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Dr Nelly Bencomo's Outputs (54)

Surprise! Surprise! Learn and Adapt (2024)
Presentation / Conference Contribution
Samin, H., Walton, D., & Bencomo, N. (2025, May). Surprise! Surprise! Learn and Adapt. Presented at 24th International Conference on Autonomous Agents and Multiagent Systems, Detroit, Michigan, USA

Self-adaptive systems (SAS) adjust their behavior at runtime in response to environmental changes, which are often unpredictable at design time. SAS must make decisions under uncertainty, balancing trade-offs between quality attributes (e.g., cost mi... Read More about Surprise! Surprise! Learn and Adapt.

Beyond Syntax: How Do LLMs Understand Code? (2024)
Presentation / Conference Contribution
North, M., Atapour-Abarghouei, A., & Bencomo, N. (2025, April). Beyond Syntax: How Do LLMs Understand Code?. Presented at 2025 IEEE/ACM International Conference on Software Engineering ICSE, Ottawa , Canada

Within software engineering research, Large Language Models (LLMs) are often treated as 'black boxes', with only their inputs and outputs being considered. In this paper, we take a machine interpretability approach to examine how LLMs internally repr... Read More about Beyond Syntax: How Do LLMs Understand Code?.

Declarative Lifecycle Management in Digital Twins (2024)
Presentation / Conference Contribution
Bencomo, N., Kamburjan, E., Tapia Tarifa, S. L., & Broch-Johnsen, E. (2024, September). Declarative Lifecycle Management in Digital Twins. Presented at 1st International Conference on Engineering Digital Twins (EDTconf 2024), Linz, Austria

Together, a digital twin and its physical counterpart can be seen as a self-adaptive system: the digital twin monitors the physical system, updates its own internal model of the physical system, and adjusts the physical system by means of controllers... Read More about Declarative Lifecycle Management in Digital Twins.

Code Gradients: Towards Automated Traceability of LLM-Generated Code (2024)
Presentation / Conference Contribution
North, M., Atapour-Abarghouei, A., & Bencomo, N. (2024, June). Code Gradients: Towards Automated Traceability of LLM-Generated Code. Presented at 2024 IEEE 32nd International Requirements Engineering Conference (RE), Reykjavik, Iceland

Large language models (LLMs) have recently seen huge growth in capability and usage. Within software engineering, LLMs are increasingly being used by developers to generate code. Code generated by an LLM can be seen essentially a continuous mapping f... Read More about Code Gradients: Towards Automated Traceability of LLM-Generated Code.

Uncertainty Flow Diagrams: Towards a Systematic Representation of Uncertainty Propagation and Interaction in Adaptive Systems (2024)
Presentation / Conference Contribution
Camara, J., Hahner, S., Perez-Palacin, D., Vallecillo, A., Acosta, M., Bencomo, N., Calinescu, R., & Gerasimou, S. (2024, April). Uncertainty Flow Diagrams: Towards a Systematic Representation of Uncertainty Propagation and Interaction in Adaptive Systems. Presented at 2024 IEEE/ACM 19th Symposium on Software Engineering for Adaptive and Self-Managing Systems, Lisbon, Portugal

Sources of uncertainty in adaptive systems are rarely independent, and their interaction can affect the attainment of system goals in unpredictable ways. Despite ample work on “taming” uncertainty, the research community has devoted little attention... Read More about Uncertainty Flow Diagrams: Towards a Systematic Representation of Uncertainty Propagation and Interaction in Adaptive Systems.

Latency-aware RDMSim: Enabling the Investigation of Latency in Self-Adaptation for the Case of Remote Data Mirroring (2024)
Presentation / Conference Contribution
Götz, S., Samin, H., & Bencomo, N. (2024, April). Latency-aware RDMSim: Enabling the Investigation of Latency in Self-Adaptation for the Case of Remote Data Mirroring. Presented at SEAMS '24: 19th International Conference on Software Engineering for Adaptive and Self-Managing Systems, Lisbon, Portugal

Self-adaptive systems are able to adapt themselves according to changing contextual conditions to ensure a set of predefined objectives (e.g., certain non-functional requirements like reliability) is reached. For this, they perform adaptation actions... Read More about Latency-aware RDMSim: Enabling the Investigation of Latency in Self-Adaptation for the Case of Remote Data Mirroring.

Responsible AI governance: A response to UN interim report on governing AI for humanity (2024)
Report
Bencomo, N., Kiden, S., Deshmukh, J., Williams, J., Ramchurn, G., Stein, S., Yazdanpanah, V., Stahl, B., Townsend, B., Maple, C., Vincent, C., Sampson, F., Gilbert, G., Ross, J., Martinez del Rincon, J., Lisinska, J., O’Shea, K., Da Costa Abreu, M., Deb, O., Winter, P., …Iniesta, R. (2024). Responsible AI governance: A response to UN interim report on governing AI for humanity. United Nations

A response to UN interim report on governing AI for humanity

Decision Making for Self-adaptation based on Partially Observable Satisfaction of Non-Functional Requirements (2024)
Journal Article
Garcia, L., Samin, H., & Bencomo, N. (2024). Decision Making for Self-adaptation based on Partially Observable Satisfaction of Non-Functional Requirements. ACM Transactions on Autonomous and Adaptive Systems, 19(2), 1-44. https://doi.org/10.1145/3643889

Approaches that support the decision-making of self-adaptive and autonomous systems (SAS) often consider an idealized situation where (i) the system’s state is treated as fully observable by the monitoring infrastructure, and (ii) adaptation actions... Read More about Decision Making for Self-adaptation based on Partially Observable Satisfaction of Non-Functional Requirements.

Automated Provenance Collection at Runtime as a Cross-Cutting Concern (2023)
Presentation / Conference Contribution
James Reynolds, O., García-Domínguez, A., & Bencomo, N. (2023, October). Automated Provenance Collection at Runtime as a Cross-Cutting Concern. Presented at 2023 ACM/IEEE International Conference on Model Driven Engineering Languages and Systems Companion (MODELS-C), Västerås, Sweden

Autonomous decision-making is increasingly applied to handle highly dynamic, uncertain environments: as incorrect decisions can cause serious harm to individuals or society, there is a need for accountability. For systems that use runtime models to r... Read More about Automated Provenance Collection at Runtime as a Cross-Cutting Concern.

To download or not to download the Covid-19 Track and Trace App? What is more influential in users’ minds? (2023)
Journal Article
Sutcliffe, A., Bencomo, N., Darby, A., Paucar, L. H., & Sawyer, P. (2023). To download or not to download the Covid-19 Track and Trace App? What is more influential in users’ minds?. International Journal of Human-Computer Studies, 180, Article 103140. https://doi.org/10.1016/j.ijhcs.2023.103140

Objectives
to investigate the role of values in technology acceptance in general and in the context of the UK Covid Track and Trace App.

Methods
A survey and interview study was conducted to elicit users’ perceptions of values in general, values... Read More about To download or not to download the Covid-19 Track and Trace App? What is more influential in users’ minds?.

History-aware explanations: towards enabling human-in-the-loop in self-adaptive systems (2022)
Presentation / Conference Contribution
Parra-Ullauri, J., Garcia-Dominguez, A., Bencomo, N., & Garcia Paucar, L. (2022, October). History-aware explanations: towards enabling human-in-the-loop in self-adaptive systems. Presented at MODELS '22: 25th International Conference on Model Driven Engineering Languages and Systems, Montreal, Canada

The complexity of real-world problems requires modern software systems to autonomously adapt and modify their behaviour at run time to deal with internal and external challenges and contexts. Consequently, these self-adaptive systems (SAS) can show u... Read More about History-aware explanations: towards enabling human-in-the-loop in self-adaptive systems.

The Implications of ‘Soft’ Requirements (2022)
Presentation / Conference Contribution
Sutcliffe, A., Sawyer, P., & Bencomo, N. (2022, August). The Implications of ‘Soft’ Requirements. Presented at IEEE International Requirements Engineering Conference (RE), Melbourne, Australia

A new focus for RE is investigated as ‘soft’ requirements which extends non-functional requirements / soft goals with a collection of people-oriented phenomena: values, motivations, emotions, and other socio-political issues that may influence the re... Read More about The Implications of ‘Soft’ Requirements.

The Uncertainty Interaction Problem in Self-Adaptive Systems (2022)
Journal Article
Camara, J., Troya1, J., Vallecillo, A., Bencomo, N., Calinescu, R., Cheng, B., Garlan, D., & Schmerl, B. (2022). The Uncertainty Interaction Problem in Self-Adaptive Systems. Software and Systems Modeling, 21(4), 1277-1294. https://doi.org/10.1007/s10270-022-01037-6

The problem of mitigating uncertainty in self-adaptation has driven much of the research proposed in the area of software engineering for self-adaptive systems in the last decade. Although many solutions have already been proposed, most of them tend... Read More about The Uncertainty Interaction Problem in Self-Adaptive Systems.

Decision-Making Support for Adaptive Learning Management Systems based on Bayesian Inference (2022)
Presentation / Conference Contribution
Bencomo, N., Samin, H., & Pavlich-Mariscal, J. (2022, July). Decision-Making Support for Adaptive Learning Management Systems based on Bayesian Inference. Paper presented at CausalEDM'22, Durham

A novel approach will be applied to the domain of virtual education, which involves an adaptive learning management system using Bayesian Learning. The student's progress is considered partially observable based on what has been monitored. The acquir... Read More about Decision-Making Support for Adaptive Learning Management Systems based on Bayesian Inference.

A Bayesian Network-based model to understand the role of soft requirements in technology acceptance: the Case of the NHS COVID-19 Test and Trace App in England and Wales (2022)
Presentation / Conference Contribution
Garcia-Paucar, L., Bencomo, N., Sutcliffe, A., & Sawyer, P. (2022, April). A Bayesian Network-based model to understand the role of soft requirements in technology acceptance: the Case of the NHS COVID-19 Test and Trace App in England and Wales. Presented at 37th Annual ACM Symposium on Applied Computing (ACM SAC'2022), Brno, Czech Republic

Soft requirements (such as human values, motivations, and personal attitudes) can strongly influence technology acceptance. As such, we need to understand, model and predict decisions made by end users regarding the adoption and utilization of softwa... Read More about A Bayesian Network-based model to understand the role of soft requirements in technology acceptance: the Case of the NHS COVID-19 Test and Trace App in England and Wales.

Decision-making under uncertainty: be aware of your priorities (2022)
Journal Article
Samin, H., Bencomo, N., & Sawyer, P. (2022). Decision-making under uncertainty: be aware of your priorities. Software and Systems Modeling, 21(6), 2213-2242. https://doi.org/10.1007/s10270-021-00956-0

Self-adaptive systems (SASs) are increasingly leveraging autonomy in their decision-making to manage uncertainty in their operating environments. A key problem with SASs is ensuring their requirements remain satisfied as they adapt. The trade-off ana... Read More about Decision-making under uncertainty: be aware of your priorities.

Gamified and Self-Adaptive Applications for the Common Good: Research Challenges Ahead (2021)
Presentation / Conference Contribution
Bucchiarone, A., Cicchetti, A., Bencomo, N., Loria, E., & Marconi, A. (2021, December). Gamified and Self-Adaptive Applications for the Common Good: Research Challenges Ahead. Presented at 16th International Symposium on Software Engineering for Adaptive and Self-Managing Systems, SEAMS@ICSE 2021, Madrid, Spain, May 18-24, 2021

Towards Technology Acceptance: a Bayesian Network of soft requirements, the case of the NHS COVID-19 Test and Trace App (2021)
Presentation / Conference Contribution
Paucar, L. H. G., Bencomo, N., Sutcliffe, A. G., Yue, T., & Mirakhorli, M. (2021, December). Towards Technology Acceptance: a Bayesian Network of soft requirements, the case of the NHS COVID-19 Test and Trace App. Presented at 29th IEEE International Requirements Engineering Conference Workshops, RE 2021 Workshops, Notre Dame, IN, USA, September 20-24, 2021

From a Series of (Un)fortunate Events to Global Explainability of Runtime Model-Based Self-Adaptive Systems (2021)
Presentation / Conference Contribution
Ullauri, J. M. P., García-Domínguez, A., & Bencomo, N. (2021, December). From a Series of (Un)fortunate Events to Global Explainability of Runtime Model-Based Self-Adaptive Systems. Presented at ACM/IEEE International Conference on Model Driven Engineering Languages and Systems Companion, MODELS 2021 Companion, Fukuoka, Japan, October 10-15, 2021