Emanuela Guglielmi

I'm

About

Ph.D Student

Automated Testing and Recommender Systems for Complex Systems.

I was born in Campobasso (Italy) on March 31th, 1997. I received a Master’s Degree in Software Systems Security from the University of Molise (Italy) in 2021 defending a thesis on Software Reliability and Testing entitled “Generative Grammars and Deep Learning for Testing Voice User Interfaces” advised by Prof. Rocco Oliveto and Mr. Giovanni Rosa. I am currently a Ph.D. Student at the Department of Biosciences and Territory of University of Molise, advised by Prof. Simone Scalabrino and co-advised by Prof. Rocco Oliveto and Prof. Gabriele Bavota. My research interests include automated testing and recommender systems for complex systems (e.g., virtual assistants and video games).

  • Birthday: 31 March 1997
  • City: Campobasso, Italy
  • Degree: Master
  • Email: emanuela.guglielmi@unimol.it

Resume

Education

Ph.D Student

2021-present

University of Molise, Italy

Research Topics: Automated Testing and
Recommender Systems for Complex Systems

Master’s Degree

2019 - 2021

University of Molise, Italy

Software Systems Security

Bachelor’s Degree

2016 - 2019

University of Molise, Italy

Computer Science

Other Experience

Visiting Period

June 2022 - September 2022

Università della Svizzera Italiana, Lugano, Switzerland

Visiting PhD Student at Software Engineering Research Group (SEART), under the supervision of Prof. Gabriele Bavota

Publications

Using Gameplay Videos for Detecting Issues in Video Games

E. Guglielmi, S. Scalabrino, G. Bavota, R. Oliveto

Journal Paper

Empirical Software Engineering (EMSE), 2023

On the robustness of code generation techniques: An empirical study on github copilot

A. Mastropaolo, L. Pascarella, E. Guglielmi, M. Ciniselli, S. Scalabrino, R. Oliveto, G. Bavota

Conference Paper

45th IEEE/AC International Conference on Software Engineering (ICSE), 2023

Sorry, I don’t Understand: Improving Voice User Interface Testing

E. Guglielmi, S. Scalabrino, G. Bavota, R. Oliveto

Conference Paper

37th IEEE/ACM International Conference on Automated Software Engineering (ASE), 2022

Towards Using Gameplay Videos for Detecting Issues in Video Games

E. Guglielmi, S. Scalabrino, G. Bavota, R. Oliveto

Registred Report

19th International Conference on Mining Software Repositories (MSR), 2022

research interests

Assessing the quality of any software system is particularly complex when traditional testing techniques are not well adapted to the type of software system. The following are examples of such systems inherent to my research interests.

Voice User Interface
Testing

End users can interact with such applications through a voice user interface (VUI), uses natural language commands to perform actions. The use of different utterances to express the same command makes testing VUIs anything but trivial.

Video Games

The video game industry is constantly growing as a result there is increasing attention on video game quality, analyzing the differences between traditional software development and video game development. However, many games are released with problems that are only revealed when users start playing the game

Recommender System for developers

In automatic source code generation tools, the natural language description provided to the model to automatically generate a code function can substantially affect the output of the model. Receiving different recommendations for semantically equivalent natural language descriptions raises questions about the robustness and usability of such tools.

Contact

Location:

Contrada Fonte Lappone, Pesche (IS), Italy

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