Can The Language Server Protocol Handle Dependent Types?

The Language Server Protocol (LSP) is a protocol that standardizes the way Integrated Development Environments (IDEs) and text editors communicate with language servers to provide language-specific features like autocompletion, go-to-definition, and diagnostics. While LSP has been widely adopted by mainstream programming languages, its adoption...

PyHintSearch: Validated Combinatorial Search for Probabilistic Type Inference Models

Type annotations in Python are an integral part of static analysis. They can be used for code documentation, error detection and the development of cleaner architectures. By enhancing code quality, they contribute to the robustness, maintainability and comprehensibility of codebases. Tools like static type checkers use type annotations to detect...

Exploiting modularity during program synthesis

Inductive logic programming is a technique that generates logic programs which keep to a given specification using a background knowledge. We propose a new task in the field of pro- gram synthesis called Time-gated Partition-selection Inductive Logic Programming, consisting of splitting the background knowledge into partitions and selecting only...

Uncovering the Secrets of the Maven Repository: Analysis of Library Sizes in Maven Central

This research explores the size variations of artifacts in Maven Central, a repository containing a large collection of Java artifacts. This analysis sheds light on the coding habits and dependency management ecosystems within Maven Central, emphasizing the importance of managing artifact sizes effectively. It also provides valuable insights to...

Cryptpath: Data-oblivious Shortest Path Discovery in Outsourced Settings

Cloud computing and storage solutions have been credited with increasing competitiveness through cost savings, greater flexibility, elasticity and optimal resource allocation. However, the data outsourced to the cloud may contain private information that must be protected from misuse. In such cases, the data can only be outsourced after...

Github Mining: Discover the Descriptive Metrics of the Context in Continuous Integration (CI) Project

Continuous Integration (CI) systems automate the building, testing, and possibly more. However, it is still unclear how CI should be implemented in different contexts. Therefore, this paper tries to answer the question "What metrics can be used to describe project activity", as part of a bigger study. We mined information from 500 repositories...

Discovering the topics of Continuous Integration Projects on GitHub

Continuous Integration (CI) is a software development technique that enhances software quality and development efficiency, but its implementation usually depends on the project's context. This creates an opportunity for studying real-world CI projects on GitHub, focusing on their CI metrics and best practices. In this paper, we explore various...

Enriching Machine Learning Model Metadata: Collecting performance metadata through automatic evaluation

As the sharing of machine learning (ML) models has increased in popularity, more so-called model zoos are created. These repositories facilitate the sharing of models and their metadata, and other people to find and re-use an existing model. However, the metadata provided for models is insufficient, with little focus on practical aspects of a...

Vulnerability Risk Modelling in Open Source Software Systems

Recent large scale cyber security incidents such as the Equifax data breach, where the personal information of around 160 million Americans leaked, demonstrate the current risk of security vulnerabilities libraries which software projects depend on.<br/>The usage of libraries forms an integral part of modern software development and is a...

Reducing Human Error in Online Controlled Experiments: A case study at ING

Online controlled experimentation (OCE), also called A/B testing, is an often used tool in industry to determine if deploying changes into production is the right decision to make. Running experiments has shown an immense impact to the revenue of companies in industry, however this type of experimentation comes with a lot of pitfalls, of which...