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A Software Engineering Perspective on Engineering Machine Learning
  Systems: State of the Art and Challenges
v1v2v3 (latest)

A Software Engineering Perspective on Engineering Machine Learning Systems: State of the Art and Challenges

Journal of Systems and Software (JSS), 2020
14 December 2020
G. Giray
ArXiv (abs)PDFHTML

Papers citing "A Software Engineering Perspective on Engineering Machine Learning Systems: State of the Art and Challenges"

30 / 30 papers shown
Enhancing software product lines with machine learning components
Enhancing software product lines with machine learning components
Luz-Viviana Cobaleda
Julián Carvajal
Paola Vallejo
Andrés López
Raúl Mazo
VLM
249
1
0
31 Oct 2025
Towards Requirements Engineering for RAG Systems
Towards Requirements Engineering for RAG Systems
Tor Sporsem
Rasmus Ulfsnes
224
1
0
12 May 2025
Explainable Artificial Intelligence Techniques for Software Development Lifecycle: A Phase-specific Survey
Explainable Artificial Intelligence Techniques for Software Development Lifecycle: A Phase-specific SurveyAnnual International Computer Software and Applications Conference (COMPSAC), 2025
Lakshit Arora
Sanjay Surendranath Girija
Shashank Kapoor
Aman Raj
Dipen Pradhan
Ankit Shetgaonkar
308
7
0
11 May 2025
Scalability and Maintainability Challenges and Solutions in Machine Learning: Systematic Literature Review
Scalability and Maintainability Challenges and Solutions in Machine Learning: Systematic Literature Review
Karthik Shivashankar
Ghadi S. Al Hajj
Antonio Martini
428
3
0
15 Apr 2025
How Do Model Export Formats Impact the Development of ML-Enabled Systems? A Case Study on Model Integration
How Do Model Export Formats Impact the Development of ML-Enabled Systems? A Case Study on Model Integration
Shreyas Kumar Parida
I. Gerostathopoulos
Justus Bogner
322
0
0
01 Feb 2025
LoCoML: A Framework for Real-World ML Inference Pipelines
LoCoML: A Framework for Real-World ML Inference Pipelines
Kritin Maddireddy
Santhosh Kotekal Methukula
Chandrasekar Sridhar
Karthik Vaidhyanathan
165
2
0
24 Jan 2025
Large Language Models for Constructing and Optimizing Machine Learning
  Workflows: A Survey
Large Language Models for Constructing and Optimizing Machine Learning Workflows: A Survey
Yang Gu
Hengyu You
Jian Cao
Muran Yu
Haoran Fan
Shiyou Qian
LM&MAAI4CE
475
17
0
11 Nov 2024
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
326
34
0
19 Sep 2024
How to Measure Human-AI Prediction Accuracy in Explainable AI Systems
How to Measure Human-AI Prediction Accuracy in Explainable AI Systems
Sujay Koujalgi
Andrew Anderson
Iyadunni Adenuga
Shikha Soneji
Rupika Dikkala
...
Leo Soccio
Sourav Panda
Rupak Kumar Das
Margaret Burnett
Jonathan Dodge
233
3
0
23 Aug 2024
On Security Weaknesses and Vulnerabilities in Deep Learning Systems
On Security Weaknesses and Vulnerabilities in Deep Learning Systems
Zhongzheng Lai
Huaming Chen
Ruoxi Sun
Yu Zhang
Minhui Xue
Dong Yuan
AAML
248
4
0
12 Jun 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
257
11
0
20 May 2024
A Framework to Model ML Engineering Processes
A Framework to Model ML Engineering Processes
Sergio Morales
Robert Clarisó
Jordi Cabot
181
6
0
29 Apr 2024
An Optimized Framework for Processing Large-scale Polysomnographic Data
  Incorporating Expert Human Oversight
An Optimized Framework for Processing Large-scale Polysomnographic Data Incorporating Expert Human Oversight
Benedikt Holm
Gabriel Jouan
Emil Hardarson
Sigríður Sigurðardóttir
Kenan Hoelke
Conor Murphy
E. S. Arnardóttir
María Óskarsdóttir
A. Islind
234
0
0
02 Apr 2024
Profile of Vulnerability Remediations in Dependencies Using Graph
  Analysis
Profile of Vulnerability Remediations in Dependencies Using Graph Analysis
Fernando Vera
Palina Pauliuchenka
Ethan Oh
Bai Chien Kao
Louis DiValentin
David A. Bader
182
1
0
08 Mar 2024
An Empirical Study of Challenges in Machine Learning Asset Management
An Empirical Study of Challenges in Machine Learning Asset Management
Zhimin Zhao
Yihao Chen
A. A. Bangash
Bram Adams
Ahmed E. Hassan
394
15
0
25 Feb 2024
Good Tools are Half the Work: Tool Usage in Deep Learning Projects
Good Tools are Half the Work: Tool Usage in Deep Learning Projects
Evangelia Panourgia
Theodoros Plessas
Ilias Balampanis
D. Spinellis
251
0
0
29 Oct 2023
Telecom AI Native Systems in the Age of Generative AI -- An Engineering
  Perspective
Telecom AI Native Systems in the Age of Generative AI -- An Engineering Perspective
Ricardo Britto
Timothy Murphy
Massimo Iovene
Leif Jonsson
Melike Erol-Kantarci
Benedek Kovács
127
9
0
18 Oct 2023
Test & Evaluation Best Practices for Machine Learning-Enabled Systems
Test & Evaluation Best Practices for Machine Learning-Enabled Systems
Jaganmohan Chandrasekaran
Tyler Cody
Nicola McCarthy
Erin Lanus
Laura J. Freeman
245
10
0
10 Oct 2023
A Meta-Summary of Challenges in Building Products with ML Components --
  Collecting Experiences from 4758+ Practitioners
A Meta-Summary of Challenges in Building Products with ML Components -- Collecting Experiences from 4758+ Practitioners
Nadia Nahar
Haoran Zhang
Grace A. Lewis
Shurui Zhou
Jane Hsieh
368
62
0
31 Mar 2023
The Effect of Structural Equation Modeling on Chatbot Usage: An
  Investigation of Dialogflow
The Effect of Structural Equation Modeling on Chatbot Usage: An Investigation of DialogflowIJAIT (International Journal of Applied Information Technology) (IJAIT), 2023
Vinh Phu Nguyen
C. T. H. Nguyen
157
9
0
07 Feb 2023
Leveraging Artificial Intelligence on Binary Code Comprehension
Leveraging Artificial Intelligence on Binary Code ComprehensionInternational Conference on Automated Software Engineering (ASE), 2022
Yifan Zhang
220
4
0
11 Oct 2022
Capturing Dependencies within Machine Learning via a Formal Process
  Model
Capturing Dependencies within Machine Learning via a Formal Process ModelLeveraging Applications of Formal Methods (ISoLA), 2022
Fabian Ritz
Thomy Phan
Andreas Sedlmeier
Philipp Altmann
J. Wieghardt
Reiner N. Schmid
Horst Sauer
Cornel Klein
Claudia Linnhoff-Popien
Thomas Gabor
VLM
209
11
0
10 Aug 2022
Differential testing for machine learning: an analysis for
  classification algorithms beyond deep learning
Differential testing for machine learning: an analysis for classification algorithms beyond deep learningEmpirical Software Engineering (EMSE), 2022
Steffen Herbold
Steffen Tunkel
242
6
0
25 Jul 2022
Modeling Quality and Machine Learning Pipelines through Extended Feature
  Models
Modeling Quality and Machine Learning Pipelines through Extended Feature Models
Giordano dÁloisio
A. Marco
Giovanni Stilo
223
7
0
15 Jul 2022
Software Engineering Approaches for TinyML based IoT Embedded Vision: A
  Systematic Literature Review
Software Engineering Approaches for TinyML based IoT Embedded Vision: A Systematic Literature ReviewInternational Workshop on Software Engineering Research & Practices for the Internet of Things (ERPIT), 2022
Shashank Bangalore Lakshman
Nasir U. Eisty
169
14
0
19 Apr 2022
Security for Machine Learning-based Software Systems: a survey of
  threats, practices and challenges
Security for Machine Learning-based Software Systems: a survey of threats, practices and challengesACM Computing Surveys (ACM CSUR), 2022
Huaming Chen
Muhammad Ali Babar
AAML
348
41
0
12 Jan 2022
Agility in Software 2.0 -- Notebook Interfaces and MLOps with Buttresses
  and Rebars
Agility in Software 2.0 -- Notebook Interfaces and MLOps with Buttresses and RebarsInternational Conference on Lean and Agile Software Development (ICLASD), 2021
Markus Borg
133
13
0
28 Nov 2021
A Survey on Machine Learning Techniques for Source Code Analysis
A Survey on Machine Learning Techniques for Source Code Analysis
Tushar Sharma
M. Kechagia
Stefanos Georgiou
Rohit Tiwari
Indira Vats
Hadi Moazen
Federica Sarro
282
80
0
18 Oct 2021
Software Engineering for AI-Based Systems: A Survey
Software Engineering for AI-Based Systems: A SurveyACM Transactions on Software Engineering and Methodology (TOSEM), 2021
Luís Cruz
Justus Bogner
Xavier Franch
Marc Oriol
Julien Siebert
Adam Trendowicz
Anna Maria Vollmer
Stefan Wagner
321
295
0
05 May 2021
Software Engineering Practices for Machine Learning
Software Engineering Practices for Machine Learning
P. Kriens
Tim Verbelen
VLM
130
4
0
25 Jun 2019
1
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