We investigate the use of relaxed decision diagrams for obtaining lower bounds on multi-machine scheduling problems. The type of scheduling problem we consider models a railway service site where maintenance jobs are performed, but is sufficiently general to potentially have wider applicability.
We find that our decision diagram formulation is able to give decent lower bounds in short time. Our implementation is competitive with lower bounds given by existing solvers, and is superior when due times are small and have small variance. Further, we find that our model greatly improves upon a naive extension of the state of the art for single-machine scheduling [23].

The quality of test suites is commonly measured using adequacy metrics that focus on error detection, like test coverage. However, the diagnostic performance of spectrum-based fault localization techniques, that can potentially reduce the time spent on debugging, rely on diagnosability of test suites --- the property of faults to be easily and precisely located. Therefore, in prior work, Perez et al. proposed a new metric, called DDU, that measures the diagnosability of test suites. However, DDU is not yet usable in practice due to its output value between 0 and 1. A developer would not know what test to write next given a certain DDU value. In this study, we explore the performance of DDU in practice by analyzing open source projects. We find no evidence that DDU is correlated to diagnosability and, thus, DDU is currently only useful when combined with test generation techniques.

In a busy railway network such as the Netherlands, more and more maintenance activities are needed to be performed. These planned activities often lead to an infeasible timetable since infrastructure is temporary unavailable for operations. A macroscopic network model can roughly adjust the timetable for a complete network, while a microscopic model is needed to check for possessions in station areas and ensure feasibility of the timetable. In this thesis a microscopic routing model is proposed that adjusts the route plan in a station area while minimising passenger dissatisfaction. The model also finds new rolling stock connections, implements shunting movements in a station area and considers shorter rolling stock formations. To increase the quality of the route plan, its robustness is increased iteratively and small time shifts of arrivals and departures are applied to resolve small conflicts that would lead to cancellations. Several case studies demonstrate the high performance of the model. Finally, a feedback mechanism to a macroscopic model is proposed.

Software testing has been around for decades and many tools exist to aid developers in their testing process. However, little is known about the rate at which developers test their projects, the tools they use for these purposes and the impact of type systems on testing practices. Our work is the first of its kind to identify and classify available test tooling for programming languages Java, C, JavaScript and Ruby. By conducting a large scale automated analysis on open-source software projects, we show that both available test tooling and type systems have significant impact on codified testing strategies. Our observations are strengthened by targeted interviews and a large-scale survey among developers working with both statically and dynamically typed programming languages. The soft typing system seems like a promising solution, allowing developers to work with the great flexibility less strict type systems provide, while simultaneously benefiting from strict type checks that help reduce the amount of testing required to ensure the correctness of a piece of software. However, future research is needed to estimate the feasibility of such a type system. To help better aid developers in their testing process and to reduce some of the testing burden many developers seem to cope with, we propose a list of test tooling improvements based on our observations.