Projects in a software engineering (SE) curriculum have many advantages for students. For example, students gain teamwork and project management skills. Involving an external stakeholder can enhance the learning experience further. For instance, students have the opportunity to practice stakeholder management. Moreover, working on a project with a real external stakeholder can help them make informed career choices. This external stakeholder can be a company, a government institution, or an organization from civil society, called ‘client’ from here onwards. In this work, we focus on startups to investigate the collaboration between startups and students in SE projects. Furthermore, we developed and introduced a design thinking workshop.
We did the research in a project course at Delft University of Technology. It is the capstone course near the end of the major in Computer Science & Engineering. In this course, students take on a project for a ‘client’. This external stakeholder brings in the project’s objective. Every student group has a unique project from different clients.
We started by analysing these projects from the client’s perspective. We interviewed several star- tups that previously participated in the course. Additionally, we sent a survey to all clients from the previous two years. We incorporated the findings of the interviews and survey with literature. From this, we concluded that startups potentially suffer from a lack of design upfront. This can lead to the creation of an undesirable product. To address this, we developed and introduced a design thinking workshop to our course. Design Thinking is a method for problem analysis and problem-solving. We evaluated the workshop by interviewing teaching assistants who supervised student groups that had participated in the workshop. Additionally, we surveyed the students who participated in the workshop and teaching assistants who joined a test run of the workshop.
From the results of the interviews with startups and survey of previous clients, we synthesized di- mensions of success for projects with students. We found three dimensions in which startups measure the success of a project. The output of a project can be important to them in terms of the 1) product that is developed or what was 2) learned during the project. Additionally, whether students are successfully 3) recruited after the project can also be a consideration when assessing success. Furthermore, we synthesized dimensions of product success and preconditions to success in these projects. We found five dimensions of product success and five preconditions to success.
The design thinking workshop was given to students in the first week they started their project. It constituted half a day during which the students learned to apply the Design Sprint method, a method for operationalizing design thinking in a structured way.
After the projects ended, we evaluated the impact of the workshop. The students and their teaching assistants were both generally positive about it. The teaching assistants, who also supervised non- workshop groups, noticed an improved early process. Furthermore, they noticed that some of their non-workshop groups fell into traps that could have possibly been prevented if the group had joined the workshop and applied the tools. This leads us to believe that the workshop should be extended to all students in the course.
Implication for startups   Spend time thoroughly understanding the problem before engineering a costly and time-consuming prototype. A design sprint is a low-cost way to discover if the problem is sufficiently understood.
Implications for companies involved in SE project courses   If properly motivated, students can create a useful product or prototype, the project does not have to be just a recruitment exercise.
Implications for teachers (of SE project courses with external stakeholders)   Add a design sprint workshop for all students at the start of the course. This thesis shows that adding such a workshop is feasible and improves students’ early process.
Implications for students  Do a design sprint before formulating requirements; this will deepen the understanding of the problem to solve and improve the process, so that it yields a product that is more aligned with the user’s needs.
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P3D is an injection moulding company that uses a technology called PRIM® (Printed Injection Mould) to create products for its customers. Different from traditional moulding companies, P3D’s main business model resolves around an efficient workflow and fast delivery of products to its customers. At the moment P3D is able to quickly fabricate and deliver its products be-cause of a small team of skilled designers and engineers who have lots of expertise in the field of injection moulding. Unfortunately, relying on the expertise of its employees, a lot of data about the company’s workflow is memorised or written down. This poses a problem as P3D would like to grow in the future and will not be able to entirely rely on memorised or analogue data.The goal of this project is to create a data management system (DMS) that digitises information about P3D its workflow and saves it in an easily accessible centralised system.

The internet consists of many networks connected by the BGP protocol and can easily be manipulated by a hacker. Every day, hackers reroute internet traffic and use that to impersonate entities such as companies, devices and humans. To detect this rerouting, which is also know as a route leak, a BGP monitor can be used. A BGP monitor checks whether the local route is correct by comparing the local route to the route from hundreds of devices. The lower the percentage of the routes that are the same, the bigger the chance there is a route leak. Hence, a user can tell whether a hacker manipulated the route. This project aims to build a BGP monitor application, that will ease the process of finding whether a hacker rerouted a part of the internet. To achieve this, the Internet Monitor application has been developed. In the Internet Monitor, an admin can add different types of tasks that will be run by the devices. This input will then be transmitted to the backend and to the database, where they will be stored. After some time, the backend will send out the tasks to the nodes. The nodes will execute the task and send back the results to the backend. These results can then be used to check whether the information from BGP servers or the local result is the same, and thus not manipulated. Apart from this, Internet Monitor also offers the possibility to see the map of all the real-time traffic between devices.

The core challenge of the BedBasedEcho BEP project is to create an algorithm to find the heart, and apply it on a robotic echocardiography solution. The team has found multiple complex solutions that are related to this problem, and has extracted useful information from these solutions to apply to this problem. However, some of these complex solutions were too complex, causing the team to run out of physical resources, or to have the solution fail entirely. By taking a step back, and simplifying the solution, the team has managed to create a system that performs marginally better than the complex solutions. The designed product consists of three major components: the data gathering, the learning, and the deployment. When used in this order, the result is an algorithm that can predict which way it should move to gain the optimal view of the heart. The algorithm will be used as a component in a larger automated echocardiography system. Ultimately, the algorithm showed promise by autonomously finding a good view of the heart.

ScenWise is an innovative company that specializes in data science revolving around traffic management. ScenWise strives to use the newest and best technologies and practices when it comes to web applications, data science and traffic management. The reason for this is that they provide tools to analyse and visualise a variety of situations that occur in traffic management. One such tool is SmartRoads 1.0, which allows users to analyse traffic data and situations via a web application. Unfortunately SmartRoads 1.0 does not perform as desired. Additionally, ScenWise itself has the problem of not being able to integrate previously made products by student groups into their own existing products. During the research aimed to resolve these problems another issue arose; the software development life cycle of ScenWise is very lacking. Research on the SmartRoads 1.0 performance problem showed that the bottleneck of its performance is due to the front-end. The outdated SmartRoads 1.0 front-end was thus replaced with a new and better SmartRoads 2.0 front-end. The integration problem and development life cycle problem are both addressed in the Longterm evolution (LTE) design found in appendix I. This LTE design contains the architecture migration plan. This plan will transform the current software architecture to a Service-oriented architecture (SOA) providing a solution for the current integration problems. A result of the first steps of this architecture migration plan is the Application Programming Interface (API) Gateway, which has been implemented in the aforementioned SmartRoads 2.0. Next to the migration plan, guidelines for ScenWise to improve their software development life cycle are elaborated in the LTE design. In this report the identified problems, their solutions and executions are explained, discussed and evaluated.

Items being misplaced in warehouses easily get lost. To combat this, warehouses have to send people in scanning all barcodes in the warehouse. This is highly inefficient, which is why Eonics wants to build a drone handling this. There are options out there to scan barcodes, but none of them match the requirements laid out by Eonics. Among these requirements are a lightweight camera, such as a GoPro, and a recording distance of 1.5-2 metres. This report will look and see if these requirements are feasible. Techniques used in this report are Mathematical Morphology, Maximally Stable Extremal Regions, Convolutional Neural Networks, Gradiental Difference and Direction Estimation with Region Extraction. The report concludes in stating that interpreting the barcodes is not possible with mere software under these requirements. The maximal distance we were able to interpret barcodes from, based on a 4K image, was around 1 metre. Continuing the trend, we would need at least an 8K camera to detect from a distance of 1.5 metres. Detection however, is less difficult and is feasible from a distance of 1.5-2 metres. The report also derives an function to use to calculate the maximum distance a barcode can be interpreted from, based on the details of the barcode and camera. Finally, research is done regarding using hardware solutions, such as a zoom-lens, which has promising results.

Switching energy suppliers can be a time consuming process and the manner in which permissions regarding consumer data are stored lacks transparency. To overcome these issues, a solution was proposed in the form of a mandate register. Said register keeps track of which consumer gave what permission, regarding energy data, to whom. In this project a prototype of such a register was built. The register is required to be designed in such a way that it is expandable and secure. From these characteristics, the conclusion was drawn that a permissioned blockchain network was the most suitable option for storing mandates in a decentralised and immutable fashion. The most fitting consensus algorithm for the blockchain network was determined to be the Raft algorithm. For implementation of the blockchain network, a widely-documented and advanced framework called Hyperledger Fabric was used, which was be configured to use Raft. A network in Hyperledger Fabric is a set of organisations of which subsets can form channels together. Each organisation consists of multiple peer nodes, each with a corresponding ledger, database and smart contracts. The mandate register network consists of two channels, the first containing seven organisations, with two peer nodes per organisation. Apart from these seven organisations, the network contains seven orderers, which work in the second channel and which are responsible for managing transactions made by an application. On top of the network, an application was built that connects to the network and functions as a simple web server. The web server allows consumers to submit their mandates as input to the network and query mandates from the network. Performance evaluation of the network shows that it requires much optimisation before being ready for deployment in the real world. Apart from optimisation, there are various tasks related to security, authentication, deployment, and the GDPR which have to be completed before the register can be used in production.

Scenwise has developed the ScenarioDesigner to support road authorities in creating response plans. The response plans describe which actions the operator should take in order to manage different traffic situations such as accidents, large scale events This thesis elaborates on the process as well as the end-product created during the Bachelor End Project The BEP is a 10 week compulsory project to complete the Computer Science and Engineering program of the Delft University of Technology. It was conducted between 11 November 2019 and 11 February 2020. During the first two weeks the group focused on researching the problem, the possible solutions and traffic management in general. The subsequent 8 weeks were designated to the development of the product. The product was developed for ScenWise, a company that focuses on innovation within traffic management. In addition to evaluating the product, this thesis gives recommendations for a following group working on extending the product.
Finally, the group would like to thank the client ScenWise, specifically K.F. Chan for providing the project as well as teaching us about the domain knowledge of the client. Furthermore, the group wants to thank Dr. A. Katsifodimos for the coaching throughout the project as well as Ir. O.W. Visser for giving the opportunity to do the BEP in the second quarter of the academic year.

Raccoon Serious Games develops different kinds of gaming experiences, including escape rooms. In an escape room, a group of players, usually between 2 and 20 people, are locked in a room, where they have to find clues and solve puzzles to escape. When such a room is played, there is always an operator, monitoring the progress of the players and keeping an eye on their safety. Modern escape rooms are quite technologically advanced, where all components of the room interact with each other. To run these games, Raccoon Serious Games needs a system which should manage all technical aspects within the room and provide a way for the operator to keep track of the players. Furthermore, the system must be flexible enough to handle many different escape rooms, which are hardcoded in configuration files. To meet these needs of Raccoon Serious Games, a team of three developers has developed a new system, called S.C.I.L.E.R.. In ten weeks, they have created a system from scratch. First, they researched technologies and requirements that would be necessary for the system and afterwards implemented the system based on their findings. S.C.I.L.E.R. allows an operator to monitor a complete escape room. The system connects a user interface to all the devices in the room, which are controlled by the user as well as the configuration of the escape room. This configuration is generated from a JSON configuration file, containing all information for the escape room. The system allows the operator to send hints to the players, control the time and manage their progress through the status of devices in the room and the puzzles they have to solve. It also contains the feeds of cameras in the room to actually see the players. Furthermore, it provides the user with a way to check a configuration file and put it to use. The system will be used by Raccoon Serious Games in the near future for the escape rooms that they will be hosting.

Nowadays, entering into a contract with an overseas company still relies on postal services to send a printed contract, which is signed on paper. Lizard Global is developing an online platform for constructing, reviewing and signing digital contracts for one of their clients. In the original system, when a signee signed a contract, his personal information was used as a signature and stored in blockchain. However, this way of signing a contract does not enjoy the same degree of legal validity as a written signature. Moreover, the implications on privacy legislation, specifically the European Data Protection Regulation (GDPR) had not yet been taken into account by Lizard Global. This project describes how agile development was used to construct a high quality software solution to the problem, thereby implementing firstly an advanced e-signature to make signing a contract legally binding and secondly functionality to store this signature in blockchain such that it is compliant with the GDPR legislation. This is done by only storing hashed values in the blockchain and adding a user panel. In this panel, signees are able to control their personal data. High quality is obtained by testing thoroughly (100 per cent branch coverage), using the static analysis tool ESLint and requesting, receiving and implementing feedback from the software improvement group.

This report documents the design and implementation of Clusus, a cyber range to provide students with a safe isolated environment to learn about cyber security and computer networks. This Bachelor project was proposed by the TU Delft cyber security group. During a two week research phase currently existing solutions were evaluated and requirements for the system were determined. Based on these requirements and research into the capabilities of cloud providers a design was proposed. In the second phase of the project was the implementation of the design. The chosen design consists of three major components, a central server that handles the communication between the learning management system and an individual exercise, a containerized exercise, and finally a program that builds these containers. The containerized exercise consists of all virtual machines required for an exercise and a monitoring program that reports progress to the central server.

This report concludes the project 'Predictive Learning Analytics' for FeedbackFruits. It includes all the work that has been done in a ten week span at FeedbackFruits. FeedbackFruits is a company inspired to help teachers shape learning activities and spark students' active thinking, by creating an online platform on which teachers can create interactive learning activities. The goal for this project was to extend the analytics tools for interactive presentations that are offered to teachers who use the platform. This hopefully results in giving them more insight in the participation of the class, understanding of the course material and the effort that students put in their school work.

With the steady increase in space missions, enabled through technological advances and increase of commercialisation within the space flight industry, both more and increasingly complex missions can be designed for space. To this end, the Lunar Zebro project competes within this field through its small lunar rover design, drastically decreasing deployment costs and risk of the mission. The road map of Lunar Zebro aims to have a multitude of rovers deployed on the Moon, being able to complete several tasks like exploring, observing, and mapping. Since this concept of rover cooperation adds a novel level of complexity to the mission, a feasibility study is required to look into the difficulties of navigating the Moon with a larger group of rovers. LunarSim is the software package developed during this project. LunarSim aims to facilitate a simulation environment in which Lunar Zebro rovers and space mission designs can be tested and validated. To legitimise the workings of the simulation, a few scenarios have been developed to test the core functionalities of the software product. These scenarios are based on phases in a practical mission plan that consists out of navigating to and observing a crater location. The scenarios is evaluated through examination of a set of defined fitness criteria. In this report, the reader will find documentation on the development process of LunarSim: the simulation in Unity, the ROS back-end, and the bridge between these two systems. Additionally, the report elaborates how the developed software was used to aid in the feasibility study of LUFAR. First, initial research and requirements are formulated to define the scope of the simulation, after which the software architecture is introduced. Then, the systems implemented for the simulation are explained. Subsequently, the implemented rover behaviour algorithm that was used for testing is explained, with additional resources on how to develop a new custom rover behaviour. After this, an evaluation is given of the simulation based on the initial requirements and research with future research and concluding remarks. At the end of the report, the technical specifications in terms of software architecture, simulation environment, and rover behaviour are defined to give an in-depth view of LunarSim.

Our challenge was to create a server program for retail RFID system with advanced message handling. However, RFID software solutions are heavily dependent on the requirements and use cases of the system. The developed solution allows for convenient interaction with RFID tags through different components of the designed system. The complete system has been developed with scalability and maintainability in mind and is thoroughly tested using unit testing, integration testing and end-to-end testing.

Amsterdam Airport Schiphol has 5 runways, each of which can be used for take-off or landing of aeroplanes. The weather heavily influences which runway configuration air traffic control might pick. Airport Forecasting Service (AFOS) predicts which configuration of runways works most efficiently given a set of expected weather conditions and the standard deviations of wind components. These standard deviations give the system an indication of the accuracy of the weather forecasts.

Currently, the KNMI (Royal Netherlands Meteorological Institute) is the only meteorological institute that provides these standard deviations along with the weather forecast. This raises the main research question of this report: Is it possible to make accurate enough estimations of the standard deviation of wind direction and wind speed using historical data and future weather expectations. Estimating these standard deviations has been researched with two different approaches: a statistical method approach and a machine learning approach.

Statistical Methods Four fitting methods have been researched in search of the best statistical model to estimate the standard deviation of wind direction and speed: the Maximum Likelihood Method (MLM) and three Least Square Method implementations of a Weibull, Minimum Weibull and Double Weibull distribution. The performance of aggregates on the outcome of these four methods was also researched. One case takes the minimum standard deviation of the four, the other takes the mean.

MLM not only performs the best but also performs most consistently of the four fitting methods. Taking into account aggregates, MLM is more consistent than the minimum method but the minimum method outperforms it. Neither of these methods managed to meet the success criteria.

Machine Learning In regards to machine learning, the problem of estimating the standard deviations of wind direction and wind speed is a regression problem. The following machine learning models have been researched for Estimatic: MLPN, LSTM RNN, ERNN and RBFN.

LSTM RNNs outperform MLPNs, RBFNs and ERNNs for both wind direction and speed standard deviation estimation. LSTM RNN performance did not meet the success criteria.

The research concludes that it is not possible to make accurate enough estimations of the standard deviation of wind components using the historical data and future weather expectations available for Amsterdam Airport Schiphol.

For a steel company it is advantageous to be able to easily track steel through the production process. At Tata Steel this is currently done with the Material Tracking Table. However, generating this table takes months. Therefore a new system had to be developed. This paper describes the building of such a new system, which generates this Material Tracking Table in less than 1 hour, as well as the related systems concerning the acquisition of the input data and the visualisation of the resulting output data.

For the past 10 weeks, we have been tasked with improving the performance of the transaction monitoring system of bunq, an internationally active mobile bank. bunq has requested that we improve this system by automating the training of the machine learning model, providing better input data for this model and creating additional machine learning models. During this project, we have been working at the offices of bunq on this system. This thesis will give an overview of our research, software design process and implementation.

Relive is a sports application that seeks to increase the retention rate of its user base. The project entails a route builder that can be incorporated in the Relive app. A route builder has several challenges, both in supporting user-friendly interaction, rendering the map and calculating the route. These challenges lead to design goals, such as a user experience focus, optimization of performance, and continuation of the project. To achieve these goals, the project is approached in an agile way with weekly planning meetings and tri-weekly stand-ups to keep it organized and well planned. The front-end features are based on a specific target audience: the Relive users that do not use a third party app for sporting activities. The screen is intuitive and supports storing of planned routes. A route can be created, edited and loaded in the Record functionality of the Relive app. To support the front-end, the back-end handles route calculation and route storing. The route calculation is done using Dijkstra’s shortest path algorithm. In addition, a proof of concept customized route calculation is created that focuses on popularity oriented routing. Route storing makes use of the internal databases of Relive and is integrated in the existing systems. Each feature is tested with automated end-to-end and unit tests. Additionally, user tests are performed to get valuable feedback from external users. Apart from active user participation, random users were selected to join a route builder experiment. During the project, more than 22 thousand users obtained the route builder feature. Each click is timed and tracked to make sure that the feature performed as expected. Based on the events and user surveys, another iteration of the application was made by making improvements based on the acquired information. These improvements are validated using event tracking to measure the desired improvements.

Our challenge was to define a format for a mission plan, and develop an application which allows the users of the robot to create a mission plan effectively. This application should assist the user in the process of creating a mission plan as much as possible. Our client was Allseas who was already the sponsor of the LOBSTER project. During the research phase we learned that our application would be best suited for an offline environment, as the user would not necessarily have an internet connection due to being at sea. Furthermore, we learned that the application had to be easy to use and not too complex. Throughout the course of this project we worked with Scrum, our repository was hosted on GitHub, with Travis CI integrated to test our code. Using this we could see our coverage and errors could not enter our final product. In our team we cooperated with an open culture to prevent frustrations. We made agreements on work hours and software methodologies. Still, we faced challenges which ranged from underestimating time needed for certain features to an increasing complexity of code and data gathering. The final product is a web application which can be accessed offline. This application can be successfully used to create missions for Autonomous Underwater Vehicles, which we showed in our final usability evaluation. The LOBSTER team will be using our product to plan their missions in the future. However, before it can be fully used, the low-level control software of the LOBSTER robots needs to be finished by the LOBSTER team.