Matthias Uflacker

Christoph Matthies, Thomas Kowark, Keven Richly et al.

Agile methods are best taught in a hands-on fashion in realistic projects. The main challenge in doing so is to assess whether students apply the methods correctly without requiring complete supervision throughout the entire project. This paper presents experiences from a classroom project where 38 students developed a single system using a scaled version of Scrum. Surveys helped us to identify which elements of Scrum correlated most with student satisfaction or posed the biggest challenges. These insights were augmented by a team of tutors, which accompanied main meetings throughout the project to provide feedback to the teams, and captured impressions of method application in practice. Finally, we performed a post-hoc, tool-supported analysis of collaboration artifacts to detect concrete indicators for anti-patterns in Scrum adoption. Through the combination of these techniques we were able to understand how students implemented Scrum in this course and which elements require further lecturing and tutoring in future iterations. Automated analysis of collaboration artifacts proved to be a promising addition to the development process that could potentially reduce manual efforts in future courses and allow for more concrete and targeted feedback, as well as more objective assessment.

Christoph Matthies, Thomas Kowark, Keven Richly et al.

Linting tools automatically identify source code fragments that do not follow a set of predefined standards. Such feedback tools are equally desirable for "linting" agile development processes. However, providing concrete feedback on process conformance is a challenging task, due to the intentional lack of formal agile process models. In this paper, we present ScrumLint, a tool that tackles this issue by analyzing development artifacts. On the basis of experiences with an undergraduate agile software engineering course, we defined a collection of process metrics. These contain the core ideas of agile methods and report deviations. Using this approach, development teams receive immediate feedback on their executed development practices. They can use this knowledge to improve their workflows, or can adapt the metrics to better reflect their project reality.

Christoph Matthies, Thomas Kowark, Matthias Uflacker et al.

Teaching agile software development by pairing lectures with hands-on projects has become the norm. This approach poses the problem of grading and evaluating practical project work as well as process conformance during development. Yet, few best practices exist for measuring the success of students in implementing agile practices. Most university courses rely on observations during the course or final oral exams. In this paper, we propose a set of metrics which give insights into the adherence to agile practices in teams. The metrics identify instances in development data, e.g. commits or user stories, where agile processes were not followed. The identified violations can serve as starting points for further investigation and team discussions. With contextual knowledge of the violation, the executed process or the metric itself can be refined. The metrics reflect our experiences with running a software engineering course over the last five years. They measure aspects which students frequently have issues with and that diminish process adoption and student engagement. We present the proposed metrics, which were tested in the latest course installment, alongside tutoring, lectures, and oral exams.

Christoph Matthies, Arian Treffer, Matthias Uflacker

Teaching programming using Massive Open Online Courses (MOOCs) is gaining popularity due to their scalability and efficiency of knowledge distribution. However, participating in these courses usually means fully committing to the supplied programming environment in the browser. While this allows a consistent and controllable setup, learners do not gain experience with actual development tools, such as local code editors, testing frameworks, issue trackers or continuous integration (CI) services, which is critical for subsequent real-world projects. Furthermore, the tests for the functionality that is to be developed are oftentimes already available in MOOCs and simply need to be executed, leading to less involvement with developing appropriate tests. In order to tackle these issues while maintaining a high degree of automation and scalability, we developed Prof. CI, a novel approach to conducting online exercises. Prof. CI leverages the existing automation infrastructure that developers use daily, i.e. CI services and Github workflows, to teach test-driven development (TDD) practices. Participants work on their own repositories in Github and receive feedback and new challenges from the CI server when they push their code. We have successfully applied this approach in a pilot project with 30 undergraduate students learning the Ruby on Rails web development framework. Our evaluation shows that the exercise effectively increased students' motivation to write tests for their code. We also present the results of participant surveys, students' experiences and teachers' observations.

Arian Treffer, Michael Perscheid, Matthias Uflacker

With back-in-time debuggers, developers can explore what happened before observable failures by following infection chains back to their root causes. While there are several such debuggers for object-oriented programming languages, we do not know of any back-in-time capabilities at the database-level. Thus, if failures are caused by SQL scripts or stored procedures, developers have difficulties in understanding their unexpected behavior. In this paper, we present an approach for bringing back-in-time debugging down to the SAP HANA in-memory database. Our TARDISP debugger allows developers to step queries backwards and inspecting the database at previous and arbitrary points in time. With the help of a SQL extension, we can express queries covering a period of execution time within a debugging session and handle large amounts of data with low overhead on performance and memory. The entire approach has been evaluated within a development project at SAP and shows promising results with respect to the gathered developer feedback.