Reusability in artificial neural networks: An empirical study

Javad Ghofrani; Ehsan Kozegar; Arezoo Bozorgmehr; Mohammad Divband Soorati

doi:10.1145/3307630.3342419

Reusability in artificial neural networks: An empirical study

Javad Ghofrani, Ehsan Kozegar, Arezoo Bozorgmehr, Mohammad Divband Soorati

Institute of Computer Engineering

Abstract

Machine learning, especially deep learning has aroused interests of researchers and practitioners for the last few years in development of intelligent systems such as speech, natural language, and image processing. Software solutions based on machine learning techniques attract more attention as alternatives to conventional software systems. In this paper, we investigate how reusability techniques are applied in implementation of artificial neural networks (ANNs). We conducted an empirical study with an online survey among experts with experience in developing solutions with ANNs. We analyze the feedback ofmore than 100 experts to our survey. The results show existing challenges and some of the applied solutions in an intersection between reusability and ANNs.

Original language	English
Title of host publication	SPLC '19: Proceedings of the 23rd International Systems and Software Product Line Conference
Editors	Carlos Cetina, Oscar Díaz, Laurence Duchien, Marianne Huchard, Rick Rabiser, Camille Salinesi, Christoph Seidl, Xhevahire Tërnava, Leopoldo Teixeira, Thomas Thüm, Tewfik Ziadi
Number of pages	8
Volume	B
Publisher	ACM
Publication date	09.09.2019
Pages	122–129
ISBN (Print)	978-1-4503-6668-7
DOIs	https://doi.org/10.1145/3307630.3342419
Publication status	Published - 09.09.2019
Event	23rd International Systems and Software Product Line Conference - Paris, France Duration: 09.09.2019 → 13.09.2019 Conference number: 154713

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Ghofrani, J., Kozegar, E., Bozorgmehr, A., & Soorati, M. D. (2019). Reusability in artificial neural networks: An empirical study. In C. Cetina, O. Díaz, L. Duchien, M. Huchard, R. Rabiser, C. Salinesi, C. Seidl, X. Tërnava, L. Teixeira, T. Thüm, & T. Ziadi (Eds.), SPLC '19: Proceedings of the 23rd International Systems and Software Product Line Conference (Vol. B, pp. 122–129). (ACM International Conference Proceeding Series; Vol. B). ACM. https://doi.org/10.1145/3307630.3342419

Ghofrani, Javad ; Kozegar, Ehsan ; Bozorgmehr, Arezoo et al. / Reusability in artificial neural networks: An empirical study. SPLC '19: Proceedings of the 23rd International Systems and Software Product Line Conference. editor / Carlos Cetina ; Oscar Díaz ; Laurence Duchien ; Marianne Huchard ; Rick Rabiser ; Camille Salinesi ; Christoph Seidl ; Xhevahire Tërnava ; Leopoldo Teixeira ; Thomas Thüm ; Tewfik Ziadi. Vol. B ACM, 2019. pp. 122–129 (ACM International Conference Proceeding Series).

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title = "Reusability in artificial neural networks: An empirical study",

abstract = "Machine learning, especially deep learning has aroused interests of researchers and practitioners for the last few years in development of intelligent systems such as speech, natural language, and image processing. Software solutions based on machine learning techniques attract more attention as alternatives to conventional software systems. In this paper, we investigate how reusability techniques are applied in implementation of artificial neural networks (ANNs). We conducted an empirical study with an online survey among experts with experience in developing solutions with ANNs. We analyze the feedback ofmore than 100 experts to our survey. The results show existing challenges and some of the applied solutions in an intersection between reusability and ANNs.",

author = "Javad Ghofrani and Ehsan Kozegar and Arezoo Bozorgmehr and Soorati, {Mohammad Divband}",

note = "Publisher Copyright: {\textcopyright} 2019 Copyright held by the owner/author(s). Copyright: Copyright 2019 Elsevier B.V., All rights reserved.; 23rd International Systems and Software Product Line Conference , SPLC 2019 ; Conference date: 09-09-2019 Through 13-09-2019",

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Ghofrani, J, Kozegar, E, Bozorgmehr, A & Soorati, MD 2019, Reusability in artificial neural networks: An empirical study. in C Cetina, O Díaz, L Duchien, M Huchard, R Rabiser, C Salinesi, C Seidl, X Tërnava, L Teixeira, T Thüm & T Ziadi (eds), SPLC '19: Proceedings of the 23rd International Systems and Software Product Line Conference. vol. B, ACM International Conference Proceeding Series, vol. B, ACM, pp. 122–129, 23rd International Systems and Software Product Line Conference , Paris, France, 09.09.19. https://doi.org/10.1145/3307630.3342419

Reusability in artificial neural networks: An empirical study. / Ghofrani, Javad; Kozegar, Ehsan; Bozorgmehr, Arezoo et al.
SPLC '19: Proceedings of the 23rd International Systems and Software Product Line Conference. ed. / Carlos Cetina; Oscar Díaz; Laurence Duchien; Marianne Huchard; Rick Rabiser; Camille Salinesi; Christoph Seidl; Xhevahire Tërnava; Leopoldo Teixeira; Thomas Thüm; Tewfik Ziadi. Vol. B ACM, 2019. p. 122–129 (ACM International Conference Proceeding Series; Vol. B).

Research output: Chapters in Books/Reports/Conference Proceedings › Conference contribution › peer-review

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T1 - Reusability in artificial neural networks: An empirical study

AU - Ghofrani, Javad

AU - Kozegar, Ehsan

AU - Bozorgmehr, Arezoo

AU - Soorati, Mohammad Divband

N1 - Conference code: 154713

PY - 2019/9/9

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N2 - Machine learning, especially deep learning has aroused interests of researchers and practitioners for the last few years in development of intelligent systems such as speech, natural language, and image processing. Software solutions based on machine learning techniques attract more attention as alternatives to conventional software systems. In this paper, we investigate how reusability techniques are applied in implementation of artificial neural networks (ANNs). We conducted an empirical study with an online survey among experts with experience in developing solutions with ANNs. We analyze the feedback ofmore than 100 experts to our survey. The results show existing challenges and some of the applied solutions in an intersection between reusability and ANNs.

AB - Machine learning, especially deep learning has aroused interests of researchers and practitioners for the last few years in development of intelligent systems such as speech, natural language, and image processing. Software solutions based on machine learning techniques attract more attention as alternatives to conventional software systems. In this paper, we investigate how reusability techniques are applied in implementation of artificial neural networks (ANNs). We conducted an empirical study with an online survey among experts with experience in developing solutions with ANNs. We analyze the feedback ofmore than 100 experts to our survey. The results show existing challenges and some of the applied solutions in an intersection between reusability and ANNs.

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VL - B

T3 - ACM International Conference Proceeding Series

SP - 122

EP - 129

BT - SPLC '19: Proceedings of the 23rd International Systems and Software Product Line Conference

A2 - Cetina, Carlos

A2 - Díaz, Oscar

A2 - Duchien, Laurence

A2 - Huchard, Marianne

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A2 - Salinesi, Camille

A2 - Seidl, Christoph

A2 - Tërnava, Xhevahire

A2 - Teixeira, Leopoldo

A2 - Thüm, Thomas

A2 - Ziadi, Tewfik

PB - ACM

T2 - 23rd International Systems and Software Product Line Conference

Y2 - 9 September 2019 through 13 September 2019

ER -

Ghofrani J, Kozegar E, Bozorgmehr A, Soorati MD. Reusability in artificial neural networks: An empirical study. In Cetina C, Díaz O, Duchien L, Huchard M, Rabiser R, Salinesi C, Seidl C, Tërnava X, Teixeira L, Thüm T, Ziadi T, editors, SPLC '19: Proceedings of the 23rd International Systems and Software Product Line Conference. Vol. B. ACM. 2019. p. 122–129. (ACM International Conference Proceeding Series). doi: 10.1145/3307630.3342419

Reusability in artificial neural networks: An empirical study

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