Analysis of Software Engineering Practices in General Software and Machine Learning Startups

Bishal Lakha, Kalyan Bhetwal, Nasir U. Eisty

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Context: On top of the inherent challenges startup software companies face applying proper software engineering practices, the non-deterministic nature of machine learning techniques makes it even more difficult for machine learning (ML) startups. Objective: Therefore, the objective of our study is to understand the whole picture of software engineering practices followed by ML startups and identify additional needs. Method: To achieve our goal, we conducted a systematic literature review study on 37 papers published in the last 21 years. We selected papers on both general software startups and ML startups. We collected data to understand software engineering (SE) practices in five phases of the software development life-cycle: requirement engineering, design, development, quality assurance, and deployment. Results: We find some interesting differences in software engineering practices in ML startups and general software startups. The data management and model learning phases are the most prominent among them. Conclusion: While ML startups face many similar challenges to general software startups, the additional difficulties of using stochastic ML models require different strategies in using software engineering practices to produce high-quality products.

Original languageEnglish
Title of host publicationProceedings - 2023 IEEE/ACIS 21st International Conference on Software Engineering Research, Management and Applications, SERA 2023
EditorsYeong-Tae Song, Junghwan Rhee, Yuseok Jeon
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages39-46
Number of pages8
ISBN (Electronic)9798350345889
DOIs
StatePublished - 2023
Event21st IEEE/ACIS International Conference on Software Engineering Research, Management and Applications, SERA 2023 - Orlando, United States
Duration: 23 May 202325 May 2023

Publication series

NameProceedings - 2023 IEEE/ACIS 21st International Conference on Software Engineering Research, Management and Applications, SERA 2023

Conference

Conference21st IEEE/ACIS International Conference on Software Engineering Research, Management and Applications, SERA 2023
Country/TerritoryUnited States
CityOrlando
Period23/05/2325/05/23

Keywords

  • Machine Learning Startups
  • Software Engineering
  • Software Startups
  • Systematic Literature Review

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