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The use of empirical studies with students in software engineering helps researchers gain insight into new or existing techniques and methods. However, due mainly to concerns of external validity, questions have been raised about the value of these types of studies. The authors of this paper draw on their experiences of conducting a large number of empirical studies in university courses in three countries (Italy, Norway, and the United States) to address this important issue. This paper first identifies the requirements that research and pedagogy place on a valid empirical study with students. This information is then used as the basis for a checklist that provides guidance for researchers and educators when planning and conducting studies in university courses. The goal of this checklist is to help ensure that these studies have as much research and pedagogical value as possible. Finally, an example application of the checklist is provided to illustrate its use

Context] Software startups have long been a significant driver in economic growth and innovation. The on-going failure of the major number of startups calls for a better understanding of state-of-the-practice of startup activities.[Objective] With a focus on engineering perspective, this study aims at identifying the change in focus of research area and thematic concepts operating startup research. [Method] A systematic mapping study on 74 primary papers (in which 27 papers are newly selected) from 1994 to 2017 was conducted with a comparison with findings from previous mapping studies. A classification schema was developed, and the primary studies were ranked according to their rigour. [Results] We discovered that most research has been conducted within the SWEBOK knowledge areas software engineering process, management, construction, design, and requirements, with the shift of focus towards process and management areas. We also provide an alternative classification for future startup research. We find that the rigour of the primary papers was assessed to be higher between 2013-2017 than that of 1994-2013. We also find an inconsistency of characterizing startups. [Conclusions] Future work can focus on certain research themes, such as startup evolution models and human aspects, and consolidate the thematic concepts describing software startups.

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