Software development in startup companies: A systematic mapping study

Abstract

Context: Software startups are newly created companies with no operating history and fast in producing cutting-edge technologies. These companies develop software under highly uncertain conditions, tackling fast-growing markets under severe lack of resources. Therefore, software startups present an unique combination of characteristics which pose several challenges to software development activities. Objective: This study aims to structure and analyze the literature on software development in startup companies, determining thereby the potential for technology transfer and identifying software development work practices reported by practitioners and researchers. Method: We conducted a systematic mapping study, developing a classification schema, ranking the selected primary studies according their rigor and relevance, and analyzing reported software development work practices in startups. Results: A total of 43 primary studies were identified and mapped, synthesizing the available evidence on software development in startups. Only 16 studies are entirely dedicated to software development in startups, of which 10 result in a weak contribution (advice and implications (6); lesson learned (3); tool (1)). Nineteen studies focus on managerial and organizational factors. Moreover, only 9 studies exhibit high scientific rigor and relevance. From the reviewed primary studies, 213 software engineering work practices were extracted, categorized and analyzed. Conclusion: This mapping study provides the first systematic exploration of the state-of-art on software startup research. The existing body of knowledge is limited to a few high quality studies. Furthermore, the results indicate that software engineering work practices are chosen opportunistically, adapted and configured to provide value under the constrains imposed by the startup context.

What Influences the Speed of Prototyping? An Empirical Investigation of Twenty Software Startups

“…A literature survey of software development shows that startups often build a prototype in an evolutionary fashion and quickly learn from users' feedback [20]. We argue that both throwaway prototypes and evolutionary prototypes are important parts of startups' journey to a launched product.…”

“…Olsson et al present a Hypothesis Experiment Data-Driven Development model that integrates feature experiments with customer feedback in Agile projects [19]. While these work characterize a process-like approach in developing startups' software products, Paternoster et al grounded a model from 13 software startups which describes a pattern that software startups often build evolutionary prototypes [20]. This study focuses on how startups are prototyping in reality and the influencing factors of the speed of learning by prototyping.…”

“…Startups often struggle with thriving in a technical uncertainty, whether under market pull or technology push impacts [20]. Due to different reasons, e.g., specific devices, platforms or protocols becoming popular in market, or new technology gaining momentum, there are needs for changing the current product's features to accommodate new technology (S01, S09, S11).…”

An empirical study on software engineering and software startups: Findings from cases in an innovation ecosystem

“…While an established (even small) company has a validated business model, startups are in the pursuit of a business model. Startups have some recurring features [9]:…”

“…Startup could be defined as a human institution designed to deliver a new product or service under conditions of extreme uncertainty [10].We can define a subset of startups that have their software-based solutions as software startups or digital startups. These are considered to be newly created companies with no operational history and are incredibly fast in the production of cutting-edge technologies [9]. DOI reference number: 10.18293/SEKE2017-115…”