BACKGROUND-The software intensive industry is moving towards the adoption of a value-driven and adaptive real-time business paradigm. The traditional view of software as an item that evolves through releases every few months is being replaced by the continuous evolution of software functionality. OBJECTIVE-This study aims to classify and analyse the literature related to continuous deployment in the software domain in order to scope the phenomenon, provide an overview of the state-of-the-art, investigate the scientific evidence in the reported results and identify areas suitable for further research. METHOD-We conducted a systematic mapping study and classified the continuous deployment literature. The benefits and challenges related to continuous deployment were also analysed. RESULTS-The systematic mapping study includes 50 primary studies published between 2001 and 2014. An in-depth analysis of the primary studies revealed ten recurrent themes that characterize continuous deployment and provide researchers with directions for future work. In addition, a set of benefits and challenges of which practitioners may take advantage were identified. CONCLUSION-Overall, although the topic area is very promising, it is still in its infancy, thus offering a plethora of new opportunities for both researchers and software intensive companies.

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[Context] Controlled experiments are an important empirical method to generate and validate theories. Many software engineering experiments are conducted with students. It is often claimed that the use of students as participants in experiments comes at the cost of low external validity while using professionals does not. [Objective] We believe a deeper understanding is needed on the external validity of software engineering experiments conducted with students or with professionals. We aim to gain insight about the pros and cons of using students and professionals in experiments. [Method] We performed an unconventional, focus group approach and a follow-up survey. First, during a session at ISERN 2014, 65 empirical researchers, including the seven authors, argued and discussed the use of students in experiments with an open mind. Afterwards, we revisited the topic and elicited experts' opinions to foster discussions. Then we derived 14 statements and asked the ISERN attendees excluding the authors, to provide their level of agreement with the statements. Finally, we analyzed the researchers' opinions and used the findings to further discuss the statements. [Results] Our survey results showed that, in general, the respondents disagreed with us about the drawbacks of professionals. We, on the contrary, strongly believe that no population (students, professionals, or others) can be deemed better than another in absolute terms. [Conclusion] Using students as participants remains a valid simplification of reality needed in laboratory contexts. It is an effective way to advance software engineering theories and technologies but, like any other aspect of study settings, should be carefully considered during the design, execution, interpretation, and reporting of an experiment. The key is to understand which developer population portion is being represented by the participants in an experiment. Thus, a proposal for describing experimental participants is put forward

Context: Successful startup firms have the ability to create jobs and contribute to economic welfare. A suitable ecosystem developed around startups is important to form and support these firms. In this regard, it is crucial to understand the startup ecosystem, particularly from researchers' and practitioners' perspectives. However, a systematic literature research on the startup ecosystem is limited. Objective: In this study, our objective was to conduct a multi-vocal literature review and rigorously find existing studies on the startup ecosystem in order to organize and analyze them, know the definitions and major elements of this ecosystem, and determine the roles of such elements in startups' product development. Method: We conducted a multi-vocal literature review to analyze relevant articles, which are published technical articles, white papers, and Internet articles that focused on the startup ecosystem. Our search generated 18,310 articles, of which 63 were considered primary candidates focusing on the startup ecosystem. Results: From our analysis of primary articles, we found four definitions of a startup ecosystem. These definitions used common terms, such as stakeholders, supporting organization, infrastructure, network, and region. Out of 63 articles, 34 belonged to the opinion type, with contributions in the form of reports, whereas over 50% had full relevance to the startup ecosystem. We identified eight major elements (finance, demography, market, education, human capital, technology, entrepreneur, and support factors) of a startup ecosystem, which directly or indirectly affected startups. Conclusions: This study aims to provide the state of the art on the startup ecosystem through a multi-vocal literature review. The results indicate that current knowledge on the startup ecosystem is mainly shared by non-peer-reviewed literature, thus signifying the need for more systematic and empirical literature on the topic. Our study also provides some recommendations for future work.

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Following a well-established track record of success in other domains such as manufacturing, Kanban is increasingly used to achieve continuous development and delivery of value in the software industry. However, while research on Kanban in software is growing, these articles are largely descriptive, and there is limited rigorous research on its application and with little cohesive building of cumulative knowledge. As a result, it is extremely difficult to determine the true value of Kanban in software engineering. This study investigates the scientific evidence to date regarding Kanban by conducting a systematic mapping of Kanban literature in software engineering between 2006 and 2016. The search strategy resulted in 382 studies, of which 23 were identified as primary papers relevant to this research. This study is unique as it compares the findings of these primary papers with insights from a review of 23 Kanban experience reports during the same period. This study makes four important contributions, (i) a state-of-the-art of Kanban research is provided, (ii) the reported benefits and challenges are identified in both the primary papers and experience reports, (iii) recommended practices from both the primary papers and experience reports are listed and (iv) opportunities for future Kanban research are identified.

Background: Test-driven development (TDD) is a technique that repeats short coding cycles interleaved with testing. The developer first writes a unit test for the desired functionality, followed by the necessary production code, and refactors the code. Many empirical studies neglect unique process characteristics related to TDD iterative nature. Aim: We formulate four process characteristic: sequencing, granularity, uniformity, and refactoring effort. We investigate how these characteristics impact quality and productivity in TDD and related variations. Method: We analyzed 82 data points collected from 39 professionals, each capturing the process used while performing a specific development task. We built regression models to assess the impact of process characteristics on quality and productivity. Quality was measured by functional correctness. Result: Quality and productivity improvements were primarily positively associated with the granularity and uniformity. Sequencing, the order in which test and production code are written, had no important influence. Refactoring effort was negatively associated with both outcomes. We explain the unexpected negative correlation with quality by possible prevalence of mixed refactoring. Conclusion: The claimed benefits of TDD may not be due to its distinctive test-first dynamic, but rather due to the fact that TDD-like processes encourage fine-grained, steady steps that improve focus and flow.