I Know What You Did Last Summer - An Investigation of How Developers Spend Their Time

Minelli, Roberto; Mocci, Andrea; Lanza, Michele

doi:10.1109/icpc.2015.12

Cited by 143 publications

(99 citation statements)

References 28 publications

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“…As an example, Goncalves and colleagues found in their observations and interviews that developers spend 45% of their time collaborating, 32% for seeking information, and they only use software process tools during 9% of their time [23]. More recent studies by Minelli et al [12] and Amann et al [13] focused on how developers spend their time inside the IDE.…”

Section: Developers' Work Practicesmentioning

confidence: 99%

“…Other studies have focused on how developers spend their time inside the Integrated Development Environment (IDE) (e.g., [12], [13]). The industry has also seen an increasing trend with self-monitoring tools to track activity and work habits, with applications such as RescueTime [14] or Codealike [15].…”

Section: Ko Et Al Observed Software Developers To Determine Whatmentioning

confidence: 99%

See 1 more Smart Citation

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

Meyer

Barton

Murphy

et al. 2017

IIEEE Trans. Software Eng.

123

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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.

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Section: Developers' Work Practicesmentioning

confidence: 99%

Section: Ko Et Al Observed Software Developers To Determine Whatmentioning

confidence: 99%

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

Meyer

Barton

Murphy

et al. 2017

IIEEE Trans. Software Eng.

123

View full text Add to dashboard Cite

show abstract

“…Predominantly, each of these approaches focuses on supporting one specific activity during the work on a change task to determine relevant information without adapting to the various activities the developer is performing over the course of the change task. With the wide variety of developer activities during a change task [2], [4] and change tasks lasting anywhere from a few minutes to several days [5], finding the right approach and the relevant information as well as switching to it is difficult at best [6], [7]. The more we know about developers' activities during change tasks, the better we can support them in their work.…”

Section: Introductionmentioning

confidence: 99%

Towards Activity-Aware Tool Support for Change Tasks

Kevic

Fritz

2017

2017 IEEE International Conference on Software Maintenance and Evolution (ICSME)

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Abstract-To complete a change task, software developers perform a number of activities, such as locating and editing the relevant code. While there is a variety of approaches to support developers for change tasks, these approaches mainly focus on a single activity each. Given the wide variety of activities during a change task, a developer has to keep track of and switch between the different approaches. By knowing more about a developer's activities and in particular by knowing when she is working on which activity, we would be able to provide better and more tailored tool support, thereby reducing developer effort.In our research we investigate the characteristics of these activities, whether they can be identified, and whether we can use this additional information to improve developer support for change tasks. We conducted two exploratory studies with a total of 21 software developers collecting data on activities in the lab and field. An empirical analysis of the data shows, amongst other results, that activities comprise a consistently small amount of code elements across all developers and tasks (approx. 8.7 elements). Further analysis of the data shows, that we can automatically detect the boundaries and types of activities, and that the information on activity types can be used to improve the identification of relevant code elements.

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“…Another aspect to consider when looking at the impact of software maintenance concerns the time needed to understand systems by developers. Several studies estimate program comprehension to take more than half the time spent on maintenance [ZSG79,MML15]. These two factors combined together highlight that getting an understanding of systems impacts for 30 to 50% of the overall costs [FH82].…”

Section: A Genesis Of Rssesmentioning

confidence: 99%

“…A deeper exploration of the developer interaction, in particular in the IDE might be beneficial for the recommendation engine in general. For example, Minelli et al [MML15] track events in the IDE, identifying when the developer enters the "understanding" phase or navigate the code. Such information can be leveraged to refine the informational context of the developer (on the IDE side), and select the best moment when to fire a notification.…”

Section: Leveraging Developers Interactionmentioning

confidence: 99%

Holistic recommender systems for software engineering

Ponzanelli

2014

Companion Proceedings of the 36th International Conference on Software Engineering

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I Know What You Did Last Summer - An Investigation of How Developers Spend Their Time

Cited by 143 publications

References 28 publications

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

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

Towards Activity-Aware Tool Support for Change Tasks

Holistic recommender systems for software engineering

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