Mining software architecture knowledge: Classifying stack overflow posts using machine learning-Reference-Cited by-同舟云学术

Mining software architecture knowledge: Classifying stack overflow posts using machine learning

Published:2021-03-31 Issue:16 Volume:33 Page:
ISSN:1532-0626
Container-title:Concurrency and Computation: Practice and Experience
language:en
Short-container-title:Concurrency Computat Pract Exper

Author:

Ali Mubashir¹,Mushtaq Husnain²,Rasheed Muhammad B³⁴^ORCID,Baqir Anees⁵,Alquthami Thamer⁶

Affiliation:

1. DIGIP University of Bergamo Bergamo Italy

2. Department of Computer Science The University of Lahore Gujrat Pakistan

3. Department of Computer Engineering The University of Alcala Madrid Spain

4. Department of Electronics and Electrical Systems The University of Lahore Lahore Pakistan

5. Department of Environmental Sciences, Informatics and Statistics Ca' Foscari University of Venice Venice Italy

6. Department of Electrical Engineering and Computer Engineering King Abdulaziz University Jeddah Saudi Arabia

Publisher

Wiley

Subject

Computational Theory and Mathematics,Computer Networks and Communications,Computer Science Applications,Theoretical Computer Science,Software

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/cpe.6277

Reference38 articles.

1. JansenA BoschJ. Software architecture as a set of architectural design decisions. Paper presented at: Proceedings of the 5th Working IEEE/IFIP Conference on Software Architecture (WICSA'05) 2005 November 6 Pittsburgh PA: IEEE;2005:109‐120.https://doi.org/10.1109/WICSA.2005.61.

2. Al‐NaeemT GortonI BabarMA RabhiF BenatallahB. A quality‐driven systematic approach for architecting distributed software applications. Paper presented at: Proceedings of the 27th International Conference on Software Engineering 2005 May 15 ACM New York NY;2005:244‐253.

3. Architectural knowledge and rationale

4. A general model of software architecture design derived from five industrial approaches

5. Past and future of software architectural decisions – A systematic mapping study

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