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Multicriteria decision making taxonomy of code recommendation system challenges : a fuzzy‑AHP analysis |
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| Author: | Akbar, Muhammad Azeem1; Khan, Arif Ali2,3; Huang, Zhiqiu4 |
| Organizations: |
1Software Engineering Department, Lappeenranta-Lahti University of Technology, 53851 Lappeenranta, Finland 2Faculty of Information Technology, University of Jyvaskyla, Jyvaskyla, Finland 3M3S Empirical Software Engineering Research Unit, University of Oulu, 90014, Oulu, Finland
4College of Computer Science and Technology, Nanjing University of Aeronautics and Astronautics, Nanjing 211100, China
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| Format: | article |
| Version: | published version |
| Access: | open |
| Online Access: | PDF Full Text (PDF, 2.1 MB) |
| Persistent link: | http://urn.fi/urn:nbn:fi-fe20230925137152 |
| Language: | English |
| Published: |
Springer Nature,
2023
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| Publish Date: | 2023-09-25 |
| Description: |
AbstractThe recommendation systems plays an important role in today’s life as it assist in reliable selection of common utilities. The code recommendation system is being used by the code databases (GitHub, source frog etc.) aiming to recommend the more appropriate code to the users. There are several factors that could negatively impact the performance of code recommendation systems (CRS). This study aims to empirically explore the challenges that could have critical impact on the performance of the CRS. Using systematic literature review and questionnaire survey approaches, 19 challenges were identified. Secondly, the investigated challenges were further prioritized using fuzzy-AHP analysis. The identification of challenges, their categorization and the fuzzy-AHP analysis provides the prioritization-based taxonomy of explored challenges. The study findings will assist the real-world industry experts and to academic researchers to improve and develop the new techniques for the improvement of CRS. see all
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| Series: |
Information technology & management |
| ISSN: | 1385-951X |
| ISSN-E: | 1573-7667 |
| ISSN-L: | 1385-951X |
| Volume: | 24 |
| Issue: | 2 |
| Pages: | 115 - 131 |
| DOI: | 10.1007/s10799-021-00355-3 |
| OADOI: | https://oadoi.org/10.1007/s10799-021-00355-3 |
| Type of Publication: |
A1 Journal article – refereed |
| Field of Science: |
213 Electronic, automation and communications engineering, electronics |
| Subjects: | |
| Funding: |
Open Access funding provided by University of Oulu including Oulu University Hospital. |
| Copyright information: |
© The Author(s) 2022. This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. |
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https://creativecommons.org/licenses/by/4.0/ |