Shared Mental Models, Familiarity, and Coordination: A Multi-Method Study of Distributed Software Teams

Coordination is important in large-scale software development because of the many people involved and the complex dependencies present in software tasks. Even small improvements in productivity can lead to substantial cost savings and competitive advantage. But despite great technological advances in software engineering and collaboration tools in recent years, coordination in software development projects continues to be problematic. Traditional theories suggest that team members coordinate by programming their tasks and by communicating with each other, but more recent research also suggests that they coordinate through work familiarity, and team cognition mechanisms like shared mental models. This paper reports on the results of a multi-method research investigation of how shared mental models, work familiarity and geographic dispersion affect coordination in software teams. This research is based on three studies conducted at a large telecommunications company: face-to-face interviews, survey, and archival studies. Results show that shared mental models have a positive effect on team coordination and that prior familiarity with the same software parts and projects reduces software development time. Results also indicate that geographic dispersion increases software development time and that the effect of work familiarity is stronger for geographically distributed teams than for colocated teams

Utilising mobile data collection software

This report details a project which involved a software review and business investigation for the development and implementation of mobile data collection software across Beca Limited (Beca). The use of mobile data collection software, for the production of documents such as site inspections and as-built reports, offer a number of benefits including improved accuracy, efficiency, and consistency. Potential users of the software applications are either not aware of software available and the value they offer, or cannot justify the cost associated with implementing the software for their projects. The investigation and review has highlighted issues currently present with the mobile data collection and recommendations are development. The recommendations are in line with Beca's business and IT strategies, and aim to eliminate or reduce the issues that are currently present. They aim to achieve a consolidated, consistent and valuable software solution for Beca. This move into more advanced technology, increasing efficiency and effectiveness of their operations, as well as being an adaptable and scalable application for future growth of the company

Abstract

Coordination is important in large-scale software development because of the many people involved and the complex dependencies present in software tasks. Even small improvements in productivity can lead to substantial cost savings and competitive advantage. But despite great technological advances in software engineering and collaboration tools in recent years, coordination in software development projects continues to be problematic. Traditional theories suggest that team members coordinate by programming their tasks and by communicating with each other, but more recent research also suggests that they coordinate through work familiarity, and team cognition mechanisms like shared mental models. This paper reports on the results of a multi-method research investigation of how shared mental models, work familiarity and geographic dispersion affect coordination in software teams. This research is based on three studies conducted at a large telecommunications company: face-to-face interviews, survey, and archival studies. Results show that shared mental models have a positive effect on team coordination and that prior familiarity with the same software parts and projects reduces software development time. Results also indicate that geographic dispersion increases software development time and that the effect of work familiarity is stronger for geographicall

Questions for Data Scientists in Software Engineering: A Replication

In 2014, a Microsoft study investigated the sort of questions that data science applied to software engineering should answer. This resulted in 145 questions that developers considered relevant for data scientists to answer, thus providing a research agenda to the community. Fast forward to five years, no further studies investigated whether the questions from the software engineers at Microsoft hold for other software companies, including software-intensive companies with different primary focus (to which we refer as software-defined enterprises). Furthermore, it is not evident that the problems identified five years ago are still applicable, given the technological advances in software engineering. This paper presents a study at ING, a software-defined enterprise in banking in which over 15,000 IT staff provides in-house software solutions. This paper presents a comprehensive guide of questions for data scientists selected from the previous study at Microsoft along with our current work at ING. We replicated the original Microsoft study at ING, looking for questions that impact both software companies and software-defined enterprises and continue to impact software engineering. We also add new questions that emerged from differences in the context of the two companies and the five years gap in between. Our results show that software engineering questions for data scientists in the software-defined enterprise are largely similar to the software company, albeit with exceptions. We hope that the software engineering research community builds on the new list of questions to create a useful body of knowledge

Shared Mental Models, Familiarity and Coordination; A Multi-Method Study of Distributed Software Teams

Coordination is important in large-scale software development because of the many people involved and the complex dependencies present in software tasks. Even small improvements in productivity can lead to substantial cost-savings and competitive advantage. But despite great technological advances in software engineering and collaboration tools in recent years, coordination in software development projects continues to be problematic. Traditional theories suggest that team members coordinate by programming their tasks and by communicating with each other, but more recent research also suggest that they coordinate through work familiarity and team cognition mechanisms like shared mental models. This paper reports on the results of a multi-method research investigation of how shared mental models, work familiarity and geographic dispersion affect coordination in software teams. This research is based on three studies conducted at a large telecommunications company: face-to-face interviews, survey, and archival studies. Results show that shared mental models have a positive effect on team coordination and that prior familiarity with the same software parts and projects reduces software development time. Results also indicate that geographic dispersion increases software development time and that the effect of work familiarity is stronger for geographically distributed teams than for co-located teams. Keywords: shared mental models, familiarity, distributed teams, software teams, coordination A Multi-Method Study of Distributed Software Team

Questions for Data Scientists in Software Engineering: A Replication

In 2014, a Microsoft study investigated the sort of questions that data science applied to software engineering should answer. This resulted in 145 questions that developers considered relevant for data scientists to answer, thus providing a research agenda to the community. Fast forward to five years, no further studies investigated whether the questions from the software engineers at Microsoft hold for other software companies, including software-intensive companies with different primary focus (to which we refer as software-defined enterprises). Furthermore, it is not evident that the problems identified five years ago are still applicable, given the technological advances in software engineering. This paper presents a study at ING, a software-defined enterprise in banking in which over 15,000 IT staff provides in-house software solutions. This paper presents a comprehensive guide of questions for data scientists selected from the previous study at Microsoft along with our current work at ING. We replicated the original Microsoft study at ING, looking for questions that impact both software companies and software-defined enterprises and continue to impact software engineering. We also add new questions that emerged from differences in the context of the two companies and the five years gap in between. Our results show that software engineering questions for data scientists in the software-defined enterprise are largely similar to the software company, albeit with exceptions. We hope that the software engineering research community builds on the new list of questions to create a useful body of knowledge.Software EngineeringElectrical Engineering, Mathematics and Computer ScienceSoftware Technolog