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Software Engineering Challenges of Deep Learning

Software Engineering Challenges of Deep Learning

29 October 2018
Anders Arpteg
B. Brinne
L. Crnkovic-Friis
J. Bosch
ArXivPDFHTML

Papers citing "Software Engineering Challenges of Deep Learning"

19 / 19 papers shown
Title
Prompts Are Programs Too! Understanding How Developers Build Software Containing Prompts
Prompts Are Programs Too! Understanding How Developers Build Software Containing Prompts
Jenny T Liang
Melissa Lin
Nikitha Rao
Brad A. Myers
83
6
0
19 Sep 2024
A Large-Scale Study of Model Integration in ML-Enabled Software Systems
A Large-Scale Study of Model Integration in ML-Enabled Software Systems
Yorick Sens
Henriette Knopp
Sven Peldszus
Thorsten Berger
AIFin
31
2
0
12 Aug 2024
Naming the Pain in Machine Learning-Enabled Systems Engineering
Naming the Pain in Machine Learning-Enabled Systems Engineering
Marcos Kalinowski
Daniel Méndez
G. Giray
Antonio Pedro Santos Alves
Kelly Azevedo
...
Stefan Biffl
Jürgen Musil
Michael Felderer
N. Lavesson
T. Gorschek
31
5
0
20 May 2024
Beyond Accuracy: An Empirical Study on Unit Testing in Open-source Deep
  Learning Projects
Beyond Accuracy: An Empirical Study on Unit Testing in Open-source Deep Learning Projects
Han Wang
Sijia Yu
Chunyang Chen
Burak Turhan
Xiaodong Zhu
ELM
MLAU
25
2
0
26 Feb 2024
Deep learning for table detection and structure recognition: A survey
Deep learning for table detection and structure recognition: A survey
M. Kasem
Abdelrahman Abdallah
Alexander Berendeyev
Ebrahem Elkady
Mahmoud Abdalla
Mohamed Mahmoud
Mohamed Hamada
D. Nurseitov
I. Taj-Eddin
LMTD
35
25
0
15 Nov 2022
Management of Machine Learning Lifecycle Artifacts: A Survey
Management of Machine Learning Lifecycle Artifacts: A Survey
Marius Schlegel
K. Sattler
25
35
0
21 Oct 2022
Distributed Ensembles of Reinforcement Learning Agents for Electricity
  Control
Distributed Ensembles of Reinforcement Learning Agents for Electricity Control
Pierrick Pochelu
S. Petiton
B. Conche
AI4CE
31
2
0
30 Aug 2022
Towards Perspective-Based Specification of Machine Learning-Enabled
  Systems
Towards Perspective-Based Specification of Machine Learning-Enabled Systems
Hugo Villamizar
Marcos Kalinowski
Hélio Lopes
10
6
0
20 Jun 2022
Towards a Change Taxonomy for Machine Learning Systems
Towards a Change Taxonomy for Machine Learning Systems
Aaditya Bhatia
Ellis E. Eghan
Manel Grichi
William G. Cavanagh
Zhen Ming
Z. Jiang
Bram Adams
31
8
0
21 Mar 2022
Challenges in Migrating Imperative Deep Learning Programs to Graph
  Execution: An Empirical Study
Challenges in Migrating Imperative Deep Learning Programs to Graph Execution: An Empirical Study
Tatiana Castro Vélez
Raffi Khatchadourian
M. Bagherzadeh
A. Raja
21
9
0
24 Jan 2022
Collaboration Challenges in Building ML-Enabled Systems: Communication,
  Documentation, Engineering, and Process
Collaboration Challenges in Building ML-Enabled Systems: Communication, Documentation, Engineering, and Process
Nadia Nahar
Shurui Zhou
Grace A. Lewis
Christian Kastner
VLM
45
126
0
19 Oct 2021
Quality Assurance Challenges for Machine Learning Software Applications
  During Software Development Life Cycle Phases
Quality Assurance Challenges for Machine Learning Software Applications During Software Development Life Cycle Phases
Md. Abdullah Al Alamin
Gias Uddin
37
11
0
03 May 2021
Integration of Convolutional Neural Networks in Mobile Applications
Integration of Convolutional Neural Networks in Mobile Applications
Roger Creus Castanyer
Silverio Martínez-Fernández
Xavier Franch
29
12
0
11 Mar 2021
How AI Developers Overcome Communication Challenges in a
  Multidisciplinary Team: A Case Study
How AI Developers Overcome Communication Challenges in a Multidisciplinary Team: A Case Study
David Piorkowski
Soya Park
A. Wang
Dakuo Wang
Michael J. Muller
Felix Portnoy
38
131
0
13 Jan 2021
A Software Engineering Perspective on Engineering Machine Learning
  Systems: State of the Art and Challenges
A Software Engineering Perspective on Engineering Machine Learning Systems: State of the Art and Challenges
G. Giray
33
120
0
14 Dec 2020
Software engineering for artificial intelligence and machine learning
  software: A systematic literature review
Software engineering for artificial intelligence and machine learning software: A systematic literature review
E. Nascimento
Anh Nguyen-Duc
Ingrid Sundbø
T. Conte
18
40
0
07 Nov 2020
Engineering AI Systems: A Research Agenda
Engineering AI Systems: A Research Agenda
J. Bosch
I. Crnkovic
Helena Holmström Olsson
AI4TS
28
100
0
16 Jan 2020
Taxonomy of Real Faults in Deep Learning Systems
Taxonomy of Real Faults in Deep Learning Systems
Nargiz Humbatova
Gunel Jahangirova
Gabriele Bavota
Vincenzo Riccio
Andrea Stocco
Paolo Tonella
12
263
0
24 Oct 2019
Losing Confidence in Quality: Unspoken Evolution of Computer Vision
  Services
Losing Confidence in Quality: Unspoken Evolution of Computer Vision Services
Alex Cummaudo
Rajesh Vasa
J. Grundy
Mohamed Abdelrazek
A. Cain
26
19
0
18 Jun 2019
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