Software Development in Startup Companies: The Greenfield Startup Model
- URL: http://arxiv.org/abs/2308.09438v1
- Date: Fri, 18 Aug 2023 10:08:10 GMT
- Title: Software Development in Startup Companies: The Greenfield Startup Model
- Authors: Carmine Giardino, Nicol\`o Paternoster, Michael Unterkalmsteiner, Tony
Gorschek, Pekka Abrahamsson
- Abstract summary: This study aims to improve understanding of the software development strategies employed by startups.
We packaged the results in the Greenfield Startup Model (GSM), which explains the priority of startups to release the product as quickly as possible.
The resulting implications of the GSM outline challenges and gaps, pointing out opportunities for future research to develop and validate engineering practices in the startup context.
- Score: 4.881718571745022
- License: http://creativecommons.org/licenses/by-nc-sa/4.0/
- Abstract: Software startups are newly created companies with no operating history and
oriented towards producing cutting-edge products. However, despite the
increasing importance of startups in the economy, few scientific studies
attempt to address software engineering issues, especially for early-stage
startups. If anything, startups need engineering practices of the same level or
better than those of larger companies, as their time and resources are more
scarce, and one failed project can put them out of business. In this study we
aim to improve understanding of the software development strategies employed by
startups. We performed this state-of-practice investigation using a grounded
theory approach. We packaged the results in the Greenfield Startup Model (GSM),
which explains the priority of startups to release the product as quickly as
possible. This strategy allows startups to verify product and market fit, and
to adjust the product trajectory according to early collected user feedback.
The need to shorten time-to-market, by speeding up the development through
low-precision engineering activities, is counterbalanced by the need to
restructure the product before targeting further growth. The resulting
implications of the GSM outline challenges and gaps, pointing out opportunities
for future research to develop and validate engineering practices in the
startup context.
Related papers
- Software engineering in start-up companies: An analysis of 88 experience
reports [3.944126365759018]
This study investigates how software engineering is applied in start-up context.
We identify the most frequently reported software engineering (requirements engineering, software design and quality) and business aspect (vision and strategy development) knowledge areas.
We conclude that most engineering challenges in start-ups stem from inadequacies in requirements engineering.
arXiv Detail & Related papers (2023-11-20T19:42:37Z) - Software-Intensive Product Engineering in Start-Ups: A Taxonomy [3.944126365759018]
Software start-ups are new companies aiming to launch an innovative product to mass markets fast with minimal resources.
However, most start-ups fail before realizing their potential.
This article aims to support further research on the field and serve as an engineering decision support tool for start-ups.
arXiv Detail & Related papers (2023-09-28T18:42:56Z) - Embedded Software Development with Digital Twins: Specific Requirements
for Small and Medium-Sized Enterprises [55.57032418885258]
Digital twins have the potential for cost-effective software development and maintenance strategies.
We interviewed SMEs about their current development processes.
First results show that real-time requirements prevent, to date, a Software-in-the-Loop development approach.
arXiv Detail & Related papers (2023-09-17T08:56:36Z) - Software Startups -- A Research Agenda [14.364137253888037]
This paper's research agenda focuses on software engineering in startups.
It identifies, in particular, 70+ research questions in the areas of supporting startup engineering activities.
We believe that with this research agenda we cover a wide spectrum of the software startup industry current needs.
arXiv Detail & Related papers (2023-08-24T14:20:21Z) - Software Engineering Knowledge Areas in Startup Companies: A Mapping
Study [3.944126365759018]
This study identifies and categorizes software engineering knowledge areas utilized in startups to map out the state-of-art.
Previous research does not provide reliable support for software engineering in any phase of a startup life cycle.
arXiv Detail & Related papers (2023-08-15T08:26:02Z) - What do we know about software development in startups? [4.881718571745022]
New ventures such as Facebook, Supercell, Linkedin, Spotify, WhatsApp, and Dropbox, are good examples of startups that evolved into successful businesses.
operating in a chaotic and rapidly evolving domain conveys new uncharted challenges for startuppers.
arXiv Detail & Related papers (2023-07-24T20:13:09Z) - Using Deep Learning to Find the Next Unicorn: A Practical Synthesis [42.70427723009158]
Venture Capital (VC) strives to identify and invest in unicorn startups during their early stages, hoping to gain a high return.
Over the past two decades, the industry has gone through a paradigm shift moving from conventional statistical approaches towards becoming machine-learning based.
In this work, we carry out a literature review and synthesis on DL-based approaches, covering the entire DL life cycle.
arXiv Detail & Related papers (2022-10-18T13:11:16Z) - Concepts and Algorithms for Agent-based Decentralized and Integrated
Scheduling of Production and Auxiliary Processes [78.120734120667]
This paper describes an agent-based decentralized and integrated scheduling approach.
Part of the requirements is to develop a linearly scaling communication architecture.
The approach is explained using an example based on industrial requirements.
arXiv Detail & Related papers (2022-05-06T18:44:29Z) - Empowered and Embedded: Ethics and Agile Processes [60.63670249088117]
We argue that ethical considerations need to be embedded into the (agile) software development process.
We put emphasis on the possibility to implement ethical deliberations in already existing and well established agile software development processes.
arXiv Detail & Related papers (2021-07-15T11:14:03Z) - Estimating Fund-Raising Performance for Start-up Projects from a Market
Graph Perspective [58.353799280109904]
We propose a Graph-based Market Environment (GME) model for predicting the fund-raising performance of the unpublished project by exploiting the market environment.
Specifically, we propose a Graph-based Market Environment (GME) model for predicting the fund-raising performance of the unpublished project by exploiting the market environment.
arXiv Detail & Related papers (2021-05-27T02:39:30Z) - Constraint Programming Algorithms for Route Planning Exploiting
Geometrical Information [91.3755431537592]
We present an overview of our current research activities concerning the development of new algorithms for route planning problems.
The research so far has focused in particular on the Euclidean Traveling Salesperson Problem (Euclidean TSP)
The aim is to exploit the results obtained also to other problems of the same category, such as the Euclidean Vehicle Problem (Euclidean VRP), in the future.
arXiv Detail & Related papers (2020-09-22T00:51:45Z)
This list is automatically generated from the titles and abstracts of the papers in this site.
This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.