Johannes Haertel

Vrije Universiteit Brussel | VUB

In Silico” research drives the world around us, as illustrated by the way our society handles climate change, controls the COVID-19 pandemic and governs economic growth. Unfortunately, the code embedded in the underlying data processing is mostly written by scientists lacking formal training in software engineering. The resulting code is vulnerable...

Empirical Software Engineering studies apply methods, like linear regression, statistic tests, or correlation analysis, to better understand software engineering scenarios. Assuring the validity of such methods and corresponding results is challenging but critical. This is also reflected by quality criteria on the validity that are part of the revi...

Collaborative software development depends on managing multiple versions of a program which requires mechanisms to merge program versions to eventually deploy a single executable. Merging program versions can be challenging as conflicts can arise. The most challenging form is a semantic conflict, which introduces unintended behaviour in the resulti...

Deep learning (DL) techniques can transform modern software engineering (SE) processes to make data-driven, self-learning, and intelligent software systems. Graph representation learning (GRL) techniques help to create graph-based representations of data (code) for automated feature extraction. This study aims to conduct a systematic literature rev...

Conventional wisdom on Model-Driven Engineering (MDE) suggests that this software discipline is the key to achieve superior automation, whether it be refactoring, simulation, or code generation. However, the diversity of employed languages and technologies blurs the picture making it difficult to analyze existing MDE-based projects in order to retr...

Graph data models are interesting in various domains, in part because of the intuitiveness and flexibility they offer compared to relational models. Specialized query languages, such as Cypher for property graphs or SPARQL for RDF, facilitate their use. In this paper, we present an empirical study on the usage of graph-based query languages in open...

APIs can be classified according to the programming domains (e.g., GUIs, databases, collections, or security) that they address. Such classification is vital in searching repositories (e.g., the Maven Central Repository for Java) and for understanding the technology stack used in software projects. We apply hierarchical clustering to a curated suit...

Selecting and properly using approaches for DSL implementation can be challenging, given their variety and complexity. To support developers, we present the software chrestomathy MetaLib, a well-organized and well-documented collection of DSL implementations useful for learning. We focus on basic metaprogramming techniques for implementing DSL synt...

The context of the reported research is the documentation of software technologies such as object/relational mappers, web-application frameworks, or code generators. We assume that documentation should model a macroscopic view on usage scenarios of technologies in terms of involved artifacts, leveraged software languages, data flows, conformance re...

We present a new feedback strategy implemented in a natural language generation-based e-learning system for German as a second language (L2). Although the system recognizes a large proportion of the grammar errors in learner-produced written sentences, its automatically generated feedback only addresses errors against rules that are relevant at the...

We describe a method and a corresponding tool for grammar-based test-data generation (GBTG). The basic generation principle is to enumerate test data based on grammatical choices. However, generation is broken down into two phases to deal with context-sensitive properties in an efficient and convenient manner. The first phase enumerates test data (...