Smart contract development: Challenges and opportunities

W Zou, D Lo, PS Kochhar, XBD Le, X **a… - IEEE transactions on …, 2019‏ - ieeexplore.ieee.org
Smart contract, a term which was originally coined to refer to the automation of legal
contracts in general, has recently seen much interest due to the advent of blockchain …

Data scientists in software teams: State of the art and challenges

M Kim, T Zimmermann, R DeLine… - IEEE Transactions on …, 2017‏ - ieeexplore.ieee.org
The demand for analyzing large scale telemetry, machine, and quality data is rapidly
increasing in software industry. Data scientists are becoming popular within software teams …

Software engineering for machine learning: A case study

S Amershi, A Begel, C Bird, R DeLine… - 2019 IEEE/ACM 41st …, 2019‏ - ieeexplore.ieee.org
Recent advances in machine learning have stimulated widespread interest within the
Information Technology sector on integrating AI capabilities into software and services. This …

[HTML][HTML] Employability skills: Profiling data scientists in the digital labour market

F Smaldone, A Ippolito, J Lagger, M Pellicano - European Management …, 2022‏ - Elsevier
In the current scenario, data scientists are expected to make sense of vast stores of big data,
which are becoming increasingly complex and heterogeneous in nature. In the context of …

How do data science workers collaborate? roles, workflows, and tools

AX Zhang, M Muller, D Wang - Proceedings of the ACM on Human …, 2020‏ - dl.acm.org
Today, the prominence of data science within organizations has given rise to teams of data
science workers collaborating on extracting insights from data, as opposed to individual data …

How data science workers work with data: Discovery, capture, curation, design, creation

M Muller, I Lange, D Wang, D Piorkowski… - Proceedings of the …, 2019‏ - dl.acm.org
With the rise of big data, there has been an increasing need for practitioners in this space
and an increasing opportunity for researchers to understand their workflows and design new …

Impact of generative artificial intelligence models on the performance of citizen data scientists in retail firms

RA Abumalloh, M Nilashi, KB Ooi, GWH Tan… - Computers in …, 2024‏ - Elsevier
Abstract Generative Artificial Intelligence (AI) models serve as powerful tools for
organizations aiming to integrate advanced data analysis and automation into their …

How does machine learning change software development practices?

Z Wan, X **a, D Lo, GC Murphy - IEEE Transactions on …, 2019‏ - ieeexplore.ieee.org
Adding an ability for a system to learn inherently adds uncertainty into the system. Given the
rising popularity of incorporating machine learning into systems, we wondered how the …

How ai developers overcome communication challenges in a multidisciplinary team: A case study

D Piorkowski, S Park, AY Wang, D Wang… - Proceedings of the …, 2021‏ - dl.acm.org
The development of AI applications is a multidisciplinary effort, involving multiple roles
collaborating with the AI developers, an umbrella term we use to include data scientists and …

MODE: automated neural network model debugging via state differential analysis and input selection

S Ma, Y Liu, WC Lee, X Zhang, A Grama - … of the 2018 26th ACM Joint …, 2018‏ - dl.acm.org
Artificial intelligence models are becoming an integral part of modern computing systems.
Just like software inevitably has bugs, models have bugs too, leading to poor classification …