Msc Thesis

Odoo is a highly-configurable web-based ERP for various management tasks (CRM, inventory management, sales, invoicing, etc.) for small and medium-sized businesses. Odoo is developed mainly in Python and Javascript. This project will involve working with Odoo developers on one of the following topics at the intersection of Continuous Integration and Software Testing.

Fuzz testing, or simply fuzzing, is an automated testing technique aiming at discovering bugs or vulnerabilities of software systems by providing random, invalid, or potential harmful input data. Fuzzing is a black-box testing technique, as typically, fuzzers, i.e. tools running fuzzing, have no access to the source code. Where structured testing will typically be manually written, i.e. developers will write test cases to ensure a system behaves as expected - verification - and fulfils the users’ expectations - validation -, fuzzing tools may employ techniques to generate a range of inputs with minimal manual intervention. However, many open-source or openly-accessible fuzzers have rudimentary user interfaces, so that developers must typically have a good understanding of what software security testing is, as well as understand how specific fuzzers need to be configured for specific software under tests. This project will explore how existing fuzzers could be made more approachable for non-experts. The scope of the project will be restricted to web systems (REST).

This thesis investigates the impacts and challenges of integrating CLING, a test generator for Java, into CI/CD (Continuous Integration/Continuous Deployment) pipelines. In a context where test automation is essential to ensure software quality, CLING generates integration tests automatically. Integrating this tool into a Docker environment standardizes and isolates the environments, thus ensuring consistent test execution. The work addresses the technical challenges encountered during this integration, such as configuring and automating necessary operations. It also describes the development of the API used to manage the data generated by CLING. The results show an improvement in the efficiency of the development process, particularly through the reduction of manual interventions. Finally, the thesis offers recommendations for developers and DevOps engineers looking to optimize the integration of test generators into their CI/CD pipelines.

Learning to program, and especially understanding it, is a difficult task for newcomers. For this rea- son, aids are provided, such as IDEs, which give them tools to help them avoid syntax and/or semantic errors, depending on the programming languages used. depending on the programming languages used. However, these aids are not always sufficient to understand the written code, and more often than not, they fail to to understand the errors generated and their causes. For this purpose, code comprehension tools are available to help visualize the code. Some advances have even made it possible to use this through virtual reality. That’s why, with the advent of MR, a draft code visualization application has been proposed. This solution, called codeMR, makes it possible to represent code in 3 dimensions following the city’s paradigm, codeCity. To test its viability, an experiment was carried out with 10 people to see if it could a future for understanding code through the mixed reality. The results showed that the solution had the capabilities to help code comprehension. However, improvements to the application are still required to ensure optimal use in this context.

This dissertation explores the impact of using natural language in the visualisation of open datasets, focusing on the design and evaluation of Aladdin, a system based on the DSR approach. Aladdin uses advanced natural language processing techniques to transform text queries into interactive data visualisations.

Amid growing concern over filter bubbles and content diversity, this thesis explores the impact of feedback mechanisms on user experience with YouTube’s recommendation algorithm. The study examines how increased user control can influence their interactions with the algorithm. Based on user interviews, personas were created to understand user behaviors and expectations. A Chrome extension was developed to allow users to report errors in their recommendation feed. Results indicate that this mechanism enhances user satisfaction and a sense of control, though some limitations suggest areas for future improvements. The study also proposes a methodology to evaluate contextual thematic diversity on YouTube, paving the way for further research into recommendation diversity and self-actualization systems.

The goal of the thesis is to devise an approach for automated test execution for digital performances developed using creative coding.

This master thesis investigates how the Language Server Protocol (LSP) can be used to develop a nomad and ergonomic code editor. Mobile devices popularity has significantly increased in the past decade, strengthening the transformation of desktop solutions to mobile ones. However, code editing activities, traditionally carried out on a computer, have not yet found real alternatives to provide a suitable development environment and allow multilanguage support on mobile devices. Previous works focus on finding interaction solution to allow better code editing productivity, mainly adapting the code editor to one single programming language. By integrating the use of language servers through the LSP, we develop new design and interaction solutions to allow multilanguage support in a single mobile code editor. In this thesis, we present a prototype code editor combining interaction solutions found in the literature with LSP functionalities and evaluate it in terms of productivity and usability. This work aims to provide an alternative solution to the traditional desktop development environment on mobile devices, addressing the technological shifts and transforming the way developers may be coding in the future.

Since many years, Odoo, a company providing business management services, is constantly expanding its scope and developing the complexity of its software, a web application. In response to that complexity, the introduction of automated testing techniques seems to be the next evolution of the testing tools already available to them. In the past, other tools for automatically testing web interfaces have been created, but often with limitations. This thesis explores the techniques that can be applied to implement fuzzing on the Odoo software web interface. It is shown that some methods do not seem applicable at present, while others work very well. A viable method will be proposed and implemented, and different configurations of the method will be evaluated. Ultimately, it will be shown that some weaknesses are present in the proposed method, but that future work in this direction can be done.