bunq is an internationally active digital bank. At the moment, the bunq app is only available in English, Dutch, German, Italian and Spanish. Their goal is to be a worldwide player. To be able to fulfil this goal, their app should be available in multiple languages. In the past, the translation process took an unnecessary large amount of time. Due to this inefficiency in the process, the client, bunq, gave the team an assignment to create an application which helps to decrease the workload and time spent on translating. The application should solve the following issues: (1) translating the strings is time-consuming; (2) developers lose time by having to copy and paste the strings into the code; (3) inconsistency mistakes between the apps are made when inserting the strings into the code; (4) translations might be incorrect; (5) fluent speakers are needed for each language. The final product is a web application that solves the main issues of decreasing the workload and time spent on translating.

The recommendation of tasks for newcomers within a software project throughgood first issues is being done within the domain of software development, such as onGithubplatform. These issues aim to help newcomers identify tasks that are suitablefor them and their level of expertise within the project. This thesis report investigatesthe effectiveness regarding developer onboarding and task completion ofgood firstissues by data mining a set of 105 repositories and manually analyzing at most 30good first issues and 30 initial commits per sampled project. It was found that, althoughgood first issues are effective at developer onboarding, and developers perceivegoodfirst issues as being useful, changes can be made to the types of tasks suggested asgood first issues to match the types of initial contributions made by newcomers. It wasalso found that developers with less than a year of experience favoreddocumentation-related contributions for their first commit to a project.

In the software engineering field the code review process has been widely adopted as a quality control, in the current day code reviews have also multiple additional advantages. In this research we explored how the code review process is used at Greenchoice, a Dutch energy supplier. Subsequently, we created a code review checklist which was used by the developers in order to improve the process. In the first step of the exploration we used a questionnaire to retrieve Greenchoice's motivation for the code review process. In the results we show that ensuring quality is the main motivation followed by knowledge sharing and functionality check. Secondly, we held 13 semi-structured interviews, performed a data analysis on the metadata of 8458 pull requests and performed a data analysis of 5400 code review comments to explore Greenchoice's code review process further. In the results of the interviews we show that the reviewers tend to focus on understanding the change and finding obvious mistakes. They also mentioned code reviews could be performed stricter improving the maintainability and evolvability aspects. However, it can be hard to know where to check on for these aspects. In the results of the metadata analysis we show that the code reviews are performed quick, frequent and small changes are made, similar to the modern code reviews processes described in the literature. In the results of the code review comments analysis we show that most comments are related to explaining or understanding the change. Next, we created together with a scrum team a code review checklist which was was used by three scrum teams for two periods of two weeks. In order to measure the effectiveness of the code review checklist we used a pre questionnaire to gauge the current situation and the expectations of the usage. A post questionnaire was used to gauge the new situation and whether the expectations were met. After comparing the results we show in the results that the checklist is less appropriate to guide the reviewer step by step in a code review. Furthermore, we show that the items in the checklists should be applicable to the different changes in the pull requests. The strength of the checklist lies in addressing the items which are often forgotten in the development process and the code reviews.

Recently published health reports from governments of western countries and the World Health Organization (WHO) provide insights on health benefits of being physically active. Performing physical activity of moderate intensity is, amongst others, associated with a smaller risk on symptoms of depression, cardiovascular disease and diabetes. Despite this information being widely available on the world wide web, one particular form of physical inactivity is still incorporated in the lives of many people: sedentary behaviour. An environment that is especially seductive for this type of physical inactivity is the workplace. Stress, depression, anxiety, and heart diseases are found to be work-related diseases, possibly as a result from sedentary behaviour. As a means of reflecting on physical activity, one could acquire an activity tracker such as FitBit or use one of the many available health monitoring mobile applications. However, it was found that activity trackers may not be very effective for stimulating a physically active lifestyle. In contrast, an emerging phenomenon may be able to do so: the intelligent personal assistant (IPA). In order to be a part of the solution for aforementioned problem, we aim to stimulate reflection on physical activity during work hours in order to incorporate physical activity into daily routines. Therefore, we carried out a user study with 16 participants in two countries. For carrying out this user study, we introduced Alexercise: a system consisting of multiple interacting components, used for collecting, processing and presenting physical activity data. Components in Alexercise exchange data in quasi-real time to provide workers with current representative physical activity data. As part of Alexercise, we developed a custom skill for Alexa to access physical activity data and present these by voice. In addition, we developed a cross-platform mobile application for tracking and reflecting on activity using the React Native framework. We investigated whether IPAs are more effective in stimulating reflection on physical activity, compared to activity trackers. In addition, we asked participants if they felt the need to take active breaks based on the experience of the user study. At last, we intended to compare results of participants who already incorporated physical activity in their lifestyles with participants who have not. In the development process, we encountered many challenges, such as the distribution of mobile applications and Echo Dots to participants in two countries, and facilitating real time tracking and reflecting on physical activity. Collected sensor data for Android smartphones was reported with infrequent intervals, and could therefore not be used to reliably assess physical activity. We investigated and elaborately explained how these challenges can be overcome for future work. In contrast to the challenges, participants reported that they perceived talking to Alexa as intuitive, and the majority of the participants reported that they feel the need to take active breaks based on their participation in the user study.

Test-cube is a tool that focuses on developer-friendly test amplification. Test amplification is a technique to improve a test suite by generating new tests based on manually written ones. Currently, these generated tests contain much redundant casting. Our study aimed to improve the readability of these generated test cases by reducing superfluous casting. To test this, we developed multiple cast deleters categorized into two types: simple and fine-grained cast deleters. A simple cast deleter removes casts based on limited knowledge but can make errors. A fine-grained cast deleter only removes casts if it knows they are redundant based on much contextual information. We compared these two types in terms of accuracy by gathering statistical data when running them against real-world examples of amplified test cases. We also discussed the types of casting cases for which they performed well or could be improved based on manual code inspections. In this study, when amplifying all the tests of four public repositories, we found 3,085 casts in 281 tests containing casts. Of these, 97.18% were redundant, and our fine-grained deleter detected and deleted 98.87% of these. We found this fine-grained deleter to be the worthwhile option compared to a simple cast deleter. This was not because the simple cast deleter was slightly less accurate at 97.18% rather than 98.80% but because it showed extremely inconsistent accuracy. The second benefit of the fine-grained deleter was that it caused no tests to fail, while the simple cast deleter caused 18.15% of tests to fail. This paper provides excellent insights and techniques to reduce vast amounts of redundant casting in test amplification. We hope it will make test amplification more developer-friendly and increase its overall practicality.

In this study, we try to understand what kind of topics and frameworks are covered by the popular software testing books, and see whether these topics satisfy the industry needs and address the rising trends. To define "popular" software testing books, we formulated three heuristics. The topics of the books are analyzed through LDA topic modelling and manual inspection. LDA results inform us on the dominance of the topics within the whole corpus, while the manual inspection results show how often a topic is addressed. We combine the results of both of the methods to analyse the most noteworthy topics. We found that test automation, test design and planning, coverage analysis were the most frequently and extensively discussed topics in our corpus. We conclude that although the books cover some major topics that are demanded by the industry, there are also areas such as test management and usability testing, which are underrepresented. We also observed that the popular software testing books do not cover the rising software testing trends. While JUnit was the most discussed framework, in general the software testing books do not include practical information for specific frameworks or tools, but rather focus on the tool selection process.

Quantum networks provide numerous potential benefits over classical networks, such as enhanced security and faster computation, making their further development a lucrative prospect. As is the case with any technology, the advancement of quantum networks relies on the development of frameworks to test their quality, and compare different implementations of the technology. One such framework is a benchmarking suite for quantum network systems, that can identify areas for improvement in their implementation, by determining the erroneous properties of the system. This paper examines the viability of using a specific quantum network application as a benchmark for quantum network systems. In order to quantify the application's ability to benchmark, we assess its sensitivity to changes in the properties of the system. These properties include link parameters, quantum gate properties, qubit coherence times, and measurement properties. We use the BB84 protocol as the benchmarking application for this project, which is a Quantum Key Distribution scheme used to establish secure keys between two parties. In particular, we use the qubit error rate and the key generation rate as the performance metrics for the application. For the setup of the experiments, we prepare two system configurations: generic quantum device nodes with a depolarising error channel, and NV device nodes with a heralded link. In order to assess how the application behaves with changes to different system properties, we observe how the performance metrics change while individually varying system parameters and keeping all other parameters constant. We find that the application is sensitive to changes in multiple parameters across both network configurations, such as link parameters, single qubit gate properties, and measurement properties. Contrarily, the application is not affected by changes to parameters such as two qubit gate properties and coherence times. We conclude that the BB84 protocol can be used as an individual localised test for the parameters it is sensitive to, and also in combination with other applications, in a more comprehensive benchmarking suite, that provide coverage for a broader range of parameters.

This research introduces a Language Model Augmented Program Synthesis (LMAPS) workflow to enhance traditional Programming by Example (PBE). PBE is a method to automatically generate a program that satisfies a specification that consists of a set of input-output examples. These program specifications are often defined by a few examples, which can lead to multiple programs that satisfy the given examples. In addition, PBE synthesisers have to explore a huge inefficient search space to solve these problems. The LMAPS workflow incorporates three components to overcome these limitations of PBE by using the language understanding capabilities of Large Language Models (LLM). LLMs can assist in generating a well-defined specification to mitigate the ambiguity issue inherent in PBE. The core component of LMAPS leverages the capabilities of LLMs to generate programs. These programs can be decomposed into building blocks to create a concise grammar for an inductive program synthesiser. This optimized grammar makes it able to synthesise correct programs at lower depths, make the workflow more efficient. LLMs can also aid in understanding the automatically generated programs, as these programs can be hard to interpret by humans. We compare LMAPS to a traditional PBE workflow in the task of synthesising regular expressions across four data sets. The results demonstrated that LMAPS can significantly reduce the search space for program synthesis and achieve up to 40% higher accuracy than PBE-only systems. Our research indicates that integrating LLMs into a typical PBE workflow shows significant improvements because of their combined strengths, resulting in a more accurate, efficient, and human-aligned workflow.

Software development is more than only implementing the functional code. A developer is also responsible for writing code measuring up to certain standards and conventions. These conventions make sure that the code is of a particular quality that improves readability and eases maintainability. Some of these conventions are checked by automated tools. Automated static analysis tools (ASATs) perform an analysis of the source code and issue warnings. ASATs are available for many programming languages and can be used to find functional or maintainability issues. Even though these tools have been proven to be useful during the code development process, developers do not always utilize them. The overload of warnings in large projects and relatively low importance of these warnings are one of the many reasons why they are ignored. In this study, a gamification tool, Checkpoint, is developed based on the GOAL methodology. The purpose of this tool is to gamify the development process pertaining to ASATs to motivate developers. The developers are motivated using various gamification elements during a pretest-posttest pre-experimental experiment. The study tested the usability of the tool and its effectiveness. The experiment showed that gamification has an impact on developer motivation.

Digital printing systems allow for the production of a large variety of different products. Making production plans for all these different products is challenging. One of the challenging aspects of making these production plans is choosing the right sequence of machines, to produce the desired intent. This is challenging due to three aspects: the large number of interdependent variables in the problem instances, the variability of machines, and the search for the best solution from a large set of valid solutions. In this thesis, we implement and evaluate the use of a domain-specific language (DSL) called RSX (Routing Space eXploration), to assist in choosing a sequence of machines. We do this together with an industrial partner. For RSX we use a model-driven approach, and it can be used to model the devices, production steps, and product properties of the digital printing domain. It transforms those into a constraint model described in the MiniZinc language, which is used as input for a constraint solver. We present the implementation of the RSX language and MiniZinc constraint model, and we evaluate the language coverage, accuracy, and performance. From these evaluations, we conclude that RSX can be used to model a number of cases, which were characteristic in the context of our industrial partner. Furthermore, we conclude that RSX can compile and solve the evaluated cases in the order of a few seconds and that the implementation is accurate, such that it can be used as a proof of concept.

In the development of any new technology, it is essential to have methods to assess the quality of a system, to compare different systems to one another, and to compare different versions of the same system, to see if changes to the system can actually be classified as improvements. For quantum networks, this is no different. To further develop quantum networks, we need a benchmarking suite to judge the quality of such systems. The aim of this research is to determine the effectiveness of blind quantum computation - a quantum network algorithm - as a benchmark. We determine what changes to the system affect the results of executing this application, and we use this to determine whether it would be effective to use this application as part of a larger benchmarking suite. We do this by simulating a quantum network, and manually varying system parameters one by one, to see if they have an effect on the results. What we observed from these experiments is that blind quantum computation is sensitive to almost all system parameters. This means that introducing an imperfection into almost any system parameter will negatively affect the results of the application. This means the application is useful as a full-system benchmark, because it is affected by almost the entire system. However, it also means that the application is less useful as a benchmark for individual parameters. This means that to make the most useful benchmarking suite, blind quantum computation would have to be combined with other quantum network applications that are more suitable for benchmarking individual system parameters.

The rapid advancement of Quantum Network architectures necessitates a comprehensive and quantitative comparison to assess their effectiveness and performance. Unfortunately, there does not exist an implemented quantum network benchmark suite capable of determining the superior architecture. Hence, our study aims to establish the foundation for developing a benchmark suite by leveraging existing quantum network applications. However, the specific inclusion of quantum network applications in the suite remains to be determined. Therefore, to address this gap, our study will explore the potential inclusion of the Clauser-Horne-Shimony-Holt (CHSH) game based on its effectiveness in identifying errors within various properties of the quantum networking system. We use an exploratory research methodology involving experiments performed on simulated quantum networks utilizing SquidASM. Each experiment simulates multiple quantum networks, with a single property as the independent variable. For each value of the independent variable, we calculate both the success probability of the game and the number of successes per second. Subsequently, we employ the one-way ANOVA test to examine if there are significant variations in these performance metrics. Our results demonstrate that the CHSH game exhibits sensitivity to all properties affecting the quality of entanglement between nodes, execution time, and the error probability of both single-qubit gates and measure operations. Additionally, we compare the success probabilities based on different input combinations using the Root Mean Squared metric to uncover any underlying patterns within the data. As a result, we discovered a procedure for quantifying the difference between the error probabilities of measurements of zero and one. Based on the outcomes of our study, we consider the CHSH game to be a suitable addition to the benchmark suite if the testing requirements of the suite align with the qualities offered by the application. We anticipate that these results will aid the development of the benchmark suite and advance the understanding of quantum network architectures and their evaluation

Comparing spreadsheet files is a new, unexplored research domain in computer science. Methods for regular file comparison are not straightforwardly applicable to spreadsheet files, because they are fundamentally different. Spreadsheets are binary files, the structure of spreadsheets is two-dimensional, they contain both data and calculations, and the content exists on different abstraction levels. Fundamental challenges in the spreadsheet comparison problem include: change propagation, performance, 2D alignment, the grouping of data, and movement detection. One simple modification can change the whole structure and model of the spreadsheet. The aim of a good file comparison method is to show the actual changes made by an end-user, not the propagated changes. In this thesis, a new pipeline-based approach for comparing two spreadsheet files is proposed. The spreadsheet comparison is solved in three phases: (1) structure analysis, (2) change detection, and (3) change aggregation. The essential element in this approach is passing on information from the structure analysis to the change detection. In addition, the detected changes are forwarded to the aggregation such that changes are converted into clear, understandable differences. The final comparison result, therefore, provides information at different levels of abstraction. New solutions like cell hashing, an optimized 2D alignment using longest common subsequences, and different algorithms for comparing worksheets, defined names, rows, columns and cells have resulted in a state-of-the-art spreadsheet comparison approach. In addition, this thesis presents a prototype demonstrating the proposed concepts in practice. This tool, called CompareXL, is a stand-alone application that can compare two spreadsheet files. The user interface is built with a multi-level interaction design, showing the comparison results intuitively to the end-user. Spreadsheets are commonly used and many problems arise from spreadsheet versioning issues. Spreadsheet users have user needs related to overview, validation, completeness, error resolving, visualization, and evolution. A spreadsheet comparison program is helpful to address these user needs. This research shows that it is beneficial to involve users in the exploration of solutions, because comparing spreadsheets is not only a technical problem but also a user problem. The outcome of this research offers multiple directions for future work, with the ultimate goal that all spreadsheet version problems will soon belong to the past.