Why is Tim wearing such a jaded look this

morning ?

What is he staring

at ?1

Deluge of Notifications for

Work-Item Updates !!

Deluge of Notifications for

Work-Item Updates !!

Mostly Useless

2

Which Work-Item Updates Need Your

Response?The 10th Working Conference on Mining Software Repositories

Which Work-Item Updates Need Your

Response?The 10th Working Conference on Mining Software Repositories

Debdoot Mukherjee, IBM Re s e a rch - Ind iaMalika Garg, Ind ia n Ins titute o f Te chno lo g y - De lhi

Why this problem

?

Why this problem

?How

severe ?How

severe ?Solution

IdeaSolution

IdeaHow

effective ?How

effective ?Talk Outline :

3

Only a fraction of the subscribedwork-items are of primary concern. Input is only sparingly necessary in the rest

10 Working Spheres

People receive MANY MORE notifications compared to the number of their own updates …

1 Out of 5 Notifications

require a response

Leads more severely impacted

than Individual

Contributors

4

Project Manager “Up da te s fro m m y c lie nt re q uire urg e nt re s p o ns e s . . . … . re s t a re m o s tly FYI ite m s . ”

Which notifications are perceived as important?

Developer“Us ua lly , I o nly re a d no tific a tio ns fro m the wo rk-ite m s tha t I o wn. Fo r o the rs , I ne e d to p a y a tte ntio n o nly if m y na m e is m e ntio ne d . ”

Architect“I a m re s p o ns ible fo r re v ie wing c o d e c o m m its m a d e by the te a m , s o I ke e p a n e y e o n up da te s tha t ha ve linke d cha ng e -s e ts .”

5

6

Predict whether a user shall respond to a notification by

learning from users’ responses to similar past

notifications

Notifications that do not demand any response but are important since they improve awareness are NOT in

scope.7

8

Creating Notification Examples

9

Labeling Notification Examples

Label a notification example generated for a user as Re s p o ns e -Re q d , if (s)he updates the work-item s o o n after receiving the notification and before others update it. Otherwise, the example is labeled as No -Re s p o ns e -Re q d .

10

Model Training Considerations

11

Efficacy of different types of classifiers Naïve Bayes, Decision Trees, Support Vector Machines

Notifications keep streaming in – which window to use as training set ? Avert this question by use of incremental classifiers

Distribution of many features may change drastically with the churn in software projects Use of adaptive classifiers to combat project dynamics Ensemble classifiers to deal with evolving data

Empirical Evaluation: Summary

12

13