Towards an Incident Management Framework in Proprietary Software Ecosystems
- URL: http://arxiv.org/abs/2410.09320v1
- Date: Sat, 12 Oct 2024 01:25:25 GMT
- Title: Towards an Incident Management Framework in Proprietary Software Ecosystems
- Abstract summary: This work introduces a framework for incident management to support the organizations' management teams in the PSECO context.
The IM Framework comprises five core categories: organizational goals, practices, success factors, associated benefits, and prevalent barriers.
- Score: 0.0
- License: http://creativecommons.org/licenses/by-nc-nd/4.0/
- Abstract: In the evolving landscape of Software Engineering, the paradigm of software ecosystems has emerged, giving rise to proprietary software ecosystems (PSECO), with their central organizations known as keystones. PSECO is characterized by the contribution of various technologies produced as private and protected by intellectual property and confidentiality agreements, centered on common technological platforms. Sustaining these PSECO technological platforms is vital, as any incident can have substantial repercussions. This work introduces a framework for incident management to support the organizations' management teams in the PSECO context, called IM Framework. The IM Framework was developed in close collaboration with practitioners across a large international organization. We grounded the IM Framework based on the results of a rapid review study that retrieved 293 studies, of which 23 were selected after applying review procedures. This framework comprises five core categories: organizational goals, practices, success factors, associated benefits, and prevalent barriers. The IM Framework offers practical guidance for the PSECO management team, focusing on real-world applications to enhance reliability and resilience in a complex and dynamic software environment. Our study also promises to fill the gap in incident management governance by supporting the PSECO organization's management team and maintaining robust technological platforms amidst evolving business demands and market pressures.
Related papers
- Modeling Dependency-Propagated Ecosystem Impact of Changes in Maintenance Activities: Evaluating Support Strategies in the PyPI Network [83.16077040470975]
We introduce a dependency-aware model of ecosystem impact that captures how changes in maintenance activities propagate through the Python Package Index (PyPI) ecosystem.<n>Our results show that a large share of the modeled ecosystem impact can be attributed to just 0.1% of all PyPI packages when prioritized based on dependency-propagated impact.
arXiv Detail & Related papers (2026-05-07T12:51:00Z) - Software-Defined Vehicle Ecosystems in Transformation -- A Systematic Literature Review [2.2217889677440272]
The automotive industry is shifting from hardware-centric development toward software-defined vehicles (SDVs)<n>Growing software complexity renders firm-centric and proprietary software development models insufficient.<n>How these SDV ecosystems emerge and operate in response to software-driven development remains insufficiently understood.
arXiv Detail & Related papers (2026-02-24T11:49:57Z) - Impostor Phenomenon as Human Debt: A Challenge to the Future of Software Engineering [46.44607910934403]
The Impostor Phenomenon (IP) impacts a significant portion of the Software Engineering workforce.<n>Similar to technical debt, Human Debt accumulates due to gaps in psychological safety and inclusive support within socio-technical ecosystems.
arXiv Detail & Related papers (2026-02-14T13:26:38Z) - S3C2 SICP Summit 2025-06: Vulnerability Response Summit [51.90004414779634]
Researchers from the NSF-supported Secure Software Supply Chain Center (S3C2) and the Software Innovation Campus Paderborn (SICP) conducted a Vulnerability Response Summit.<n>The goal of the Summit is to enable sharing between industry practitioners having practical experiences and challenges with software supply chain security.
arXiv Detail & Related papers (2025-12-02T10:05:41Z) - A Survey of Vibe Coding with Large Language Models [93.88284590533242]
"Vibe Coding" is a development methodology where developers validate AI-generated implementations through outcome observation.<n>Despite its transformative potential, the effectiveness of this emergent paradigm remains under-explored.<n>This survey provides the first comprehensive and systematic review of Vibe Coding with large language models.
arXiv Detail & Related papers (2025-10-14T11:26:56Z) - Perspectives, Needs and Challenges for Sustainable Software Engineering Teams: A FinServ Case Study [0.5097809301149341]
This research focuses on a financial services company (FinServCo) that invited us to investigate perceptions of sustainability in their IT function.<n>We conducted an exploratory qualitative case study using interviews and a focus group with six higher management employees and 16 software engineers.<n>Our study found a clear divergence in how sustainability is perceived between organisational levels.
arXiv Detail & Related papers (2025-09-15T21:21:02Z) - SCOR: A Framework for Responsible AI Innovation in Digital Ecosystems [0.2864713389096699]
AI-driven digital ecosystems span diverse stakeholders including technology firms, regulators, accelerators and civil society.<n>This paper proposes a four-pillar framework (SCOR) to embed accountability, fairness, and inclusivity across such multi-actor networks.
arXiv Detail & Related papers (2025-09-12T19:29:51Z) - Charting Uncertain Waters: A Socio-Technical Framework for Navigating GenAI's Impact on Open Source Communities [53.812795099349295]
We conduct a scenario-driven, conceptual exploration using a socio-technical framework inspired by McLuhan's Tetrad to surface both risks and opportunities for community resilience amid GenAI-driven disruption of OSS development across four domains: software practices, documentation, community engagement, and governance.<n>By adopting this lens, OSS leaders and researchers can proactively shape the future of their ecosystems, rather than simply reacting to technological upheaval.
arXiv Detail & Related papers (2025-08-06T22:54:15Z) - Psychological safety in software workplaces: A systematic literature review [0.8331356470329141]
Psychological safety (PS) is an important factor influencing team well-being and performance.<n>Despite its acknowledged significance, research on PS within the field of software engineering remains limited.
arXiv Detail & Related papers (2025-08-05T12:19:17Z) - Greening AI-enabled Systems with Software Engineering: A Research Agenda for Environmentally Sustainable AI Practices [70.24403396375277]
The "Greening AI with Software Engineering" CECAM-Lorentz workshop was held February 3-7, 2025 in Lausanne, Switzerland.<n>This report presents a research agenda emerging from the workshop.<n>It outlines open research directions and practical recommendations to guide the development of environmentally sustainable AI-enabled systems.
arXiv Detail & Related papers (2025-06-02T15:19:49Z) - Federated Learning for Cyber Physical Systems: A Comprehensive Survey [49.54239703000928]
Federated learning (FL) has become increasingly popular in recent years.<n>The article scrutinizes how FL is utilized in critical CPS applications, e.g., intelligent transportation systems, cybersecurity services, smart cities, and smart healthcare solutions.
arXiv Detail & Related papers (2025-05-08T01:17:15Z) - In-House Evaluation Is Not Enough: Towards Robust Third-Party Flaw Disclosure for General-Purpose AI [93.33036653316591]
We call for three interventions to advance system safety.
First, we propose using standardized AI flaw reports and rules of engagement for researchers.
Second, we propose GPAI system providers adopt broadly-scoped flaw disclosure programs.
Third, we advocate for the development of improved infrastructure to coordinate distribution of flaw reports.
arXiv Detail & Related papers (2025-03-21T05:09:46Z) - Transforming the Hybrid Cloud for Emerging AI Workloads [81.15269563290326]
This white paper envisions transforming hybrid cloud systems to meet the growing complexity of AI workloads.
The proposed framework addresses critical challenges in energy efficiency, performance, and cost-effectiveness.
This joint initiative aims to establish hybrid clouds as secure, efficient, and sustainable platforms.
arXiv Detail & Related papers (2024-11-20T11:57:43Z) - Lingma SWE-GPT: An Open Development-Process-Centric Language Model for Automated Software Improvement [62.94719119451089]
Lingma SWE-GPT series learns from and simulating real-world code submission activities.
Lingma SWE-GPT 72B resolves 30.20% of GitHub issues, marking a significant improvement in automatic issue resolution.
arXiv Detail & Related papers (2024-11-01T14:27:16Z) - Estimating the Energy Footprint of Software Systems: a Primer [56.200335252600354]
quantifying the energy footprint of a software system is one of the most basic activities.
This document aims to be a starting point for researchers who want to begin conducting work in this area.
arXiv Detail & Related papers (2024-07-16T11:21:30Z) - An Actionable Framework for Understanding and Improving Talent Retention
as a Competitive Advantage in IT Organizations [44.342141516382284]
This work presents an actionable framework for Talent Retention (TR) used in IT organizations.
Our framework encompasses a set of factors, contextual characteristics, barriers, strategies, and coping mechanisms.
Our findings indicated that software engineers can be differentiated from other professional groups.
arXiv Detail & Related papers (2024-02-02T17:08:14Z) - Survey on Foundation Models for Prognostics and Health Management in
Industrial Cyber-Physical Systems [1.1034992901877594]
Large-scale foundation models (LFMs) like BERT and GPT signifies a significant advancement in AI technology.
ChatGPT stands as a remarkable accomplishment within this research paradigm, harboring potential for General Artificial Intelligence.
Considering the ongoing enhancement in data acquisition technology and data processing capability, LFMs are anticipated to assume a crucial role in the PHM domain of ICPS.
arXiv Detail & Related papers (2023-12-11T09:58:46Z) - On-Premise AIOps Infrastructure for a Software Editor SME: An Experience
Report [0.3277163122167433]
The concept of AIOps has emerged to enhance predictive maintenance using Big Data and Machine Learning capabilities.
This paper investigates the feasibility of implementing on-premise AIOps solutions by leveraging open-source tools.
arXiv Detail & Related papers (2023-08-22T06:47:36Z) - An Introduction to Software Ecosystems [7.574742446357262]
This chapter defines and presents different kinds of software ecosystems.
The focus is on the development, tooling and analytics aspects of software ecosystems.
The chapter also introduces and clarifies the relevant terms needed to understand and analyse these ecosystems.
arXiv Detail & Related papers (2023-07-28T17:58:59Z) - Devops And Agile Methods Integrated Software Configuration Management
Experience [0.0]
The aim of this study is to examine the differences and benefits that innovative methods bring to the software configuration management field when compared to traditional methods.
Improvements are seen in the build and deployment time, automated report generation, more accurate and fault-free version management.
arXiv Detail & Related papers (2023-06-24T13:40:27Z) - 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) - Leveraging traditional ecological knowledge in ecosystem restoration
projects utilizing machine learning [77.34726150561087]
Community engagement throughout the stages of ecosystem restoration projects could contribute to improved community well-being.
We suggest that adaptive and scalable practices could incentivize interdisciplinary collaboration during all stages of ecosystemic ML restoration projects.
arXiv Detail & Related papers (2020-06-22T16:17:48Z)
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.