Context: Software start-ups are emerging as suppliers of innovation and software-intensive products. However, traditional software engineering practices are not evaluated in the context, nor adopted to goals and challenges of start-ups. As a result, there is insufficient support for software engineering in the start-up context. Objective: We aim to collect data related to engineering goals, challenges, and practices in start-up companies to ascertain trends and patterns characterizing engineering work in start-ups. Such data allows researchers to understand better how goals and challenges are related to practices. This understanding can then inform future studies aimed at designing solutions addressing those goals and challenges. Besides, these trends and patterns can be useful for practitioners to make more informed decisions in their engineering practice. Method: We use a case survey method to gather first-hand, in-depth experiences from a large sample of software start-ups. We use open coding and cross-case analysis to describe and identify patterns, and corroborate the findings with statistical analysis. Results: We analyze 84 start-up cases and identify 16 goals, 9 challenges, and 16 engineering practices that are common among start-ups. We have mapped these goals, challenges, and practices to start-up life-cycle stages (inception, stabilization, growth, and maturity). Thus, creating the progression model guiding software engineering efforts in start-ups. Conclusions: We conclude that start-ups to a large extent face the same challenges and use the same practices as established companies. However, the primary software engineering challenge in start-ups is to evolve multiple process areas at once, with a little margin for serious errors.

This study aims to characterize the state-of-the-art of the software startup education by analyzing and identifying best practices, opportunities and gaps on this field. To do so, we conducted a systematic mapping study in order to analyze and evaluate studies on software startup education. As a result, we found 31 publications in this process. These studies were classified into four categories: real projects, multidiscipline, environment and teaching. We concluded that research on software startup education is still scarce. Furthermore, there are several gaps and opportunities to be explored in future works. One of them is the difficulty in providing a real world experience in a educational setting. Successful cases reported combine three major components: real world projects, the right environment and a multidisciplinary context.

The advances in technology have enabled people to develop services and products that can reach millions of people around the world. Facebook and Google are examples of successful startups. However, most startups fail in their first years of life. From an education standpoint, even though universities are adapting their curriculums in order to embrace startup education content, the challenge still remains: how can we provide real world experiences for students to build relevant startups? In order to fill this gap, this paper introduces the Challenge Based Startup Learning, a framework that combines the Challenge Based Learning methodology with Lean Startup and Customer Development concepts, supported by software development techniques. We have applied and evaluated the framework in an undergraduate digital entrepreneurship course. Our preliminary results indicate that students not only understood what it takes to run a real startup, but they also felt engaged and empowered by delivering a useful and meaningful software.

Training students on mobile application development inherits the challenges of teaching software engineering where the target computer is a device that has a large number of features accessible by software.Furthermore, the most related experience in teaching students reveals difficulties in developing software engineering competencies.In this paper we present results from an iOS course held in a smart learning environment that adopted the Challenge Based Learning framework as the teaching methodology.Our results indicate that combining an active methodology along with an engaging environment can foster and improve software development learning.

Context:Software startups are increasingly seen as opportunities in a varieties of areas; from simple applications, as personal controls, to complex solutions, involving artificial intelligence or using big data.The process of developing these solutions happens quickly and in abbreviated form.Thus, software engineering should be adapted to better understand this world of software startups in a way to assist them in their customer discovery challenges and in the search for scalable business models.Main Goal: Understand the factors that positively and negatively influence the software development of software startups and present solutions found in an empirical study on startups located in an innovation ecosystem Methodology: We conducted interviews and observations as data collection techniques in eight software startups located at a Tech Park.