Developers’ Diverging Perceptions of Productivity

To overcome the ever-growing demand for software, software development organizations strive to enhance the productivity of their developers. But what does productivity mean in the context of software development? A substantial amount of work on developer productivity has been undertaken over the past four decades. The majority of this work considered productivity from a top-down perspective (the manager view) in terms of the artifacts and code created per unit of time. Common examples of such productivity measures are the lines of source code modified per hour, the resolution time for modification requests, or function points created per month. These productivity measures focus on a single, output-oriented factor for quantifying productivity, and do not take into account developers’ individual work roles, practices and other factors that might affect their productivity, such as work fragmentation, the tools used, or the work/office environment. In our research, we investigated how productivity could be quantified from the bottom-up, following a mixed-methods approach that involved more than 800 software developers. By investigating developers’ individual productivity, it is possible to better understand the individual work habits and patterns, how they relate to the productivity perceptions and also which factors are most relevant for a developer’s productivity

Why Research on Test-Driven Development is Inconclusive?

[Background] Recent investigations into the effects of Test-Driven Development (TDD) have been contradictory and inconclusive. This hinders development teams to use research results as the basis for deciding whether and how to apply TDD. [Aim] To support researchers when designing a new study and to increase the applicability of TDD research in the decision-making process in the industrial context, we aim at identifying the reasons behind the inconclusive research results in TDD. [Method] We studied the state of the art in TDD research published in top venues in the past decade, and analyzed the way these studies were set up. [Results] We identified five categories of factors that directly impact the outcome of studies on TDD. [Conclusions] This work can help researchers to conduct more reliable studies, and inform practitioners of risks they need to consider when consulting research on TDD.Comment: ESEM '20: ACM / IEEE International Symposium on Empirical Software Engineering and Measurement (ESEM), October 8--9, 2020, Bari, Ital

Rethinking Productivity in Software Engineering

Get the most out of this foundational reference and improve the productivity of your software teams. This open access book collects the wisdom of the 2017 "Dagstuhl" seminar on productivity in software engineering, a meeting of community leaders, who came together with the goal of rethinking traditional definitions and measures of productivity. The results of their work, Rethinking Productivity in Software Engineering, includes chapters covering definitions and core concepts related to productivity, guidelines for measuring productivity in specific contexts, best practices and pitfalls, and theories and open questions on productivity. You'll benefit from the many short chapters, each offering a focused discussion on one aspect of productivity in software engineering. Readers in many fields and industries will benefit from their collected work. Developers wanting to improve their personal productivity, will learn effective strategies for overcoming common issues that interfere with progress. Organizations thinking about building internal programs for measuring productivity of programmers and teams will learn best practices from industry and researchers in measuring productivity. And researchers can leverage the conceptual frameworks and rich body of literature in the book to effectively pursue new research directions. What You'll Learn Review the definitions and dimensions of software productivity See how time management is having the opposite of the intended effect Develop valuable dashboards Understand the impact of sensors on productivity Avoid software development waste Work with human-centered methods to measure productivity Look at the intersection of neuroscience and productivity Manage interruptions and context-switching Who Book Is For Industry developers and those responsible for seminar-style courses that include a segment on software developer productivity. Chapters are written for a generalist audience, without excessive use of technical terminology. ; Collects the wisdom of software engineering thought leaders in a form digestible for any developer Shares hard-won best practices and pitfalls to avoid An up to date look at current practices in software engineering productivit

An Empirical Study of Bots in Software Development -- Characteristics and Challenges from a Practitioner's Perspective

Software engineering bots - automated tools that handle tedious tasks - are increasingly used by industrial and open source projects to improve developer productivity. Current research in this area is held back by a lack of consensus of what software engineering bots (DevBots) actually are, what characteristics distinguish them from other tools, and what benefits and challenges are associated with DevBot usage. In this paper we report on a mixed-method empirical study of DevBot usage in industrial practice. We report on findings from interviewing 21 and surveying a total of 111 developers. We identify three different personas among DevBot users (focusing on autonomy, chat interfaces, and "smartness"), each with different definitions of what a DevBot is, why developers use them, and what they struggle with. We conclude that future DevBot research should situate their work within our framework, to clearly identify what type of bot the work targets, and what advantages practitioners can expect. Further, we find that there currently is a lack of general purpose "smart" bots that go beyond simple automation tools or chat interfaces. This is problematic, as we have seen that such bots, if available, can have a transformative effect on the projects that use them.Comment: To be published at the ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering (ESEC/FSE

An Exploratory Study of Productivity Perceptions in Software Teams

Software development is a collaborative process requiring a careful balance of focused individual effort and team coordination. Though questions of individual productivity have been widely examined in past literature, less is known about the interplay between developers' perceptions of their own productivity as opposed to their team’s. In this paper, we present an analysis of 624 daily surveys and 2899 self-reports from 25 individuals across five software teams in North America and Europe, collected over the course of three months. We found that developers tend to operate in fluid team constructs, which impacts team awareness and complicates gauging team productivity. We also found that perceived individual productivity most strongly predicted perceived team productivity, even more than the amount of team interactions, unplanned work, and time spent in meetings. Future research should explore how fluid team structures impact individual and organizational productivity

Rethinking Productivity in Software Engineering

Get the most out of this foundational reference and improve the productivity of your software teams. This open access book collects the wisdom of the 2017 "Dagstuhl" seminar on productivity in software engineering, a meeting of community leaders, who came together with the goal of rethinking traditional definitions and measures of productivity. The results of their work, Rethinking Productivity in Software Engineering, includes chapters covering definitions and core concepts related to productivity, guidelines for measuring productivity in specific contexts, best practices and pitfalls, and theories and open questions on productivity. You'll benefit from the many short chapters, each offering a focused discussion on one aspect of productivity in software engineering. Readers in many fields and industries will benefit from their collected work. Developers wanting to improve their personal productivity, will learn effective strategies for overcoming common issues that interfere with progress. Organizations thinking about building internal programs for measuring productivity of programmers and teams will learn best practices from industry and researchers in measuring productivity. And researchers can leverage the conceptual frameworks and rich body of literature in the book to effectively pursue new research directions. What You'll Learn Review the definitions and dimensions of software productivity See how time management is having the opposite of the intended effect Develop valuable dashboards Understand the impact of sensors on productivity Avoid software development waste Work with human-centered methods to measure productivity Look at the intersection of neuroscience and productivity Manage interruptions and context-switching Who Book Is For Industry developers and those responsible for seminar-style courses that include a segment on software developer productivity. Chapters are written for a generalist audience, without excessive use of technical terminology. ; Collects the wisdom of software engineering thought leaders in a form digestible for any developer Shares hard-won best practices and pitfalls to avoid An up to date look at current practices in software engineering productivit

Franchising: A literature review on management and control issues.

Franchising; Literature review; Management control;