Sebastian Baltes

Software Engineering
Empirical Research
Interdisciplinarity

This page provides an overview of my previous and ongoing research projects, arranged along seven main research areas. Many projects we work on focus on software analytics, that is, processing, analyzing, and visualizing software engineering data to monitor, govern, and improve software development processes and tools. We are further interested in interdisciplinary research and methodological aspects of empirical software engineering. We are convinced that thoroughly analyzing and understanding the state-of-practice is an essential first step towards improving how software is being developed. Our vision is that software engineering becomes more evidence-based, which is only possible if academic researchers provide actionable insights on topics that are relevant to practitioners. You can find more information on my personal notion of empirical software engineering in my research statement.

Data-driven decision making in software engineering

Projects in this research area are include empirical studies performed or tool prototypes built to support data-driven decision making in software projects. In our paper Taming Timeout Flakiness: An Empirical Study of SAP HANA, for example, we empirically analyzed the impact of test case timeouts on test flakiness and proposed and evaluated a cost-optimal alternative to the commonly used baseline of developer-defined timeout values. Our paper Visually Analyzing Company-wide Software Service Dependencies: An Industrial Case Study reports how we developed a tailored visualization for company-wide software service dependencies that was used to guide service deprecation and retirement. With our global Pandemic Programming study, we were among the first researchers to provide data-driven recommendations for organizations to better understand and support their developers in a forced work from home setup.

Human-centric software engineering

Software is developed with and for a wide range of stakeholders. Better understanding how human behavior impacts software development and vice versa is another research area we work on. Our paper UX Debt: Developers Borrow While Users Pay we, for example, investigated the relationship of traditional code-centric notions of technical debt and the broader concept of user experience debt. Another example is our paper “STILL AROUND”: Experiences and Survival Strategies of Veteran Women Software Developers, where we studied the intersection of ageism and sexism in the software industry by interviewing veteran software developers belonging to marginalized genders.

Mining software repositories

Projects in this research area typically analyze data from (large) software repositories, including version control systems, issue tracking systems, or developer Q&A forums, with the goal of identifying patterns or deriving recommendations. In the past, we studied aspects such as links in commit messages, how developers use novel features such as GitHub Discussions, characterized how developers search for content on Stack Overflow, or if and how they attribute code snippets from Stack Overflow when they reuse them in GitHub projects.

Meta-scientific issues in software engineering research

As empirical software engineering matures as a discipline, meta-scientific discussions on how to best conduct empirical research in software engineering get more and more important. An issue we focused on early is the effectiveness and ethical implications of different strategies for sampling software developers. We later continued that line of work with a critical review of sampling in software engineering research. Another aspect we published about is secondary research in software engineering, which is still quite rudimentary compared to other disciplines.

Developer experience and tool support

Developer experience refers to how the interplay of people (developers and other stakeholders) and the environment (processes, tools, culture, technology) positively or negatively affect different parts of the software development lifecycle. This broad area touches “micro” aspects such as developer’s local tooling but also “macro” aspects such as documentation ecosystems that developers rely on in their daily work. Related aspects are developer productivity, wellbeing, and satisfaction, all of which are difficult to accurately describe and operationalize. This category also shows that the research areas outlined on this page overlap, as our Pandemic Programming study also captured developers’ self-assessed productivity and wellbeing as central aspects. Other papers in this area presented novel tool prototypes, for example, to better integrate cost transparency in the development of cloud applications or to support developers in linking documentation and source code.

Behavioral studies of software developers

Traces of software developers’ behavior can be found in existing repositories and artifacts (see mining software repositories), but it can also be studied using other empirical research methods such as lab and field studies, online surveys, and interviews. Our previous work in this area includes a study on how developers debug performance bugs in a pair programming setting, how they use sketches and diagrams in their daily work, and how they link documentation resources.

Interdisciplinary research

Interdisciplinary research in software engineering can mean applying concepts from other disciplines such as psychology or mathematics to software engineering problems. However, it can also mean working with researchers from other disciplines on problems rooted in software engineering or in their domain. It can also mean conducting a study focusing on software engineering, the results of which are then picked up in other disciplines as well.