The Work Life of Developers: Activities, Switches and Perceived Productivity

Abstract

Many software development organizations strive to enhance the productivity of their developers. All too often, efforts aimed at improving developer productivity are undertaken without knowledge about how developers spend their time at work and how it influences their own perception of productivity. To fill in this gap, we deployed a monitoring application at 20 computers of professional software developers from four companies for an average of 11 full workdays in situ. Corroborating earlier findings, we found that developers spend their time on a wide variety of activities and switch regularly between them, resulting in highly fragmented work. Our findings extend beyond existing research in that we correlate developers' work habits with perceived productivity and also show productivity is a personal matter. Although productivity is personal, developers can be roughly grouped into morning, low-at-lunch and afternoon people. A stepwise linear regression per participant revealed that more user input is most often associated with a positive, and emails, planned meetings and work unrelated websites with a negative perception of productivity. We discuss opportunities of our findings, the potential to predict high and low productivity and suggest design approaches to create better tool support for planning developers' workdays and improving their personal productivity. Abstract-Many software development organizations strive to enhance the productivity of their developers. All too often, efforts aimed at improving developer productivity are undertaken without knowledge about how developers spend their time at work and how it influences their own perception of productivity. To fill in this gap, we deployed a monitoring application at 20 computers of professional software developers from four companies for an average of 11 full workdays in situ. Corroborating earlier findings, we found that developers spend their time on a wide variety of activities and switch regularly between them, resulting in highly fragmented work. Our findings extend beyond existing research in that we correlate developers' work habits with perceived productivity and also show productivity is a personal matter. Although productivity is personal, developers can be roughly grouped into morning, low-at-lunch and afternoon people. A stepwise linear regression per participant revealed that more user input is most often associated with a positive, and emails, planned meetings and work unrelated websites with a negative perception of productivity. We discuss opportunities of our findings, the potential to predict high and low productivity and suggest design approaches to create better tool support for planning developers' workdays and improving their personal productivity.

What Predicts Software Developers’ Productivity?

“…To focus their effort, developers, management, and executives can use our productivity factor ranking to prioritize what is otherwise a wide array of investment options. 3 In short, prior research provides many ways that organizations can improve software developer productivity, and our research provides a way to prioritize them.…”

“…Similar to Meyer and colleagues' recent investigation into software developer productivity [3], we have chosen to use survey questions as a subjective measurement of productivity, for two main reasons. First, as Ramírez and Nembhard note, surveys are a "straightforward and commonly used method to measure [knowledge worker] productivity" [2].…”

“…Beyond these examples, Wagner and Ruhe's systematic review provides a good overview of the individual productivity factors that correlate with productivity [14]. Likewise, Meyer and colleagues provide a more recent overview of productivity factors [3]. In general, our work builds on these factor-by-factor productivity studies by broadly investigating a wide variety of factors.…”

The effect of noise on software engineers' performance

“…Flow is a state of high concentration that results in an absolute assimilation in the activity at hand (e.g., so ware development) [11]. Disturbance from the surrounding environment in which the activity is taking place (e.g., due to noise) can disrupt a state of ow causing work fragmentation and negative impact on productivity [27]. Alongside, Meyer et al [28] found that developers feel productive when they do not need to switch between tasks and are not interrupted.…”

Context-Augmented Software Development in Traditional and Big Data Projects: Literature Review and Preliminary Framework

“…Software development in traditional and big data projects is a complex knowledge-intensive [1] effort [2]: there is a broad number of different technologies involved in software development. Documentation for the technologies used is everywhere, i.e., Tutorials, Stack Overflow, GitHub, Project Wikis, API Tutorials, and others.…”