Replication Data for: Uncovering LLMs for Service-Composition: Challenges and Opportunities (doi:10.18419/darus-3767)

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Part 1: Document Description
Part 2: Study Description
Part 3: Data Files Description
Part 4: Variable Description
Part 5: Other Study-Related Materials
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Document Description

Citation

Title:

Replication Data for: Uncovering LLMs for Service-Composition: Challenges and Opportunities

Identification Number:

doi:10.18419/darus-3767

Distributor:

DaRUS

Date of Distribution:

2023-11-27

Version:

1

Bibliographic Citation:

Pesl, Robin D.; Stötzner, Miles; Georgievski, Ilche; Aiello, Marco, 2023, "Replication Data for: Uncovering LLMs for Service-Composition: Challenges and Opportunities", https://doi.org/10.18419/darus-3767, DaRUS, V1, UNF:6:GV+GzTPs7xXW9ITeS6uC7Q== [fileUNF]

Study Description

Citation

Title:

Replication Data for: Uncovering LLMs for Service-Composition: Challenges and Opportunities

Identification Number:

doi:10.18419/darus-3767

Authoring Entity:

Pesl, Robin D. (University of Stuttgart, Institute of Architecture of Application Systems)

Stötzner, Miles (University of Stuttgart, Institute of Software Engineering)

Georgievski, Ilche (University of Stuttgart, Institute of Architecture of Application Systems)

Aiello, Marco (University of Stuttgart, Institute of Architecture of Application Systems)

Grant Number:

19S21002

Distributor:

DaRUS

Access Authority:

Pesl, Robin D.

Depositor:

Pesl, Robin D.

Date of Deposit:

2023-11-06

Holdings Information:

https://doi.org/10.18419/darus-3767

Study Scope

Keywords:

Computer and Information Science, Automated Service Composition, Large Language Models, Automatic Programming, ChatGPT, GPT-4, Service-Oriented Architecture

Abstract:

Experimental results for the ICSOC 2023 AI-PA position paper "Uncovering LLMs for Service-Composition: Challenges and Opportunities." <br> <ul> <li><i>Exemplars</i>: List of scenarios found in the Google Scholar literature search. <li><i>Experiment 1 Service Discovery</i>: Chat history for experiment 1 asking ChatGPT for existing real services.</li> <li><i>Experiment 2 Service Composition</i>: Chat history and service composition for experiment 2 asking ChatGPT for a service composition in Python using a natural language task and the list of services from experiment 1.</li> <li><i>Experiment 3 Combined Service Discovery and Composition</i>: Chat history and service composition for experiment 3 asking ChatGPT for a service composition in Python using a natural language task without a list of services.</li> </ul> Each experiment in the dataset has its own folder (use the tree view to see the folder layout of the files). Chats in experiments 2 and 3 are accompanied by their service composition in Python from that chat as an extra file.

Date of Collection:

2023-06-24-2023-07-26

Methodology and Processing

Sources Statement

Data Access

Other Study Description Materials

Related Publications

Citation

Title:

Pesl, R.D., Stötzner, M., Georgievski, I., Aiello, M.: Uncovering LLMs for Service- Composition: Challenges and Opportunities. In: ICSOC 2023 Workshops (2023)

Bibliographic Citation:

Pesl, R.D., Stötzner, M., Georgievski, I., Aiello, M.: Uncovering LLMs for Service- Composition: Challenges and Opportunities. In: ICSOC 2023 Workshops (2023)

File Description--f265316

File: Exemplars.tab

  • Number of cases: 54

  • No. of variables per record: 9

  • Type of File: text/tab-separated-values

Notes:

UNF:6:GV+GzTPs7xXW9ITeS6uC7Q==

Variable Description

List of Variables:

Variables

Paper

f265316 Location:

Summary Statistics: StDev 16.407545434031604; Mean 30.0; Valid 54.0; Min. 1.0; Max. 57.0

Variable Format: numeric

Notes: UNF:6:P40YtQ8z4Z9B8zVcxd+yHA==

Scenario

f265316 Location:

Variable Format: character

Notes: UNF:6:uq/7uR4cIJ3SHNF47KdOWg==

Technology

f265316 Location:

Variable Format: character

Notes: UNF:6:p8sNqqIRhmbINLfPHQrIeg==

#services

f265316 Location:

Summary Statistics: StDev 2.0989665022001875; Mean 4.166666666666666; Min. 1.0; Max. 13.0; Valid 54.0

Variable Format: numeric

Notes: UNF:6:+ZG9u5OZ4Af7HB4l5M/V2w==

Cites

f265316 Location:

Summary Statistics: Mean 193.2592592592593; Valid 54.0; Min. 0.0; Max. 1913.0; StDev 335.01552682604915

Variable Format: numeric

Notes: UNF:6:MmgESDsHene4ye0LnZTveg==

Year

f265316 Location:

Summary Statistics: Max. 2022.0; Valid 54.0; Min. 2001.0; StDev 6.035071040163345; Mean 2008.7407407407406

Variable Format: numeric

Notes: UNF:6:ovwAQ8KDYB75ufV2oVseGQ==

Title

f265316 Location:

Variable Format: character

Notes: UNF:6:s8Mr4T4882Ri5669Jy0e8A==

Link

f265316 Location:

Variable Format: character

Notes: UNF:6:stRIK1aTUwg9dKZDZoTlHg==

Remarks

f265316 Location:

Variable Format: character

Notes: UNF:6:yILzxorrKMEgYSx64wSO0g==

Other Study-Related Materials

Label:

Exemplars.xlsx

Text:

List of scenarios found in the Google Scholar literature search. (The original file.)

Notes:

application/vnd.openxmlformats-officedocument.spreadsheetml.sheet

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ChatGPT_1_21.png

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ChatGPT_2_21_2.png

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composition.py

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text/x-python

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ChatGPT_2_25.png

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composition.py

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text/x-python

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composition.py

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text/x-python

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ChatGPT_2_33.png

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composition.py

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text/x-python

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ChatGPT_2_38.png

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composition.py

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text/x-python

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ChatGPT_2_57.png

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composition.py

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text/x-python

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composition.py

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text/x-python

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ChatGPT_3_25.png

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composition.py

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text/x-python

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ChatGPT_3_32.png

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composition.py

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text/x-python

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ChatGPT_3_33.png

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composition.py

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text/x-python

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ChatGPT_3_38.png

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image/png

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composition.py

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text/x-python

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ChatGPT_3_57.png

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image/png

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Label:

composition.py

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text/x-python