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Software Startups - A Research Agenda

Software startup companies develop innovative, software-intensive products within limited timeframes and with few resources, searching for sustainable and scalable business models. Software startup ...

Functional Size Measures and Effort Estimation in Agile Development: a Replicated Study

To help developers during the Scrum planning poker, in our previous work we ran a case study on a Moonlight Scrum process to understand if it is possible to introduce functional size metrics to improve estimation accuracy and to measure the accuracy of expert-based estimation. The results of this original study showed that expert-based estimations are more accurate than those obtained by means of models, calculated with functional size measures. To validate the results and to extend them to plain Scrum processes, we replicated the original study twice, applying an exact replication to two plain Scrum development processes. The results of this replicated study show that the accuracy of the effort estimated by the developers is very accurate and higher than that obtained through functional size measures. In particular, SiFP and IFPUG Function Points, have low predictive power and are thus not help to improve the estimation accuracy in Scrum.

Self-organized learning in software factory: experiences and lessons learned

Self-organization is one of the key agile principles. How it can be applied in an educational context is not explored extensively. In this paper we draw on relevant educational literature as the theoretical basis to investigate the self-organized learning that happens in Software Factory, an experimental, shared educational platform between several universities. Based on a comparative case study of two Software Factories we identified a set of themes that can potentially explain self-organization from the learning viewpoint. These themes include self-decided learning goals and personalized learning outcomes, peer teaching through active collaboration, diversity is the key and the personal attitude towards the learning matters. We also reported how students perceive the necessary infrastructure and the role of traditional lecturing and teachers in the Software Factory context. The study contributes to a better offering of learning experience in software engineering education by making most out of the self-organized learning approach.

The predictor impact of Web search media on Bitcoin trading volumes

In the last decade, Web 2.0 services have been widely used as communication media. Due to the huge amount of available information, searching has become dominant in the use of Internet. Millions of users daily interact with search engines, producing valuable sources of interesting data regarding several aspects of the world. Search queries prove to be a useful source of information in financial applications, where the frequency of searches of terms related to the digital currency can be a good measure of interest in it. Bitcoin, a decentralized electronic currency, represents a radical change in financial systems, attracting a large number of users and a lot of media attention. In this work we studied the existing relationship between Bitcoins trading volumes and the queries volumes of Google search engine. We achieved significant cross correlation values, demonstrating search volumes power to anticipate trading volumes of Bitcoin currency.

Requirements Elicitation Techniques Applied in Software Startups

Requirements elicitation is the first crucial stage of a requirements engineering process, which intends to uncover, acquire and elaborate requirements for software systems. When software startups are concerned, requirements elicitation is particularly challenging due to the high uncertainty that a startup is confronted with. Few studies have investigated how software startups conduct requirements elicitation and what techniques are used in such a context. This study intends to address this knowledge gap. Three software startups from different part of the globe were studied. The findings reveal that the requirements elicitation process in startups is primordial and mainly informal, and it is an ongoing process alongside with product evolution. Software startups do employ established requirements elicitation techniques including interviews, prototyping and brainstorming. They also utilize other less common ones such as competitor analysis, collaborative team discussion and use of model users. This study highlights the market-driven nature of requirements that software startups have to deal with, and offers the first insights on the requirements elicitation techniques that could be relevant and applicable in the context of software startups.

Using measurement and simulation for understanding distributed development processes in the cloud

Organizations increasingly develop software in a distributed manner. The Cloud provides an environment to create and maintain software-based products and services. Currently, it is widely unknown which software processes are suited for Cloud-based development and what their effects in specific contexts are. This paper presents a process simulation to study distributed development in the Cloud. We contribute a simulation model, which helps analyzing different project parameters and their impact on projects carried out in the Cloud. The simulator helps reproducing activities, developers, issues and events in the project, and it generates statistics, e.g., on throughput, total time, and lead and cycle time. The aim of this simulation model is thus to analyze the tradeoffs regarding throughput, total time, project size, and team size. Furthermore, the modified simulation model aims to help project managers select the most suitable planning alternative. Based on observed projects in Finland and Spain, we simulated a distributed project using artificial and real data. Particularly, we studied the variables project size, team size, throughput, and total project duration. A comparison of the real project data with the results obtained from the simulation shows the simulation producing results close to the real data, and we could successfully replicate a distributed software project. By improving the understanding of distributed development processes, our simulation model thus supports project managers in their decision-making.

Is Bitcoin’s Market Predictable? Analysis of Web Search and Social Media

In recent years, Internet has completely changed the way real life works. In particular, it has been possible to witness the online emergence of web 2.0 services that have been widely used as communication media. On one hand, services such as blogs, tweets, forums, chats, email have gained wide popularity. On the other hand, due to the huge amount of available information, searching has become dominant in the use of Internet. Millions of users daily interact with search engines, producing valuable sources of interesting data regarding several aspects of the world. Bitcoin, a decentralized electronic currency, represents a radical change in financial systems, attracting a large number of users and a lot of media attention. In this work we studied whether Bitcoin’s trading volume is related to the web search and social volumes about Bitcoin. We investigated whether public sentiment, expressed in large-scale collections of daily Twitter posts, can be used to predict the Bitcoin market too. We achieved significant cross correlation outcomes, demonstrating the search and social volumes power to anticipate trading volumes of Bitcoin currency.