A flow-based programming framework for mobile App development

Zaman, Jesse; Hoste, Lode; Meuter, Wolfgang De

doi:10.1145/2824823.2824825

Cited by 4 publications

(1 citation statement)

References 9 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…FBP has a reputation as a paradigm that optimizes speed, bandwidth and processing power in multi-tasking, parallel processing applications. For example Szydlo [53]. Recent years saw birth of several general-purpose projects built on flow-based programming principles, such as NoFlo [2] and Node-RED 2 .…”

Section: Flow-based Programmingmentioning

confidence: 99%

An Empirical Evaluation of Flow Based Programming in the Machine Learning Deployment Context

Paleyes¹,

Cabrera²,

Lawrence³

2022

Preprint

View full text Add to dashboard Cite

As use of data driven technologies spreads, software engineers are more often faced with the task of solving a business problem using data-driven methods such as machine learning (ML) algorithms. Deployment of ML within large software systems brings new challenges that are not addressed by standard engineering practices and as a result businesses observe high rate of ML deployment project failures. Data Oriented Architecture (DOA) is an emerging approach that can support data scientists and software developers when addressing such challenges. However, there is a lack of clarity about how DOA systems should be implemented in practice. This paper proposes to consider Flow-Based Programming (FBP) as a paradigm for creating DOA applications. We empirically evaluate FBP in the context of ML deployment on four applications that represent typical data science projects. We use Service Oriented Architecture (SOA) as a baseline for comparison. Evaluation is done with respect to different application domains, ML deployment stages, and code quality metrics. Results reveal that FBP is a suitable paradigm for data collection and data science tasks, and is able to simplify data collection and discovery when compared with SOA. We discuss the advantages of FBP as well as the gaps that need to be addressed to increase FBP adoption as a standard design paradigm for DOA. CCS CONCEPTS• Software and its engineering → Software design tradeoffs; • Computing methodologies → Machine learning.

show abstract

Section: Flow-based Programmingmentioning

confidence: 99%