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- discussionAugust 2024
Phillip Carter on Observability for Large Language Models
Presents a panel discussion on the topic of Observability for Large Language Models.
- research-articleAugust 2024
Computer <italic>Still</italic> Says …
It used to be a standing joke with computer systems when questioning their frequently suspicious outputs. You might call a computer support line to complain about a strange telephone bill, only to be told that the bill is correct because “Computer says …”...
- tutorialAugust 2024
Bringing Software Engineering Discipline to the Development of AI-Enabled Systems
- Miroslaw Staron,
- Silvia Abrahão,
- Grace Lewis,
- Henry Muccini,
- Chetan Honnenahalli,
- Miroslaw Staron,
- Silvia Abrahão
Engineering AI Software systems is starting to evolve from the pure development of machine learning (ML) models to a more structured discipline that treats ML components as part of much larger software systems. As such, more structured principles are ...
- research-articleFebruary 2024
Decentralized Governance-Driven Architecture for Designing Foundation-Model-Based Systems: Exploring the Role of Blockchain in Responsible AI
We identify eight governance challenges of foundation-model-based AI systems regarding the three fundamental dimensions of governance: decision rights, incentives, and accountability. Furthermore, we explore blockchain’s potential as an architectural ...
- tutorialFebruary 2024
Testing, Debugging, and Log Analysis With Modern AI Tools
This edition of the “Practitioners’ Digest” covers recent papers employing generative artificial intelligence in support of testing, debugging, and log analysis that were presented at the 38th IEEE/ACM International Conference on Automated Software ...
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- research-articleFebruary 2024
The State of Documentation Practices of Third-Party Machine Learning Models and Datasets
We use statistical analysis and hybrid card sorting to assess the state of the practice of documenting model cards and dataset cards in a large current model store, Hugging Face. Our findings reveal the lack of documentation of models and datasets, ...
- research-articleDecember 2023
Automation Doesn’t Work the Way We Think It Does
For resilience in complex and large-scale software systems, we need to go beyond observability and explainability and consider joint cognition between human–machine teams.
- research-articleDecember 2023
Navigating the Upcoming European Union AI Act
The upcoming Artificial Intelligence (AI) Act is the European Union’s attempt to regulate high-risk AI systems and foundation models. We give an up-to-date overview of the act’s key requirements, explain how the high-risk classification works, and ...
- research-articleDecember 2023
Commands as AI Conversations
Developers and data scientists often struggle to write command-line inputs, even though graphical interfaces or tools like ChatGPT can assist. The solution? “ai-cli,” an open-source system inspired by GitHub Copilot that converts natural language prompts ...
- research-articleDecember 2023
Artificial Intelligence for Cybersecurity
Cybersecurity attacks are on a steep increase across industry domains.1,2 With ubiquitous connectivity and increasingly standard software stacks, basically all software is accessible and vulnerable. Yet, cybersecurity is not systematically deployed ...
- discussionDecember 2023
Focusing on Developers in the Era of AI and ML
- Silvia Abrahão,
- Miroslaw Staron,
- Alexander Serebrenik,
- Birgit Penzenstadler,
- Rafael Prikladnicki,
- Henry Muccini,
- Silvia Abrahão,
- Miroslaw Staron
This edition of the “Practitioners’ Digest” covers recent articles and/or papers on novel approaches and tools to support developers and communities in the era of artificial intelligence from the Technical Track and the Software Engineering in Practice ...
- research-articleOctober 2023
SE4AI: A Training Program Considering Technical, Social, and Professional Aspects of AI-Based Software Systems
We share our experience developing a training program that provides trainees with technical, social, and professional knowledge in the context of artificial intelligence-based software systems. Survey results indicate the program has helped trainees ...
- research-articleOctober 2023
Explaining Black Boxes With a SMILE: Statistical Model-Agnostic Interpretability With Local Explanations
- Koorosh Aslansefat,
- Mojgan Hashemian,
- Martin Walker,
- Mohammed Naveed Akram,
- Ioannis Sorokos,
- Yiannis Papadopoulos
Explainability is a key aspect of improving trustworthiness. We therefore propose SMILE, a new method that builds on previous approaches by making use of statistical distance measures to improve explainability while remaining applicable to a wide range of ...
- research-articleOctober 2023
Explainability With Observation Sharing in Long Collaboration Chains of Automated Systems of Systems
- Paulius Daubaris,
- Simo Linkola,
- Juan F. Inglés-Romero,
- Javier Berrocal,
- Cristina Vicente-Chicote,
- Juan Manuel Murillo,
- Tommi Mikkonen,
- Niko Mäkitalo
This article introduces a blueprint architecture for long collaboration chains formed by systems of systems, provided by multiple companies, that can significantly improve the understanding of the processes and events taking place. We illustrate the ...
- research-articleSeptember 2023
Explaining Cyberphysical System Behavior With Digital Twins
We present a model-driven software architecture that combines the wealth of data, information, and models intrinsic to digital twins with techniques for the self-explainability of software systems to support domain experts in configuring, deploying, ...
- discussionOctober 2023
Can Architecture Knowledge Guide Software Development With Generative AI?
Incorporating architecture knowledge into data that large language models are trained on and to tools that software engineers use to solve large scoped development problems ranging from technology upgrades, language translation, to software evolution is ...
- research-articleAugust 2023
Uncertainty-Aware Virtual Sensors for Cyber-Physical Systems
We present a data pipeline to train and deploy uncertainty-aware virtual sensors in cyber-physical systems. Our virtual sensor predicts the expected values of a physical sensor and a standard deviation indicating the degree of uncertainty in its ...
- research-articleAugust 2023
Generative Artificial Intelligence Assistants in Software Development Education: A Vision for Integrating Generative Artificial Intelligence Into Educational Practice, Not Instinctively Defending Against It
The use of Generative AI in software development is gaining traction. But what are the potentials and implications on software development education? We gathered insights on the use of Generative AI from professional software developers and make some ...
- discussionNovember 2022
Can Software Engineering Harness the Benefits of Advanced AI?
Artificial intelligence (AI) has allowed us to build systems beyond anything deemed possible earlier. Can we evolve existing techniques in software engineering to meet the needs of AI enabled systems or do we need to build unique and novel tools to do so?
- opinionNovember 2022
AI Engineering: Realizing the Potential of AI
Artificial Intelligence (AI) engineering is an engineering discipline that is concerned with all aspects of development and evolution of AI systems (that is, systems that include AI components). AI engineering is primarily an extension of software ...