Replication and formalization of (Co)Church encoded shortcut fusion: Master's Thesis

When writing functional code that composes multiple recursive functions that operate on a datastrcuture, we often incur a lot of computational overhead allocating memory, only to later read, use, and discard this information.<br/>This can be alleviated using fusion, a technique that combines these multiple recursive datastructure traversals into...

Dealing with conflicting trains: Effectively avoiding and resolving conflicts during shunting

A shunting yard is used to store trains between arrival and departure. A conflict arises in a shunting yard when one train obstructs another from leaving. Resolving a conflict is done by re-allocating the trains obstructing the departing train to other tracks in the shunting yard. However, these re-allocations complicate the problem at hand and...

Mixed-direction train shunting with numerical planning: Approach to support train departures at any time during the shunting plan

In this paper, we discuss our novel approach to support mixed-direction shunting in the planning domain for tree-like shunting yards. We explain how we used numeric fluents to improve an existing PDDL domain to support such actions. We elaborate on the underlying conceptual model of our domain and argue how does it accurately represent<br/...

Comparing planners for rail planning in PDDL: How multiple shunting yard layouts can be created in PDDL to replicate real-world scenarios

This paper explored the usage of the Planning Domain Definition Language in the Train Unit Shunting Problem or TUSP, an NP-hard problem that occurs in train storage. This paper focuses on the evaluation and improvement of existing planners to solve TUSP with multiple shunting yard layouts, as well as an appropriate domain with it. Starting with...

Utilizing General Planners to Solve the Train Unit Shunting Problem Extended with Servicing

When not in use, trains are stored at shunting yards, where they may need servicing. Planning for where the rolling stock should be parked during its stay at the yard is known as the Train Unit Shunting Problem (TUSP) and it is NP-hard. Algorithmic planners can assist with this computationally difficult task by providing a sequence of actions to...

Optimizing the PDDL domain of TUSP to improve planner performance: Modifying the domain to improve planner execution time, plan quality, and problem solvability

It is possible to improve the performance of planners by modifying the PDDL domain of a problem. The goal of this research is to implement this to the domain of the Train Unit Shunting Problem (TUSP). The research question we attempt to answer is: To what extent can we improve planner performance by optimizing the PDDL domain of TUSP? The main...

Exploring Code Coverage in Open-Source Development

Software development has increasingly become an activity that is (partially) done online on open-source platforms such as GitHub, and with it, so have the tools developers typically use. One such category of tools is that of code coverage tools. These tools track and report coverage data generated during CI tests. As the adoption of these tools...

EDATA: Energy Debugging And Testing for Android

This thesis was written in during my internship at Adyen as the final project of the Master’s program in Computer Science at the TU Delft. In my Bachelor’s thesis, I compared the energy consumption of three Android UI frameworks, and I chose to continue working on the subject of energy consumption on Android as it is relevant both to Adyen and...

Reference-free biomarker mining in metagenomic data using language embedding

Metagenomic Next-Generation Sequencing (mNGS) presents a promising avenue to generate massive volume of sequence reads in a short period of time. This has opened opportunities for disease diagnosis based on individual variations and mutations by considering the microbiome profile of each patient. However, the effective use of this data requires...

Optimizing machine learning inference queries for multiple objectives

Machine learning inference queries are a type of database query for databases where a model pipeline is needed to evaluate its boolean predicates. Using a model zoo it is possible to select a variety of models to execute in a sequence rather than using a highly specialized model to answer every query predicate. Machine learning models can have...

Permutation-Invariant Tabular Data Synthesis

Tabular data synthesis is a promising approach to circumvent strict regulations on data privacy. Although the state-of-the-art tabular data synthesizers, e.g., table-GAN, CTGAN, TVAE, and CTAB-GAN, are effective at generating synthetic tabular data, they are sensitive to column permutations of input data. In this work, we conduct an impact and...

The Category of Sets in Homotopy Type Theory

This paper is a literature survey on homotopy type theory, analyzing the formalization of sets within homotopy type theory. Set theory is embedded in homotopy type theory via h-sets, with all h-sets forming the type <b>Set</b>. This paper presents the properties of the type <b>Set </b>from a categorical perspective, comparing it with its set...

Evaluating Scopes of Different Implementations of Finite Sets in Homotopy Type Theory

This report explores the differences in implementations of homotopy type theory using different definitions of finite sets. The expressive ability of homotopy theory is explored when using the newly established definition and implementation of Kuratowski finite sets. This implementation is then compared to that when using the previously...

The Proof of the Fundamental Group of the Circle in Homotopy Type Theory’s Dependence on the Univalence Axiom

The incorporation of the univalence axiom into homotopy type theory has facilitated a new way of proving a basic result in algebraic topology: that the fundamental group of the circle is the integers (π1(S1) ≃ Z). This proof is formalised by Licata and Shulman. However, while the authors note that the univalence axiom is essential, it is not...