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Software Engineering in Start-up Companies
Blekinge Institute of Technology, Faculty of Computing, Department of Software Engineering.ORCID iD: 0000-0002-1987-2234
2019 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

Start-up companies have emerged as suppliers of innovation and software-intensive products. Small teams, lack of legacy products, experimental nature, and absence of any organizational processes enable start-ups to develop and market new products and services quickly. However, most start-ups fail before delivering any value. Start-up failures can be attributed to market factors, shortcomings in business models, lack of motivation, or self-destruction, among other reasons. However, inadequacies in product engineering precede any market or business-related challenges and could be a significant contributing factor to start-up failures. At the same time, state-of-the-art software engineering (SE) practices are often neglected by start-ups as inadequate. At the beginning of this work, SE in start-ups had attracted very little attention from researchers. Thus, there was no coherent view of SE state-of-practice in start-ups and no starting point for a focused investigation.

 

In this thesis, we explore how start-ups practice SE, what specific SE challenges should be addressed, and what new SE practices are needed to support the engineering of innovative software-intensive products and services.

 

A substantial part of this work is exploratory and aimed to explore SE state-of-practice in start-ups. Our initial findings suggest that start-ups overlook the best SE practices. Teams of a few people working on relatively experimental and straightforward software see no upside of following the best practices. However, late start-ups face substantial challenges as their teams grow, and products become more complex. The key difficulties concern installing adequate SE practices supporting collaboration, coordination of work, and management of accumulated technical debt. To support the evolution of engineering practices in start-ups, we propose the start-up progression model outlining engineering goals, common challenges, and useful practices with regards to the start-up life-cycle phases. Further findings suggest inadequate support for market-driven requirements engineering (MDRE). Specifically, on how to aggregate needs and wishes of a large and loosely defined set of stakeholders who may not be able to articulate their needs and expectations. To address this challenge, we propose a method for the identification and prioritization of data sources and stakeholders in MDRE. Analyzing SE context in start-ups and other organizations developing innovative and market-driven products, we have found many similarities. While start-ups have challenges, they do not appear to be unique. Thus, most start-up challenges can be addressed by transferring the best practices from other engineering contexts.

 

We conclude that there is a little need for start-up specific engineering practices. Best software engineering practices are relevant to address challenges in start-ups. The key engineering challenge in start-ups is the management of the evolution of SE practices to match the growing complexity of the product and the organization. Our work also highlights the need for better MDRE practices to support new market-driven product development in both start-ups and other types of organizations. 

Place, publisher, year, edition, pages
Karlskrona: Blekinge Tekniska Högskola, 2019.
Series
Blekinge Institute of Technology Doctoral Dissertation Series, ISSN 1653-2090 ; 12
Keywords [en]
start-ups, software engineering, practices, models
National Category
Software Engineering
Identifiers
URN: urn:nbn:se:bth-18694ISBN: 978-91-7295-384-0 (print)OAI: oai:DiVA.org:bth-18694DiVA, id: diva2:1354736
Public defence
2019-12-16, J1516, Campus Grasvik, Karlskrona, 09:00 (English)
Opponent
Supervisors
Available from: 2019-10-21 Created: 2019-09-26 Last updated: 2021-05-24Bibliographically approved
List of papers
1. Software engineering in start-up companies: An analysis of 88 experience reports
Open this publication in new window or tab >>Software engineering in start-up companies: An analysis of 88 experience reports
2019 (English)In: Empirical Software Engineering, ISSN 1382-3256, E-ISSN 1573-7616, Vol. 24, no 1, p. 68-102Article in journal (Refereed) Published
Abstract [en]

Context: Start-up companies have become an important supplier of innovation and software-intensive products. The flexibility and reactiveness of start-ups enables fast development and launch of innovative products. However, a majority of software start-up companies fail before achieving any success. Among other factors, poor software engineering could be a significant contributor to the challenges experienced by start-ups. However, the state-of-practice of software engineering in start-ups, as well as the utilization of state-of-the-art is largely an unexplored area. Objective: In this study we investigate how software engineering is applied in start-up context with a focus to identify key knowledge areas and opportunities for further research. Method: We perform a multi-vocal exploratory study of 88 start-up experience reports. We develop a custom taxonomy to categorize the reported software engineering practices and their interrelation with business aspects, and apply qualitative data analysis to explore influences and dependencies between the knowledge areas. Results: We identify the most frequently reported software engineering (requirements engineering, software design and quality) and business aspect (vision and strategy development) knowledge areas, and illustrate their relationships. We also present a summary of how relevant software engineering knowledge areas are implemented in start-ups and identify potentially useful practices for adoption in start-ups. Conclusions: The results enable a more focused research on engineering practices in start-ups. We conclude that most engineering challenges in start-ups stem from inadequacies in requirements engineering. Many promising practices to address specific engineering challenges exists, however more research on adaptation of established practices, and validation of new start-up specific practices is needed. © 2018 The Author(s)

Place, publisher, year, edition, pages
Springer New York LLC, 2019
Keywords
Experience reports, Software engineering practices, Software start-up, Requirements engineering, Engineering challenges, Engineering knowledge, Engineering practices, Experience report, Exploratory studies, Qualitative data analysis, Strategy development, Software design
National Category
Software Engineering
Identifiers
urn:nbn:se:bth-16246 (URN)10.1007/s10664-018-9620-y (DOI)000458634400003 ()2-s2.0-85047198507 (Scopus ID)
Note

open access

Available from: 2018-05-31 Created: 2018-05-31 Last updated: 2022-09-15Bibliographically approved
2. Software Engineering Anti-Patterns in Start-Ups
Open this publication in new window or tab >>Software Engineering Anti-Patterns in Start-Ups
2019 (English)In: IEEE Software, ISSN 0740-7459, E-ISSN 1937-4194, Vol. 36, no 2, p. 118-126Article in journal (Refereed) Published
Abstract [en]

Software start-up failures are often explained with a poor business model, market issues, insufficient funding, or simply a bad product idea. However, inadequacies in software engineering are relatively unexplored and could be a significant contributing factor to the high start-up failure rate. In this paper we present the analysis of 88 start-up experience reports, revealing three anti-patterns associated with start-up progression phases. The anti-patterns address challenges of releasing the first version of the product, attracting customers, and expanding the product into new markets. The anti-patterns show that challenges and failure scenarios that appear to be business or market related are, at least partially, rooted in engineering inadequacies.

Place, publisher, year, edition, pages
IEEE Computer Society, 2019
Keywords
Software Engineering, Software Start-ups, Software quality
National Category
Software Engineering
Identifiers
urn:nbn:se:bth-17450 (URN)10.1109/MS.2018.227105530 (DOI)000459536000018 ()
Available from: 2019-01-10 Created: 2019-01-10 Last updated: 2022-11-30Bibliographically approved
3. A progression model of software engineering goals, challenges, and practices in start-ups
Open this publication in new window or tab >>A progression model of software engineering goals, challenges, and practices in start-ups
Show others...
2021 (English)In: IEEE Transactions on Software Engineering, ISSN 0098-5589, E-ISSN 1939-3520, Vol. 47, no 3, p. 498-521Article in journal (Refereed) Published
Abstract [en]

Context: Software start-ups are emerging as suppliers of innovation and software-intensive products. However, traditional software engineering practices are not evaluated in the context, nor adopted to goals and challenges of start-ups. As a result, there is insufficient support for software engineering in the start-up context. IEEE

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers Inc., 2021
Keywords
Analytical models, Companies, Market opportunities, progression model, Requirements engineering, Software, Software engineering, software engineering practices, software start-up, Computer software, Industry
National Category
Software Engineering
Identifiers
urn:nbn:se:bth-17706 (URN)10.1109/TSE.2019.2900213 (DOI)000631200300004 ()2-s2.0-85061979918 (Scopus ID)
Available from: 2019-03-07 Created: 2019-03-07 Last updated: 2021-05-24Bibliographically approved
4. Exploration of technical debt in start-ups
Open this publication in new window or tab >>Exploration of technical debt in start-ups
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2018 (English)In: Proceedings - International Conference on Software Engineering, IEEE Computer Society , 2018, p. 75-84Conference paper, Published paper (Refereed)
Abstract [en]

Context: Software start-ups are young companies aiming to build and market software-intensive products fast with little resources. Aiming to accelerate time-to-market, start-ups often opt for ad-hoc engineering practices, make shortcuts in product engineering, and accumulate technical debt. Objective: In this paper we explore to what extent precedents, dimensions and outcomes associated with technical debt are prevalent in start-ups. Method: We apply a case survey method to identify aspects of technical debt and contextual information characterizing the engineering context in start-ups. Results: By analyzing responses from 86 start-up cases we found that start-ups accumulate most technical debt in the testing dimension, despite attempts to automate testing. Furthermore, we found that start-up team size and experience is a leading precedent for accumulating technical debt: larger teams face more challenges in keeping the debt under control. Conclusions: This study highlights the necessity to monitor levels of technical debt and to preemptively introduce practices to keep the debt under control. Adding more people to an already difficult to maintain product could amplify other precedents, such as resource shortages, communication issues and negatively affect decisions pertaining to the use of good engineering practices. © 2018 ACM.

Place, publisher, year, edition, pages
IEEE Computer Society, 2018
Series
Proceedings - International Conference on Software Engineering, ISSN 0270-5257
Keywords
Software start-ups, Technical debt, Commerce, Case surveys, Contextual information, Engineering practices, Good engineering practices, Product engineering, Resource shortage, Technical debts, Time to market, Software engineering
National Category
Software Engineering
Identifiers
urn:nbn:se:bth-16893 (URN)10.1145/3183519.3183539 (DOI)000576755600010 ()2-s2.0-85049673180 (Scopus ID)9781450356596 (ISBN)
Conference
40th ACM/IEEE International Conference on Software Engineering: Software Engineering in Practice, ICSE-SEIP 2018; Gothenburg
Available from: 2018-08-20 Created: 2018-08-20 Last updated: 2021-05-24Bibliographically approved
5. Use of Agile Practices in Start-ups
Open this publication in new window or tab >>Use of Agile Practices in Start-ups
Show others...
(English)Manuscript (preprint) (Other academic)
Abstract [en]

Context. Software start-ups have shown their ability to develop and launch in- novative software products and services. Small, motivated teams and uncertain project scope makes start-ups good candidates for adopting Agile practices.

Objective. We explore how start-ups use Agile practices and what effects can be associated with the use of those practices.

Method. We use a case survey to analyze 84 start-up cases and 56 Agile prac- tices. We apply statistical methods to test for statistically significant associa- tions between the use of Agile practices, team, and product factors.

Results. Our results suggest that backlog, version control, refactoring, and user stories are the most frequently reported practices. We identify 22 associations between the use of Agile practices, team, and product factors. The use of Agile practices is associated with effects on source code and overall product quality. A teams’ positive or negative attitude towards best engineering practices is a significant indicator for either adoption or rejection of certain Agile practices. To explore the relationships in our findings, we set forth a number of propositions that can be investigated by future research.

Conclusions. We conclude that start-ups use Agile practices, however without following any specific methodology. We identify the opportunity for more fine- grained studies into the adoption and effects of individual Agile practices. Start- up practitioners could benefit from Agile practices in terms of better overall quality, tighter control over team performance and resource utilization.

National Category
Software Engineering
Identifiers
urn:nbn:se:bth-18864 (URN)
Available from: 2019-11-04 Created: 2019-11-04 Last updated: 2021-05-24Bibliographically approved
6. Software start-ups through an empirical lens: Are start-ups snowflakes?
Open this publication in new window or tab >>Software start-ups through an empirical lens: Are start-ups snowflakes?
2018 (English)In: CEUR Workshop Proceedings / [ed] Wang X.,Munch J.,Suominen A.,Bosch J.,Jud C.,Hyrynsalmi S., CEUR-WS , 2018Conference paper, Published paper (Refereed)
Abstract [en]

Most of the existing research assume that software start-ups are “unique” and require a special approach to software engineering. The uniqueness of start-ups is often justified by the scarcity of resources, time pressure, little operating history, and focus on innovation. As a consequence, most research on software start-ups concentrate on exploring the start-up context and are overlooking the potential of transferring the best engineering practices from other contexts to start-ups. In this paper, we examine results from an earlier mapping study reporting frequently used terms in literature used to characterize start-ups. We analyze how much empirical evidence support each characteristic, and how unique each characteristic is in the context of innovative, market-driven, software-intensive product development. Our findings suggest that many of the terms used to describe startups originate from anecdotal evidence and have little empirical backing. Therefore, there is a potential to revise the original start-up characterization. In conclusion, we identify three potential research avenues for further work: a) considering shareholder perspective in product decisions, b) providing support for software engineering in rapidly growing organizations, and c) focusing on transferring the best engineering practices from other contexts to start-ups. © 2018 CEUR-WS. All rights reserved.

Place, publisher, year, edition, pages
CEUR-WS, 2018
Series
CEUR Workshop Proceedings, ISSN 1613-0073
Keywords
Engineering context, Software engineering, Start-ups, Boron compounds, Ecosystems, Engineering research, Silicon compounds, Tungsten compounds, Anecdotal evidences, Engineering practices, Further works, Mapping studies, Market driven, Potential researches, Time pressures, C (programming language)
National Category
Software Engineering
Identifiers
urn:nbn:se:bth-17590 (URN)2-s2.0-85060578194 (Scopus ID)
Conference
1st International Workshop on Software-Intensive Business: Start-Ups, Ecosystems and Platforms, SiBW 2018, Espoo, Finland, 3 December 2018
Available from: 2019-02-11 Created: 2019-02-11 Last updated: 2021-05-24Bibliographically approved
7. A collaborative method for identification and prioritization of data sources in MDRE
Open this publication in new window or tab >>A collaborative method for identification and prioritization of data sources in MDRE
Show others...
(English)Manuscript (preprint) (Other academic)
Abstract [en]

Requirements engineering (RE) literature acknowledges the importance of stakeholder identification early in the software engineering activities. However, literature overlooks the challenge of identifying and selecting the right stakeholders and the potential of using other inanimate requirements sources for RE activities for market-driven products.

Market-driven products are influenced by a large number of stakeholders. Consulting all stakeholders directly is impractical, and companies utilize indirect data sources, e.g. documents and representatives of larger groups of stakeholders. However, without a systematic approach, companies often use easy to access or hard to ignore data sources for RE activities. As a consequence, companies waste resources on collecting irrelevant data or develop the product based on the input from a few sources, thus missing market opportunities.

We propose a collaborative and structured method to support analysts in the identification and selection of the most relevant data sources for market-driven product engineering. The method consists of four steps and aims to build consensus between different perspectives in an organization and facilitates the identification of most relevant data sources. We demonstrate the use of the method with two industrial case studies.

Our results show that the method can support market-driven requirements engineering in two ways: (1) by providing systematic steps to identify and prioritize data sources for RE, and (2) by highlighting and resolving discrepancies between different perspectives in an organization.

National Category
Software Engineering
Identifiers
urn:nbn:se:bth-18712 (URN)
Available from: 2019-09-29 Created: 2019-09-29 Last updated: 2021-05-25Bibliographically approved

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