBPP), comparing two prompting strategies (base, test-driven) and four LLMs (GPT-4o, GPT-4o-mini, Qwen 14B, Qwen 32B).

- 📈 Measured effect: Average accuracy increase of +2.22 percentage points (pp) over baseline for TDP (95% CI [1.22–3.23 pp], p < 0.001, d = 0.3974).

- 📉 Platform differences: LLMs perform worse on mobile languages (66.85%–88.87%) than on Python (86.90%–91.30%), and exhibit reduced responsiveness to TDP in mobile development.

- ⚖️ Practical guidance: We provide recommendations for choosing trade-offs (max accuracy vs. budget vs. self-hosted) and offer platform-specific suggestions for applying TDP.


TDP is a reliable, low-overhead prompt engineering method for mobile app development that integrates smoothly with existing test-driven workflows; we recommend researchers and practitioners adopt TDP as a standard part of LLM-assisted mobile development.


## Authors


**Muhammad Rizqullah** (<mrizqullah@stu.kau.edu.sa>) and **Emad Albassam** (<ealbassam@kau.edu.sa>)

Computer Science Department, King Abdulaziz University, Jeddah, Saudi Arabia


*Corresponding author: Muhammad Rizqullah. Any enquiries about the research should be directed to him.*


## Repository Structure


- `datasets/` - Programming problems and test cases from HumanEval, MBPP, and Code Contests

- `raw_results/` - Complete experimental results for each AI model and dataset combination

- `results/` - Statistical analysis and comparison reports
DOI: 10.3334/cdiac/otg.soop_colibri_lines_2016
title: Surface underway measurements of partial pressure of carbon dioxide (pCO2) in the Atlantic Ocean during the M/N Colibri Ships of Opportunity (SOOP) lines in 2016 (NCEI Accession 0160554)

description: This dataset includes surface underway, chemical, meteorological and physical data collected from MN Colibri in the English Channel and North Atlantic Ocean in 2016. These data include barometric pressure, partial pressure of carbon dioxide - atmosphere, partial pressure of carbon dioxide - water, sea surface salinity and temperature. The instruments used to collect these data include Carbon dioxide (CO2) gas analyzer. These data were collected by Denis Diverrès of French National Research Institute for Sustainable Development (IRD) and Nathalie Lefèvre of Sorbonne University (SU) as part of the VOS_Colibri_Line_2016 dataset.
DOI: 10.3334/cdiac/otg.soccom_096u20160426_uw
title: Partial pressure (or fugacity) of carbon dioxide, salinity and other variables collected from Surface underway observations using Barometric pressure sensor, Carbon dioxide (CO2) gas analyzer and other instruments from Investigator in the North Pacific Ocean, South Pacific Ocean and Southern Oceans from 2016-04-26 to 2016-06-29 (NCEI Accession 0160555)

description: This dataset includes Surface underway, chemical, meteorological and physical data collected from Investigator in the North Pacific Ocean, South Pacific Ocean and Southern Oceans (&gt; 60 degrees South) from 2016-04-26 to 2016-06-29. These data include AIR-SEA DIFFERENCE - PARTIAL PRESSURE (OR FUGACITY) OF CARBON DIOXIDE, BAROMETRIC PRESSURE, Partial pressure (or fugacity) of carbon dioxide - atmosphere, Partial pressure (or fugacity) of carbon dioxide - water, SALINITY, SEA SURFACE TEMPERATURE, WIND DIRECTION and WIND SPEED. The instruments used to collect these data include Barometric pressure sensor and Carbon dioxide (CO2) gas analyzer.

These data were collected by Bronte Tilbrook, Craig Neill, and John Akl of Commonwealth Scientific and Industrial Research Organization (CSIRO) as part of the SOCCOM_096U20160426_UW dataset. CDIAC associated the following cruise ID(s) with this dataset: 096U20160426
DOI: 10.3334/cdiac/otg.vos_aa_2016
title: Integrated Marine Observing System (IMOS) sea surface and atmospheric fCO2 measurements in the Southern Ocean onboard R/V Aurora Australis and R/V Investigator in 2016 (NCEI Accession 0160556)

description: This dataset includes Surface underway, chemical, meteorological and physical data collected from R/V Aurora Australis and R/V Investigator in the Indian Ocean, South Pacific Ocean, Southern Oceans and Tasman Sea from 2016-01-11 to 2017-01-20. These data include AIR-SEA DIFFERENCE - PARTIAL PRESSURE (OR FUGACITY) OF CARBON DIOXIDE, BAROMETRIC PRESSURE, Partial pressure (or fugacity) of carbon dioxide - atmosphere, Partial pressure (or fugacity) of carbon dioxide - water, SALINITY, SEA SURFACE TEMPERATURE, WIND DIRECTION and WIND SPEED. The instruments used to collect these data include Barometric pressure sensor and Carbon dioxide (CO2) gas analyzer.

These data were collected by Bronte Tilbrook, John Akl and Craig Neill of Commonwealth Scientific and Industrial Research Organization.
DOI: 10.3334/cdiac/otg.socat_v3_grid
title: Surface Ocean CO2 Atlas (SOCAT) version 3 from 1968-11-16 to 2013-12-31 (NCEI Accession 0160918)

description: This dataset includes the Surface Ocean CO2 Atlas (SOCAT) version 3. These data include surface underway, chemical, meteorological, navigational and physical data collected from unknown platforms in the world-wide oceans from 1968-11-16 to 2013-12-31. These data include BAROMETRIC PRESSURE, LATITUDE, LONGITUDE, Partial pressure (or fugacity) of carbon dioxide - water, SALINITY and SEA SURFACE TEMPERATURE.

The Surface Ocean CO2 Atlas (SOCAT) is an international effort, endorsed by the International Ocean Carbon Coordination Project (IOCCP), the Surface Ocean Lower Atmosphere Study (SOLAS) and the Integrated Marine Biogeochemistry and Ecosystem Research program (IMBER), to deliver a uniformly quality-controlled surface ocean CO2 database.
DOI: 10.15468/dl.5mqkp5
title: Occurrence Download

description: A dataset containing 411436 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Switzerland",
 "DatasetKey is one of (EOD – eBird Observation Dataset, Swiss National Butterflies and Forester Moths Databank, Swiss National Mammal Databank, Swiss National Dragonflies Databank, Swiss National Grasshoppers Databank, Swiss National Fauna Databank, Swiss National Apoidea Databank, Swiss National Amphibian Databank, iNaturalist Research-grade Observations, Swiss National Coleoptera Databank)",
 "Geometry POLYGON((8.40378 47.33313,8.69895 47.33313,8.69895 47.50088,8.40378 47.50088,8.40378 47.33313))",
 "OccurrenceStatus is Present",
 "TaxonKey is Animalia",
 "Year 2005-2025"
 ]
}

 The dataset includes 411436 records from 10 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0011709-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.emjhw2
title: Occurrence Download

description: A dataset containing 5325 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Bungarus",
 "HasCoordinate is TRUE"
 ]
}

 The dataset includes 5325 records from 50 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0011753-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.7289/v5kw5d97
title: Global Ocean Data Analysis Project, Version 2 (GLODAPv2) (NCEI Accession 0162565)

description: This data product is composed of data from 724 scientific cruises covering the global ocean. It includes data assembled during the previous interior ocean data synthesis efforts GLODAPv1.1 (Global Ocean Data Analysis Project version 1.1) in 2004, CARINA (CARbon IN the Atlantic) in 2009/2010, and PACIFICA (PACIFic ocean Interior CArbon) in 2013, as well as data from an additional 168 cruises. This dataset includes discrete bottle measurements of salinity, oxygen, nitrate, silicate, phosphate, dissolved inorganic carbon, total alkalinity, pH, CFC-11, CFC-12, CFC-113, and CCl4, carbon isotopes and chlorophyll. These data have been subjected to extensive primary and secondary quality control which included systematic evaluation of bias, and adjustments have been applied to remove significant biases, respecting occurrences of any known or likely time trends or variations.
DOI: 10.25921/wax2-kk29
title: Oceanographic data and information collected during the EX1706 Johnston Atoll (ROV/Mapping) expedition on NOAA Ship OKEANOS EXPLORER in the Pacific Ocean from 2017-07-07 to 2017-08-02 (NCEI Accession 0165181)

description: This dataset contains oceanographic data collected in and around the Johnston Atoll Unit (JAU) of the Pacific Remote Islands Marine National Monument, the U.S. EEZ around Hawaii, and the high seas during transit to and from JAU. Operations included the use of the ship’s Acoustic Doppler Current Profilers (ADCP), Scientific Computer System (SCS) data acquisition system designed for oceanographic and fisheries applications, and the ship’s high-bandwidth satellite connection for continuous real-time ship-to-shore communications. Underway CTD and XBT casts were also conducted, as well as use of OER’s 6000 m two-body ROV Deep Discoverer and Seirios.
DOI: 10.15468/dl.ahgkqq
title: Occurrence Download

description: A dataset containing 565 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "TaxonKey is Lutjanus malabaricus",
 "Year 2000-2025"
 ]
}

 The dataset includes 565 records from 32 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0011754-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.7289/v5cr5rkq
title: Partial pressure (or fugacity) of carbon dioxide, temperature, and other variables collected from surface underway observations using carbon dioxide gas analyzer, shower head equilibrator and other instruments from R/V Hakuho Maru Cruises in the North Pacific Ocean between 2011-12-01 and 2013-05-01 (NCEI Accession 0166708)

description: This dataset includes surface underway, chemical, meteorological and physical data collected from R/V Hakuho Maru Cruises in the North Pacific Ocean between 2011-12-01 and 2013-05-01. These data include measurements of mole fraction of CO2 in ambient atmosphere in dry air, mole fraction of CO2 in air from equilibrator in dry air, atmospheric pressure, sea surface temperature and sea surface salinity. These data were collected by Naohiro Kosugi, Masao Ishii and Daisuke Sasano of Meteorological Research Institute, Japan.
DOI: 10.7289/v5qz287g
title: Partial pressure (or fugacity) of carbon dioxide, sea surface temperature, sea surface salinity and barometric pressure collected from the Mooring PIRATA_8N38W deployments in the Atlantic Ocean (NCEI Accession 0167529)

description: This dataset includes chemical, physical, meteorological, and time series data collected from Mooring PIRATA_8N38W deployments in the Atlantic Ocean from 2008-04-20 to 2013-10-13. These data include mole fraction of CO2 in air in equilibrium with the seawater at sea surface temperature and measured humidity, sea surface temperature in degrees Celsius, sea surface salinity, and atmospheric pressure.
DOI: 10.7289/v58s4n54
title: Partial pressure (or fugacity) of carbon dioxide, salinity and other variables collected from surface underway observations using carbon dioxide (CO2) gas analyzer, shower head chamber equilibrator for autonomous carbon dioxide (CO2) measurement and other instruments from R/V Keifu Maru II in the Pacific Ocean, East China Sea and Sea of Japan in 2015 (NCEI Accession 0169101)

description: This dataset includes Surface underway data collected from R/V Keifu Maru II in the Pacific Ocean, East China Sea and Sea of Japan, from 2015-01-08 to 2015-11-30. These data include barometric pressure, partial pressure (or fugacity) of carbon dioxide - atmosphere, partial pressure (or fugacity) of carbon dioxide - water, sea surface salinity and sea surface temperature. The instruments used to collect these data include carbon dioxide (CO2) gas analyzer, shower head chamber equilibrator for autonomous carbon dioxide (CO2) measurement. These data were collected by Shu Saito of Japan Meteorological Agency (JMA) as part of the SOOP_Keifu_Maru_II_2015 dataset.
DOI: 10.7289/v5513wg5
title: Partial pressure (or fugacity) of carbon dioxide, salinity and other variables collected from surface underway observations using carbon dioxide (CO2) gas analyzer, shower head chamber equilibrator for autonomous carbon dioxide (CO2) measurement and other instruments from R/V Ryofu Maru III in the Pacific Ocean and East China Sea from 2014-03-07 to 2015-12-12 (NCEI Accession 0169110)

description: This dataset includes Surface underway data collected from R/V Ryofu Maru III in the Pacific Ocean and East China Sea from 2014-03-07 to 2015-12-12. These data include barometric pressure, partial pressure (or fugacity) of carbon dioxide - atmosphere, partial pressure (or fugacity) of carbon dioxide - water, sea surface salinity and sea surface temperature. The instruments used to collect these data include carbon dioxide (CO2) gas analyzer, shower head chamber equilibrator for autonomous carbon dioxide (CO2) measurement. These data were collected by Shu Saito of Japan Meteorological Agency (JMA) as part of the SOOP_Ryofu_Maru_III_2014_2015 dataset.
DOI: 10.7289/v5n29v64
title: Integrated Marine Observing System (IMOS) sea surface and atmospheric fCO2 measurements in the Southern Ocean onboard R/V Aurora Australis in 2017 (NCEI Accession 0169479)

description: This dataset includes surface underway, chemical, meteorological and physical data collected from R/V Aurora Australis in the Indian Ocean, South Pacific Ocean, Southern Oceans from 2017-01-25 to 2018-01-11. These data include air-sea difference of partial pressure of carbon dioxide (pCO2), barometric pressure, pCO2 in atmosphere, pCO2 in water, sea surface salinity, sea surface temperature, wind speed and direction. The instruments used to collect these data include Barometric pressure sensor and Carbon dioxide (CO2) gas analyzer. These data were collected by Bronte Tilbrook, John Akl and Craig Neill of Commonwealth Scientific and Industrial Research Organization.
DOI: 10.7289/v5rv0kz4
title: Integrated Marine Observing System (IMOS) sea surface and atmospheric fCO2 measurements in the Southern Ocean onboard R/V Investigator in 2017 (NCEI Accession 0169488)

description: This dataset includes Surface underway, chemical, meteorological and physical data collected from R/V Investigator in the Indian Ocean, South Pacific Ocean, Southern Oceans from 2017-01-14 to 2017-09-17. These data include partial pressure (or fugacity) of carbon dioxide, barometric pressure, partial pressure (or fugacity) of carbon dioxide - atmosphere, partial pressure (or fugacity) of carbon dioxide - water, salinity, sea surface temperature, wind direction and wind speed. The instruments used to collect these data include Barometric pressure sensor and carbon dioxide (CO2) gas analyzer. These data were collected by Bronte Tilbrook, John Akl and Craig Neill of Commonwealth Scientific and Industrial Research Organization.
DOI: 10.7289/v5q23xjs
title: Monitoring of the atmosphere-ocean carbon dioxide exchange by the ship of opportunity (SOOP) during the M/S Trans Future-5 line cruises in 2016 (NCEI Accession 0169730)

description: This dataset includes surface underway, chemical, meteorological and physical data collected from M/S Trans Future 5 in the, North Pacific Ocean, Philippine Sea, Solomon Sea, South Pacific Ocean and Tasman Sea from 2016-01-12 to 2017-01-10. These data include air-sea difference of partial pressure of CO2, partial pressure of carbon dioxide in atmosphere, partial pressure of carbon dioxide in water, relative humidity, absolute humidity, sea surface salinity, sea surface temperature, air temperature, barometric pressure, and wind direction and speed. The instruments used to collect these data include barometric pressure sensor, carbon dioxide (CO2) gas analyzer, shower head chamber equilibrator for autonomous carbon dioxide (CO2) measurement and thermosalinographs. These data were collected by Shin-ichiro Nakaoka and Yukihiro Nojiri of National Institute for Environmental Studies as part of the SOOP_Trans_Future_5_2016 lines data.
DOI: 10.7289/v5kd1w5w
title: Monitoring of the atmosphere-ocean carbon dioxide exchange by the ship of opportunity (SOOP) during the M/S New Century 2 line cruises in 2016 (NCEI Accession 0169950)

description: This dataset includes surface underway, chemical, meteorological and physical data collected from M/S New Century 2 in the North Pacific Ocean, Caribbean Sea, North Atlantic Ocean from 2016-01-03 to 2016-11-03. These data include absolute humidity, air temperature, air-sea difference - partial pressure of carbon dioxide, barometric pressure, partial pressure of carbon dioxide - atmosphere, partial pressure of carbon dioxide - water, relative humidity, sea surface salinity, sea surface temperature and wind direction and speed. The instruments used to collect these data include barometric pressure sensor, carbon dioxide (CO2) gas analyzer, shower head chamber equilibrator for autonomous carbon dioxide (CO2) measurement and thermosalinographs. These data were collected by Shin-ichiro Nakaoka of National Institute for Environmental Studies as part of the SOOP New Century-2 2016 lines data.