Causal Impact Analysis for App Releases in Google Play

This is a complementary web page for the FSE'16 paper entitled "Causal Impact Analysis for App Releases in Google Play", providing access to the supplementary reports, tool and data.
If you find resources on this web page useful, we encourage you to cite our work: @inproceedings{martin16fse, author = {William Martin and Sarro, Federica and Harman, Mark}, title = {Causal Impact Analysis for App Releases in Google Play}, booktitle = {Proceedings of the 24th ACM SIGSOFT International Symposium on the Foundations of Software Engineering}, series = {FSE '16}, year = {2016}, location = {Seattle, WA}, numpages = {12}, note = {To appear.} }

Tool

The tool is available here.

Tool Data Specifications

The format for target files is:
line: targetID(integer),priorStartWeek(count from 1),releaseWeek(start of posterior),posteriorEndWeek,[comma separated list of floats for the vector]
Each target goes on a new line.
Download the sample target file here: targets.csv

The format for control files is:
line: [comma separated list of floats - week 1 for each control]
line: [comma separated list of floats - week 2 for each control]
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V
Each control spans every line; each week goes on a new line.
Download the sample controls file here: controls.csv

Both samples are available in this zip: ciraSamples.zip

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Questionnaire

The following questionnaire was sent to developers who expressed an interest in receiving a report on their significant release.

Answering these questions will take only 12 keystrokes, including 6 return key presses.
However, if you want to elaborate on your answer, please do feel free to do so in free text.
We are very interested to hear your views on whether this research could be useful to you.

1. Did you find the time series report useful? 0 - no, 1 - yes

2. Would you be interested in further time series reports on your app(s)? 0 - no, 1 - yes

3. Do you agree that the release impacted your app's performance? 0 - no, 1 - yes

4. Are you aware of any external influences, such as advertising campaigns, that could have led to the observed effect? 0 - no, 1 - yes

5. Would you be interested in learning about potential contributing factors to significant releases? 0 - no, 1 - yes

6. Would you make any changes to your app releasing strategy based on these findings? 0 - no, 1 - yes

Data

To request a copy of the time-series google app data used in the FSE study, please fill the following form.

Name:

E-mail:

Affiliation:


Additional Topic Results

Read the results from our additional runs using 10, 20, 50, 200, 500 and 1000 topics in this report: FSE16_Topics.pdf

Contact

w.martin (at) ucl.ac.uk