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Dr Nelly Bencomo's Outputs (35)

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.

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

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., …Gerasimou, S. (2024). Uncertainty Flow Diagrams: Towards a Systematic Representation of Uncertainty Propagation and Interaction in Adaptive Systems. In 2024 IEEE/ACM 19th Symposium on Software Engineering for Adaptive and Self-Managing Systems (SEAMS). https://doi.org/10.1145/3643915.3644084

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). Latency-aware RDMSim: Enabling the Investigation of Latency in Self-Adaptation for the Case of Remote Data Mirroring. In SEAMS '24: Proceedings of the 19th International Symposium on Software Engineering for Adaptive and Self-Managing Systems. https://doi.org/10.1145/3643915.3644106

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.

Automated Provenance Collection at Runtime as a Cross-Cutting Concern (2023)
Presentation / Conference Contribution
James Reynolds, O., García-Domínguez, A., & Bencomo, N. (2023). Automated Provenance Collection at Runtime as a Cross-Cutting Concern. In 2023 ACM/IEEE International Conference on Model Driven Engineering Languages and Systems Companion (MODELS-C) (276-285). https://doi.org/10.1109/MODELS-C59198.2023.00057

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.

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). History-aware explanations: towards enabling human-in-the-loop in self-adaptive systems. . https://doi.org/10.1145/3550356.3561538

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). The Implications of ‘Soft’ Requirements. In E. Knauss, G. Mussbacher, C. Arora, M. Bano, & J. Schneider (Eds.), 2022 IEEE 30th International Requirements Engineering Conference (RE) (178-188). https://doi.org/10.1109/re54965.2022.00022

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.

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). 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. . https://doi.org/10.1145/3477314.3507147

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.

Temporal Models for History-Aware Explainability (2020)
Presentation / Conference Contribution
Ullauri, J. M. P., García-Domínguez, A., Paucar, L. H. G., & Bencomo, N. (2020). Temporal Models for History-Aware Explainability. In A. Gherbi, W. Hamou-Lhadj, & A. Bali (Eds.), . https://doi.org/10.1145/3419804.3420276

On one hand, there has been a growing interest towards the application of AI-based learning and evolutionary programming for self-adaptation under uncertainty. On the other hand, self-explanation is one of the self-* properties that has been neglecte... Read More about Temporal Models for History-Aware Explainability.

RaM: Causally-Connected and Requirements-Aware Runtime Models using Bayesian Learning (2019)
Presentation / Conference Contribution
Bencomo, N., & Paucar, L. H. G. (2019). RaM: Causally-Connected and Requirements-Aware Runtime Models using Bayesian Learning. In M. Kessentini, T. Yue, A. Pretschner, S. Voss, & L. Burgueño (Eds.), . https://doi.org/10.1109/models.2019.00005

[Context/Motivation] A model at runtime can be defined as an abstract representation of a system, including its structure and behaviour, which exist alongside with the running system. Runtime models provide support for decision-making and reasoning b... Read More about RaM: Causally-Connected and Requirements-Aware Runtime Models using Bayesian Learning.

Software Engineering for Self-Adaptive Systems: Research Challenges in the Provision of Assurances (2013)
Presentation / Conference Contribution
Lemos, R. D., Garlan, D., Ghezzi, C., Giese, H., Andersson, J., Litoiu, M., Schmerl, B. R., Weyns, D., Baresi, L., Bencomo, N., Brun, Y., Cámara, J., Calinescu, R., Cohen, M. B., Gorla, A., Grassi, V., Grunske, L., Inverardi, P., Jézéquel, J.-M., Malek, S., …Zambonelli, F. (2013, December). Software Engineering for Self-Adaptive Systems: Research Challenges in the Provision of Assurances. Presented at Software Engineering for Self-Adaptive Systems III. Assurances - International Seminar, Dagstuhl Castle, Germany, December 15-19, 2013, Revised Selected and Invited Papers

The important concern for modern software systems is to become more cost-effective, while being versatile, flexible, resilient, dependable, energy-efficient, customisable, configurable and self-optimising when reacting to run-time changes that may oc... Read More about Software Engineering for Self-Adaptive Systems: Research Challenges in the Provision of Assurances.

Supporting Decision-Making for Self-Adaptive Systems: From Goal Models to Dynamic Decision Networks (2013)
Presentation / Conference Contribution
Bencomo, N., & Belaggoun, A. (2013, April). Supporting Decision-Making for Self-Adaptive Systems: From Goal Models to Dynamic Decision Networks. Presented at Requirements Engineering: Foundation for Software Quality - 19th International Working Conference, REFSQ 2013, Essen, Germany, April 8-11, 2013. Proceedings, Essen, Germany

[Context/Motivation] Different modeling techniques have been used to model requirements and decision-making of self-adaptive systems (SASs). Specifically, goal models have been prolific in supporting decision-making depending on partial and total ful... Read More about Supporting Decision-Making for Self-Adaptive Systems: From Goal Models to Dynamic Decision Networks.

Dynamic decision networks for decision-making in self-adaptive systems: a case study (2013)
Presentation / Conference Contribution
Bencomo, N., Belaggoun, A., & Issarny, V. (2013). Dynamic decision networks for decision-making in self-adaptive systems: a case study. In M. Litoiu, & J. Mylopoulos (Eds.), . https://doi.org/10.1109/seams.2013.6595498

Bayesian decision theory is increasingly applied to support decision-making processes under environmental variability and uncertainty. Researchers from application areas like psychology and biomedicine have applied these techniques successfully. Howe... Read More about Dynamic decision networks for decision-making in self-adaptive systems: a case study.