Query Expansion Based on User Requirements Clustering for Finding Feature Location

Achmad Arwan; Siti Rochimah; Chastine Fatichah

doi:10.1109/ICITISEE57756.2022.10057893

Query Expansion Based on User Requirements Clustering for Finding Feature Location

Achmad Arwan^*
, Siti Rochimah
, Chastine Fatichah

^*Corresponding author for this work

Informatics Department
Institut Teknologi Sepuluh Nopember

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

3 Citations (Scopus)

Abstract

Feature Location is an approach of how to determine the code area based on high level software artifacts. Use Case Scenarios (UCS) are requirements documents in software artifacts that contain many words. A sentence in a UCS is sometimes described by a sentence in other UCS, so capture the relationship among UCS may be advantageous in finding feature locations. The research contribution is how to find feature locations better by making an expansion to query based on UCS clustering. The method was clustering the UCS using k-medoids clustering and index the source code using latent dirichlet allocation. The results was 56.8% for the best recall rate.

Original language	English
Title of host publication	Proceeding - 6th International Conference on Information Technology, Information Systems and Electrical Engineering
Subtitle of host publication	Applying Data Sciences and Artificial Intelligence Technologies for Environmental Sustainability, ICITISEE 2022
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	149-153
Number of pages	5
ISBN (Electronic)	9798350399615
DOIs	https://doi.org/10.1109/ICITISEE57756.2022.10057893
Publication status	Published - 2022
Event	6th International Conference on Information Technology, Information Systems and Electrical Engineering, ICITISEE 2022 - Virtual, Online, Indonesia Duration: 13 Dec 2022 → 14 Dec 2022

Publication series

Name	Proceeding - 6th International Conference on Information Technology, Information Systems and Electrical Engineering: Applying Data Sciences and Artificial Intelligence Technologies for Environmental Sustainability, ICITISEE 2022

Conference

Conference	6th International Conference on Information Technology, Information Systems and Electrical Engineering, ICITISEE 2022
Country/Territory	Indonesia
City	Virtual, Online
Period	13/12/22 → 14/12/22

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 7 Affordable and Clean Energy

Keywords

Clustering
Feature location
Latent Dirichlet Allocation
Use Case Scenario
research

Access to Document

10.1109/ICITISEE57756.2022.10057893

Cite this

Arwan, A., Rochimah, S., & Fatichah, C. (2022). Query Expansion Based on User Requirements Clustering for Finding Feature Location. In Proceeding - 6th International Conference on Information Technology, Information Systems and Electrical Engineering: Applying Data Sciences and Artificial Intelligence Technologies for Environmental Sustainability, ICITISEE 2022 (pp. 149-153). (Proceeding - 6th International Conference on Information Technology, Information Systems and Electrical Engineering: Applying Data Sciences and Artificial Intelligence Technologies for Environmental Sustainability, ICITISEE 2022). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICITISEE57756.2022.10057893

Arwan, Achmad ; Rochimah, Siti ; Fatichah, Chastine. / Query Expansion Based on User Requirements Clustering for Finding Feature Location. Proceeding - 6th International Conference on Information Technology, Information Systems and Electrical Engineering: Applying Data Sciences and Artificial Intelligence Technologies for Environmental Sustainability, ICITISEE 2022. Institute of Electrical and Electronics Engineers Inc., 2022. pp. 149-153 (Proceeding - 6th International Conference on Information Technology, Information Systems and Electrical Engineering: Applying Data Sciences and Artificial Intelligence Technologies for Environmental Sustainability, ICITISEE 2022).

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title = "Query Expansion Based on User Requirements Clustering for Finding Feature Location",

abstract = "Feature Location is an approach of how to determine the code area based on high level software artifacts. Use Case Scenarios (UCS) are requirements documents in software artifacts that contain many words. A sentence in a UCS is sometimes described by a sentence in other UCS, so capture the relationship among UCS may be advantageous in finding feature locations. The research contribution is how to find feature locations better by making an expansion to query based on UCS clustering. The method was clustering the UCS using k-medoids clustering and index the source code using latent dirichlet allocation. The results was 56.8\% for the best recall rate.",

keywords = "Clustering, Feature location, Latent Dirichlet Allocation, Use Case Scenario, research",

author = "Achmad Arwan and Siti Rochimah and Chastine Fatichah",

note = "Publisher Copyright: {\textcopyright} 2022 IEEE.; 6th International Conference on Information Technology, Information Systems and Electrical Engineering, ICITISEE 2022 ; Conference date: 13-12-2022 Through 14-12-2022",

year = "2022",

doi = "10.1109/ICITISEE57756.2022.10057893",

language = "English",

series = "Proceeding - 6th International Conference on Information Technology, Information Systems and Electrical Engineering: Applying Data Sciences and Artificial Intelligence Technologies for Environmental Sustainability, ICITISEE 2022",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

pages = "149--153",

booktitle = "Proceeding - 6th International Conference on Information Technology, Information Systems and Electrical Engineering",

address = "United States",

}

Arwan, A, Rochimah, S & Fatichah, C 2022, Query Expansion Based on User Requirements Clustering for Finding Feature Location. in Proceeding - 6th International Conference on Information Technology, Information Systems and Electrical Engineering: Applying Data Sciences and Artificial Intelligence Technologies for Environmental Sustainability, ICITISEE 2022. Proceeding - 6th International Conference on Information Technology, Information Systems and Electrical Engineering: Applying Data Sciences and Artificial Intelligence Technologies for Environmental Sustainability, ICITISEE 2022, Institute of Electrical and Electronics Engineers Inc., pp. 149-153, 6th International Conference on Information Technology, Information Systems and Electrical Engineering, ICITISEE 2022, Virtual, Online, Indonesia, 13/12/22. https://doi.org/10.1109/ICITISEE57756.2022.10057893

Query Expansion Based on User Requirements Clustering for Finding Feature Location. / Arwan, Achmad; Rochimah, Siti ; Fatichah, Chastine.
Proceeding - 6th International Conference on Information Technology, Information Systems and Electrical Engineering: Applying Data Sciences and Artificial Intelligence Technologies for Environmental Sustainability, ICITISEE 2022. Institute of Electrical and Electronics Engineers Inc., 2022. p. 149-153 (Proceeding - 6th International Conference on Information Technology, Information Systems and Electrical Engineering: Applying Data Sciences and Artificial Intelligence Technologies for Environmental Sustainability, ICITISEE 2022).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Query Expansion Based on User Requirements Clustering for Finding Feature Location

AU - Arwan, Achmad

AU - Rochimah, Siti

AU - Fatichah, Chastine

PY - 2022

Y1 - 2022

N2 - Feature Location is an approach of how to determine the code area based on high level software artifacts. Use Case Scenarios (UCS) are requirements documents in software artifacts that contain many words. A sentence in a UCS is sometimes described by a sentence in other UCS, so capture the relationship among UCS may be advantageous in finding feature locations. The research contribution is how to find feature locations better by making an expansion to query based on UCS clustering. The method was clustering the UCS using k-medoids clustering and index the source code using latent dirichlet allocation. The results was 56.8% for the best recall rate.

AB - Feature Location is an approach of how to determine the code area based on high level software artifacts. Use Case Scenarios (UCS) are requirements documents in software artifacts that contain many words. A sentence in a UCS is sometimes described by a sentence in other UCS, so capture the relationship among UCS may be advantageous in finding feature locations. The research contribution is how to find feature locations better by making an expansion to query based on UCS clustering. The method was clustering the UCS using k-medoids clustering and index the source code using latent dirichlet allocation. The results was 56.8% for the best recall rate.

KW - Clustering

KW - Feature location

KW - Latent Dirichlet Allocation

KW - Use Case Scenario

KW - research

UR - https://www.scopus.com/pages/publications/85150423132

U2 - 10.1109/ICITISEE57756.2022.10057893

DO - 10.1109/ICITISEE57756.2022.10057893

M3 - Conference contribution

AN - SCOPUS:85150423132

T3 - Proceeding - 6th International Conference on Information Technology, Information Systems and Electrical Engineering: Applying Data Sciences and Artificial Intelligence Technologies for Environmental Sustainability, ICITISEE 2022

SP - 149

EP - 153

BT - Proceeding - 6th International Conference on Information Technology, Information Systems and Electrical Engineering

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 6th International Conference on Information Technology, Information Systems and Electrical Engineering, ICITISEE 2022

Y2 - 13 December 2022 through 14 December 2022

ER -

Arwan A, Rochimah S , Fatichah C. Query Expansion Based on User Requirements Clustering for Finding Feature Location. In Proceeding - 6th International Conference on Information Technology, Information Systems and Electrical Engineering: Applying Data Sciences and Artificial Intelligence Technologies for Environmental Sustainability, ICITISEE 2022. Institute of Electrical and Electronics Engineers Inc. 2022. p. 149-153. (Proceeding - 6th International Conference on Information Technology, Information Systems and Electrical Engineering: Applying Data Sciences and Artificial Intelligence Technologies for Environmental Sustainability, ICITISEE 2022). doi: 10.1109/ICITISEE57756.2022.10057893

Query Expansion Based on User Requirements Clustering for Finding Feature Location

Abstract

Publication series

Conference

UN SDGs

Keywords

Access to Document

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