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A systematic literature review on trust in the software ecosystem
Abstract
The worldwide software ecosystem is a trust-rich part of the world. Throughout the software life cycle, software engineers, end-users, and other stakeholders collaboratively place their trust in major hubs in the ecosystem, such as package managers, repository services, and software components. However, as our reliance on software grows, this trust is frequently violated by bad actors and crippling vulnerabilities in the software supply chain. This study aims to define software trust in the worldwide SECO, that is, to determine what signifies a trustworthy system, actor, or hub. We conduct a systematic literature review on the concept of trust in the software ecosystem. We acknowledge that trust is something between two actors in the software ecosystem, and we examine what role trust plays in the relationships between end-users and (1) software products, (2) package managers, (3) software producing organizations, and (4) software engineers. Two major findings emerged from the systematic literature review. To begin, we define trust in the software ecosystem by examining the definition and characteristics of trust. Second, we provide a list of trust factors that can be used to assemble an overview of software trust. Trust is critical in the communication between actors in the worldwide software ecosystem, particularly regarding software selection and evaluation. With this comprehensive overview of trust, software engineering researchers have a new foundation to understand and use trust to create a trustworthy software ecosystem.
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“D'Angelo et al. [40] and Hou and Jansen [68] highlight the roles of control, expectation management, and reputation in shaping trust.”
From What Needs Attention? Prioritizing Drivers of Developers' Trust and Adoption of Generative AI (2025) · cites this paper as [68]
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“In addition to the financial cost, the time cost, such as time to market and project completion time, and potential cost risks that can impact the cost also need to be considered (Vargas et al. 2020; Mohagheghi and Conradi 2007).”
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Cai, Y., & Zhu, D. (2016) · Decision Support Systems · doi:10.1016/j.dss.2016.08.004 · Cited by 43
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Cited by
What Needs Attention? Prioritizing Drivers of Developers' Trust and Adoption of Generative AI
Choudhuri, R., Trinkenreich, B., Pandita, R., Kalliamvakou, E., Steinmacher, I., Gerosa, M., Sanchez, C., & Sarma, A. (2025) · arXiv · doi:10.48550/arxiv.2505.17418 · Cited by 14
On the Need to Rethink Trust in AI Assistants for Software Development: A Critical Review
Baltes, S., Speith, T., Chiteri, B., Mohsenimofidi, S., Chakraborty, S., & Buschek, D. (2026) · IEEE Transactions on Software Engineering · doi:10.1109/tse.2026.3659804 · Cited by 5
Metadata
- Authors
- Hou, F., & Jansen, S.
- ORCID
- Hou, Fang
- Venue
- Empirical Software Engineering
- Published
- 2022-11-23
- Volume
- 28
- Issue
- 1
- ISSN
- 1382-3256
- 1573-7616
- Cited by
- 48
- References
- 3
- Language
- en
- Licence
- creativecommons.org/licenses/by/4.0 (tdm)
- creativecommons.org/licenses/by/4.0 (vor)
- Funders
- TruBlo (Grant Agreement Number 957228)
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