L. Miranda da Cruz
68 records found
1
Authored
MLSmellHound
A Context-Aware Code Analysis Tool
Meeting the rise of industry demand to incorporate machine learning (ML) components into software systems requires interdisciplinary teams contributing to a shared code base. To maintain consistency, reduce defects and ensure maintainability, developers use code analysis tools ...
The adoption of Artificial Intelligence (AI) in high-stakes domains such as healthcare, wildlife preservation, autonomous driving and criminal justice system calls for a data-centric approach to AI. Data scientists spend the majority of their time studying and wrangling the da ...
Removing dependencies from large software projects
Are you really sure?
Machine Learning (ML) projects incur novel challenges in their development and productionisation over traditional software applications, though established principles and best practices in ensuring the project's software quality still apply. While using static analysis to catc ...
The popularity of machine learning has wildly expanded in recent years. Machine learning techniques have been heatedly studied in academia and applied in the industry to create business value. However, there is a lack of guidelines for code quality in machine learning applicat ...
Are Concept Drift Detectors Reliable Alarming Systems?
A Comparative Study
Security is a requirement of utmost importance to produce high-quality software. However, there is still a considerable amount of vulnerabilities being discovered and fixed almost weekly. We hypothesize that developers affect the maintainability of their codebases when patchin ...
High energy consumption is a challenging issue that an ever increasing number of mobile applications face today. However, energy consumption is being tested in an ad hoc way, despite being an important non-functional requirement of an application. Such limitation becomes parti ...
AI lifecycle models need to be revised
An exploratory study in Fintech
This chapter discusses how to build production-ready machine learning systems. There are several challenges involved in accomplishing this, each with its specific solutions regarding practices and tool support. The chapter presents those solutions and introduces MLOps (machine ...
Travis CI handles automatically thousands of builds every day to, amongst other things, provide valuable feedback to thousands of open-source developers. In this paper, we investigate Travis CI to firstly understand who is using it, and when they start to use it. Secondly, we ...