cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.14590935
title: [Dataset] NICE: Non-Functional Requirements Identification, Classification, and Explanation Using Small Language Models

description: This dataset is based on the original PROMISE dataset [1] and is part of the research conducted for the paper titled "NICE: Non-Functional Requirements Identification, Classification, and Explanation Using Small Language Models," accepted at the International Conference on Software Engineering (ICSE'25).

The original PROMISE dataset was introduced in the RE'17 data challenge by Cleland-Huang et al. [2]. It was further augmented by Dalpaiz et al. [3, 4] through the relabeling of Functional Requirements (FRs) and Non-Functional Requirements (NFRs) in a multi-label manner. In our work, we further relabeled the NFR sub-classes (e.g., Availability, Security, Performance) within the NFRs using the multi-label classification schema detailed in our paper. Through this repository, we present the updated, multi-label NFR version of the augmented PROMISE dataset.

We removed three duplicate entries from the augmented PROMISE dataset. Specifically, we removed the following sentences from the dataset:



"For each class within a sequence for a cohort, Program Administrators and Nursing Staff Members shall be able to specify which quarter that class will be offered."

"Only registered customers can purchase streaming movies."

"The response time shall be fast enough to maintain the flow of the game. The response time shall be no more than 2 seconds for 95% of responses and no more than 4% for the remaining responses."


After deduplication, the NFRs in the augmented PROMISE dataset were labeled using a multi-label classification scheme. The dataset consists of 16 columns, with the requirement classes labeled using binary labels (0 or 1).



ProjectID

RequirementText    

IsFunctional

IsQuality

Availability (A)

Fault Tolerance (FT)

Legal (L)

Look & Feel (LF)

Maintainability (MN)

Operability (O)

Performance (PE)

Portability (PO)

Scalability (SC)

Security (SE)

Usability (US)

Other (OT)


For the paper pre-print and the dataset license file, please visit >https://zenodo.org/records/14709254

 

References

[1] Original PROMISE dataset - https://zenodo.org/records/268542

[2] J. Cleland-Huang, R. Settimi, X. Zou, and P. Solc. “Automated classification of non-functional requirements”. In: Requirements engineering 12 (2007), pp. 103–120.

[3] Dalpiaz, F., Dell'Anna, D., Aydemir, F.B. and Çevikol, S., 2019, September. Requirements classification with interpretable machine learning and dependency parsing. In 2019 IEEE 27th International Requirements Engineering Conference (RE) (pp. 142-152). IEEE.

[4] Augmented PROMISE dataset - https://zenodo.org/records/3309669
DOI: 10.5281/zenodo.14590934
title: [Dataset] NICE: Non-Functional Requirements Identification, Classification, and Explanation Using Small Language Models

description: This dataset is based on the original PROMISE dataset [1] and is part of the research conducted for the paper titled "NICE: Non-Functional Requirements Identification, Classification, and Explanation Using Small Language Models," accepted at the International Conference on Software Engineering (ICSE'25).

The original PROMISE dataset was introduced in the RE'17 data challenge by Cleland-Huang et al. [2]. It was further augmented by Dalpaiz et al. [3, 4] through the relabeling of Functional Requirements (FRs) and Non-Functional Requirements (NFRs) in a multi-label manner. In our work, we further relabeled the NFR sub-classes (e.g., Availability, Security, Performance) within the NFRs using the multi-label classification schema detailed in our paper. Through this repository, we present the updated, multi-label NFR version of the augmented PROMISE dataset.

We removed three duplicate entries from the augmented PROMISE dataset. Specifically, we removed the following sentences from the dataset:



"For each class within a sequence for a cohort, Program Administrators and Nursing Staff Members shall be able to specify which quarter that class will be offered."

"Only registered customers can purchase streaming movies."

"The response time shall be fast enough to maintain the flow of the game. The response time shall be no more than 2 seconds for 95% of responses and no more than 4% for the remaining responses."


After deduplication, the NFRs in the augmented PROMISE dataset were labeled using a multi-label classification scheme. The dataset consists of 16 columns, with the requirement classes labeled using binary labels (0 or 1).



ProjectID

RequirementText    

IsFunctional

IsQuality

Availability (A)

Fault Tolerance (FT)

Legal (L)

Look & Feel (LF)

Maintainability (MN)

Operability (O)

Performance (PE)

Portability (PO)

Scalability (SC)

Security (SE)

Usability (US)

Other (OT)


For the paper pre-print and the dataset license file, please visit >https://zenodo.org/records/14709254

 

References

[1] Original PROMISE dataset - https://zenodo.org/records/268542

[2] J. Cleland-Huang, R. Settimi, X. Zou, and P. Solc. “Automated classification of non-functional requirements”. In: Requirements engineering 12 (2007), pp. 103–120.

[3] Dalpiaz, F., Dell'Anna, D., Aydemir, F.B. and Çevikol, S., 2019, September. Requirements classification with interpretable machine learning and dependency parsing. In 2019 IEEE 27th International Requirements Engineering Conference (RE) (pp. 142-152). IEEE.

[4] Augmented PROMISE dataset - https://zenodo.org/records/3309669
DOI: 10.15468/dl.nmytdk
title: Occurrence Download

description: A dataset containing 5 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Neosalangichthys ishikawae (Wakiya & Takahashi, 1913)",
 "Geometry POLYGON((170 20, 170 50, 120 50, 120 20, 170 20))",
 "HasCoordinate is true"
 ]
}

 The dataset includes 5 records from 3 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0024613-250127130748423/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.26nw3h
title: Occurrence Download

description: A dataset containing 464 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Oplegnathus fasciatus (Temminck & Schlegel, 1844)",
 "Geometry POLYGON((170 20, 170 50, 120 50, 120 20, 170 20))",
 "HasCoordinate is true"
 ]
}

 The dataset includes 464 records from 28 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0024614-250127130748423/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.fvxvqq
title: Occurrence Download

description: A dataset containing 2271 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Bupleurum scorzonerifolium Willd."
 ]
}

 The dataset includes 2271 records from 84 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0024615-250127130748423/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.x87ny2
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Scaradon fasciatus Temminck & Schlegel, 1844",
 "Geometry POLYGON((170 20, 170 50, 120 50, 120 20, 170 20))",
 "HasCoordinate is true"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0024616-250127130748423/datasets/export for details.
DOI: 10.6084/m9.figshare.28262426
title: Hydrangea

description: Hydrangea is a defect library for LLM-enabled software. Hydrangea has 4 main petals, each corresponding to one of the major components where defects often arise: LLM agent, vector database, software component, and system.This repository is made available under the Public Domain Dedication and License v1.0 whose full text can be found at: http://opendatacommons.org/licenses/pddl/1.0/ - see the LICENSE file for details.What is LLM-enabled software?It is software that integrates LLMs (large language models) with RAG (retrieval-augmented generation ) support to realize intelligence features.It contains four components:<b>LLM agent</b> that manages LLM interfaces, constructs prompts, and invokes the LLM<b>Vector database</b> that supports RAG algorithm and enhances the LLM agent<b>Software component</b> that interacts with the first two components to perform certain tasks<b>System</b> that manages resources and privileges to carry out the executionWhat's inside the artifact:For enhanced availability and reusability, we offer an organized defect library utilized in our manual studies.Below are details of what is included in each part:Application benchmarkA suite of 100 non-trivial projects which tightly integrates LLMs and vector databases in their workflow.We have uploaded application.csv, it contains:software project nameGitHub link and commit IDclassificationused LLM and vector databaseHydrangea Defect LibraryThe result of TABLE Ⅱ in our paper can be reproduced by this organized defect library.In the uploaded defect.csv, we have documented different cases for the same defect type, as defects can manifest in various ways. For each distinct case of the same defect, we have separated them with a blank line and labeled them as case 1, case 2, and so on, according to the specific circumstances.It contains:A collection of defects in these projects (involves 100 projects),containingthe defect type and its detailed explanationthe exact file and source-code line location of the defectthe consequences of defectthe defect-triggering testsThe meaning of different columns in defect.csv:<b>APP</b>: the applications from GitHub.<b>commit url</b>: the relevant version of the application on GitHub.<b>types</b>: different defect types.<b>cases</b>: different examples for each defect type. Cells containing a "/" indicate that there is only one case for that defect type.<b>explanation</b>: details of the defect.<b>consequences</b>: the impacts of the defect. Here we use the abbreviations: ST refer to fail-stops, IC refer to incorrectness, SL refer to slower execution, UI refer to unfriendly user interface, TK refer to more tokens, and IS refer to insecure.<b>source-code locations</b>: The location of the code file where the defect occurs.<b>defect-triggering tests</b>: The software input that triggers the defect.<br>
DOI: 10.6084/m9.figshare.28262426.v2
title: Hydrangea

description: Hydrangea is a defect library for LLM-enabled software. Hydrangea has 4 main petals, each corresponding to one of the major components where defects often arise: LLM agent, vector database, software component, and system.What is LLM-enabled software?It is software that integrates LLMs (large language models) with RAG (retrieval-augmented generation ) support to realize intelligence features.It contains four components:<b>LLM agent</b> that manages LLM interfaces, constructs prompts, and invokes the LLM<b>Vector database</b> that supports RAG algorithm and enhances the LLM agent<b>Software component</b> that interacts with the first two components to perform certain tasks<b>System</b> that manages resources and privileges to carry out the executionWhat's inside the artifact:For enhanced availability and reusability, we offer an organized defect library utilized in our manual studies.Below are details of what is included in each part:Application benchmarkA suite of 100 non-trivial projects which tightly integrates LLMs and vector databases in their workflow.We have uploaded <code>application.csv</code>, it contains:software project nameGitHub link and commit IDclassificationused LLM and vector databaseHydrangea Defect LibraryThe result of TABLE Ⅱ in our paper can be reproduced by this organized defect library.In the uploaded <code>defect.csv</code>, we have documented different cases for the same defect type, as defects can manifest in various ways. For each distinct case of the same defect, we have separated them with a blank line and labeled them as case 1, case 2, and so on, according to the specific circumstances.It contains:A collection of defects in these projects (involves 100 projects),containingthe defect type and its detailed explanationthe exact file and source-code line location of the defectthe consequences of defectthe defect-triggering tests
DOI: 10.26179/146h-9b03
title: Orthomosaic and digital surface model of Edgeworth David Camp, Bunger Hills, 06 February 2023
DOI: 10.15468/dl.dc6zh6
title: Occurrence Download

description: A dataset containing 21079 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Heteromeles arbutifolia (Lindl.) M.Roem.",
 "CoordinateUncertaintyInMeters is less than 500"
 ]
}

 The dataset includes 21079 records from 43 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0024617-250127130748423/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.k4e7ge
title: Occurrence Download

description: A dataset containing 78 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Panulirus japonicus (Von Siebold, 1824)",
 "Geometry POLYGON((170 20, 170 50, 120 50, 120 20, 170 20))",
 "HasCoordinate is true"
 ]
}

 The dataset includes 78 records from 9 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0024618-250127130748423/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.14854430
title: PAGETologia Castille-Leon epidemiology one health hypothesis

description: Pagetology Study: Epidemiological Study of Paget's Disease of Bone (PDB) in the Castilla y León Region, Spain.

This study evaluates new cases of PDB between 2009 and 2019 in relation to the area's population. It aims to identify an association between the disease and occupational activities, primarily agriculture. Ecological analyses compare incidence rates across different regions based on occupational activities.

The datasets provided include new cases of PDB, population data for those years, and the number of animals.
DOI: 10.5281/zenodo.14854431
title: PAGETologia Castille-Leon epidemiology one health hypothesis

description: Pagetology Study: Epidemiological Study of Paget's Disease of Bone (PDB) in the Castilla y León Region, Spain.

This study evaluates new cases of PDB between 2009 and 2019 in relation to the area's population. It aims to identify an association between the disease and occupational activities, primarily agriculture. Ecological analyses compare incidence rates across different regions based on occupational activities.

The datasets provided include new cases of PDB, population data for those years, and the number of animals.
DOI: 10.15468/dl.xwwn4a
title: Occurrence Download

description: A dataset containing 744 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is China",
 "TaxonKey is Bupleurum scorzonerifolium Willd."
 ]
}

 The dataset includes 744 records from 25 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0024621-250127130748423/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.6084/m9.figshare.28379513
title: Table S3

description: R1 and R3 SNP matrix
DOI: 10.6084/m9.figshare.28379513.v1
title: Table S3

description: R1 and R3 SNP matrix
DOI: 10.15468/dl.7zwf49
title: Occurrence Download

description: A dataset containing 2 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Palinurus japonicus Von Siebold, 1824",
 "Geometry POLYGON((170 20, 170 50, 120 50, 120 20, 170 20))",
 "HasCoordinate is true"
 ]
}

 The dataset includes 2 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0024622-250127130748423/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.473b9r
title: Occurrence Download

description: A dataset containing 136596 species occurrences available in GBIF matching the query:
{
 "and" : [
 {
 "and" : [
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Living Specimen)"
 ]
 }
 }
 ]
 },
 "TaxonKey is Campanula glomerata L."
 ]
}

 The dataset includes 136596 records from 983 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0024612-250127130748423/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.bgurcs
title: Occurrence Download

description: A dataset containing 3148 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is Occurrence data of seagrasses in Southeast Asia extracted from literature"
 ]
}

 The dataset includes 3148 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0024623-250127130748423/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.xjkwbb
title: Occurrence Download

description: A dataset containing 200 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Dicerorhinus sumatrensis (G.Fischer, 1814)"
 ]
}

 The dataset includes 200 records from 29 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0024624-250127130748423/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.ttc6be
title: Occurrence Download

description: A dataset containing 268 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Laemonema longipes Schmidt, 1938",
 "Geometry POLYGON((170 20, 170 50, 120 50, 120 20, 170 20))",
 "HasCoordinate is true"
 ]
}

 The dataset includes 268 records from 10 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0024625-250127130748423/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.3dmky7
title: Occurrence Download

description: A dataset containing 284807181 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is United States of America",
 "Month is one of (January, February, October, November)"
 ]
}

 The dataset includes 284807181 records from 2880 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0024610-250127130748423/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.6084/m9.figshare.24104284
title: Additional file 11 of Transcriptome sequencing and metabolome analysis reveal the metabolic reprogramming of partial hepatectomy and extended hepatectomy

description: Additional file 11: Table S4. Primers for DEGs q-PCR analysis.
DOI: 10.6084/m9.figshare.24104284.v1
title: Additional file 11 of Transcriptome sequencing and metabolome analysis reveal the metabolic reprogramming of partial hepatectomy and extended hepatectomy

description: Additional file 11: Table S4. Primers for DEGs q-PCR analysis.
DOI: 10.6084/m9.figshare.24104417
title: Additional file 7 of The gut microbiome changes in wild type and IL-18 knockout mice after 9.0 Gy total body irradiation

description: Supp Table 1. Detailed number of faecal samples collected.
DOI: 10.6084/m9.figshare.24104417.v1
title: Additional file 7 of The gut microbiome changes in wild type and IL-18 knockout mice after 9.0 Gy total body irradiation

description: Supp Table 1. Detailed number of faecal samples collected.
DOI: 10.6084/m9.figshare.24104420
title: Additional file 8 of The gut microbiome changes in wild type and IL-18 knockout mice after 9.0 Gy total body irradiation

description: Supp Table 2. General statistics of the 372 16S sequencing files.
DOI: 10.6084/m9.figshare.24104420.v1
title: Additional file 8 of The gut microbiome changes in wild type and IL-18 knockout mice after 9.0 Gy total body irradiation

description: Supp Table 2. General statistics of the 372 16S sequencing files.
DOI: 10.6084/m9.figshare.24104423
title: Additional file 9 of The gut microbiome changes in wild type and IL-18 knockout mice after 9.0 Gy total body irradiation

description: Supp Table 3. Detailed list of significantly changed bacterial genera of the pure IL-18 knockout and wild type mice at specific time points after irradiation compared to their d0 samples respectively.
DOI: 10.6084/m9.figshare.24104423.v1
title: Additional file 9 of The gut microbiome changes in wild type and IL-18 knockout mice after 9.0 Gy total body irradiation

description: Supp Table 3. Detailed list of significantly changed bacterial genera of the pure IL-18 knockout and wild type mice at specific time points after irradiation compared to their d0 samples respectively.
DOI: 10.6084/m9.figshare.24104426.v1
title: Additional file 10 of The gut microbiome changes in wild type and IL-18 knockout mice after 9.0 Gy total body irradiation

description: Supp Table 4. Detailed list of significantly changed bacteria of the pure IL-18 knockout and wild type mice.
DOI: 10.6084/m9.figshare.24104426
title: Additional file 10 of The gut microbiome changes in wild type and IL-18 knockout mice after 9.0 Gy total body irradiation

description: Supp Table 4. Detailed list of significantly changed bacteria of the pure IL-18 knockout and wild type mice.
DOI: 10.6084/m9.figshare.24104429
title: Additional file 11 of The gut microbiome changes in wild type and IL-18 knockout mice after 9.0 Gy total body irradiation

description: Supp Table 5. Detailed list of significantly correlated bacteria genera of the pure IL-18 knockout and wild type mice.
DOI: 10.6084/m9.figshare.24104429.v1
title: Additional file 11 of The gut microbiome changes in wild type and IL-18 knockout mice after 9.0 Gy total body irradiation

description: Supp Table 5. Detailed list of significantly correlated bacteria genera of the pure IL-18 knockout and wild type mice.
DOI: 10.6084/m9.figshare.24104386
title: Additional file 1 of Establishment of a predictive model for postpartum hemorrhage in twins: a retrospective study

description: Additional file 1.
DOI: 10.6084/m9.figshare.24104386.v1
title: Additional file 1 of Establishment of a predictive model for postpartum hemorrhage in twins: a retrospective study

description: Additional file 1.
DOI: 10.15468/dl.5pgpce
title: Occurrence Download

description: A dataset containing 36 species occurrences available in GBIF matching the query:
{
 "Geometry" : [
 "MULTIPOLYGON (((148.108989 -33.853706, 148.113481 -33.853706, 148.113481 -33.849214, 148.108989 -33.849214, 148.108989 -33.853706)), ((148.108989 -33.853706, 148.104498 -33.853706, 148.104498 -33.855952, 148.108989 -33.855952, 148.108989 -33.853706)))"
 ]
}

 The dataset includes 36 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0069813-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.6084/m9.figshare.26737800.v1
title: Additional file 1 of Clinical results with a multifocal intraocular lens with a novel optical design

description: Supplementary Material 1.
DOI: 10.6084/m9.figshare.24104447
title: Additional file 2 of Review on infection control strategies to minimize outbreaks of the emerging pathogen Elizabethkingia anophelis

description: Supplementary Material 2
DOI: 10.6084/m9.figshare.24104447.v1
title: Additional file 2 of Review on infection control strategies to minimize outbreaks of the emerging pathogen Elizabethkingia anophelis

description: Supplementary Material 2