Mobile Apps quality - a tale about energy, performance, and users’ perception

Ivano Malavolta
VRIJE
UNIVERSITEIT
AMSTERDAM
VRIJE
UNIVERSITEIT
AMSTERDAM
Ivano Malavolta
Assistant professor
Vrije Universiteit Amsterdam
Mobile Apps quality -
a tale about energy,
performance,
and users’ perception

Ivano Malavolta
VRIJE
UNIVERSITEIT
AMSTERDAM
iOS developer
Who’s speaking?
2009
Android developer2010
Cross-platform developer2011
Instructor on mobile apps development
for 5 years2012
VRIJE
UNIVERSITEIT
AMSTERDAM
2014
2016
Experiments at the
GREEN LAB
Empirical research on hybrid apps
2017

Ivano Malavolta
VRIJE
UNIVERSITEIT
AMSTERDAM
The Green Lab
Our platform for researching
on software
– energy efficiency
– performance
Students measure
real software solutions
OpenSTF
+ ADB
Serve
web pages
VMWare
manager
SSH
MEASURES
Wifi
network
Router
Experiment
orchestrator
OpenSTF
Web
interface
Power
meters
A PLATFORM
A COURSE

Ivano Malavolta
VRIJE
UNIVERSITEIT
AMSTERDAM
Roadmap
Questions
Deep dive into mobile apps development
Who is speaking?
Energy consumption (of progressive web apps)
User perceptions (of hybrid apps)
Performance (of native apps)

Ivano Malavolta
VRIJE
UNIVERSITEIT
AMSTERDAM
Deep dive into mobile apps development
Ivano Malavolta (2016). Web-based hybrid mobile apps: state of the practice and research opportunities. In
Proceedings of the International Conference on Mobile Software Engineering and Systems, MOBILESoft '16
Ivano Malavolta (2016). Beyond Native Apps: Web Technologies to the Rescue! (Keynote). In Proceedings of the
1st International Workshop on Mobile Development (Mobile!)

Ivano Malavolta
VRIJE
UNIVERSITEIT
AMSTERDAM
Let’s burst the first myth
http://www.slideshare.net/fling/native-v-hybrid-v-web
Mobile apps development IS NOT CHEAP

Ivano Malavolta
VRIJE
UNIVERSITEIT
AMSTERDAM
NATIVE
APP
01010101010101101010
1010101011011010
010101010101011101
010101010101011010
PLATFORM APIs
Native
Development strategies

Ivano Malavolta
VRIJE
UNIVERSITEIT
AMSTERDAM
• rich user interfaces and heavy graphics
• work offline
• visibility via stores
• slow iteration pace for iOS (stores mediation)
• no indexing by search engines
• and.....
PROS
CONS
Native apps
NATIVE
APP
01010101010101101010
1010101011011010
010101010101011101
010101010101011010
PLATFORM APIs

Ivano Malavolta
VRIJE
UNIVERSITEIT
AMSTERDAM
Fragmentation
Obj-C
code
Swift
code
XCode
Java
code
C++
code
Eclipse
C#
code
C++
code
Visual Studio
JS
code

Ivano Malavolta
VRIJE
UNIVERSITEIT
AMSTERDAM
NATIVE
APP
01010101010101101010
1010101011011010
010101010101011101
010101010101011010
PLATFORM APIs
Native
BROWSER
<html>
<head>
<script src=” ...” />
</head>
<body>
...
Web

Ivano Malavolta
VRIJE
UNIVERSITEIT
AMSTERDAM
• fast development
• simple maintenance and updates
• cross-platform
• 2-steps access
– they are launched via a browser
• do not work offline
• no background activities
– geofencing
• poor access to system APIs
– push notifications, contacts, etc.
Web apps
PROS
CONS

Ivano Malavolta
VRIJE
UNIVERSITEIT
AMSTERDAM
BROWSER
<html>
<head>
</head>
<body>
...
NATIVE
WRAPPER
<html>
<head>
</head>
<body>
...
PLATFORM APIs
NATIVE
APP
01010101010101101010
1010101011011010
010101010101011101
010101010101011010
PLATFORM APIs
Native Web
Hybrid

Ivano Malavolta
VRIJE
UNIVERSITEIT
AMSTERDAM
Web-based hybrid mobile apps
Single code
base
Bridge API

Ivano Malavolta
VRIJE
UNIVERSITEIT
AMSTERDAM
Web-based hybrid apps
• cross-platform portability
• reuse of existing knowledge of web
developers
• simpler and less expensive development
process
• inherit some cons of native apps
• restricted access to system APIs
• (slight) decrease in performance
PROS
CONS

Ivano Malavolta
VRIJE
UNIVERSITEIT
AMSTERDAM
BROWSER
<html>
<head>
</head>
<body>
...
NATIVE
WRAPPER
<html>
<head>
</head>
<body>
...
PLATFORM APIs
NATIVE
APP
01010101010101101010
1010101011011010
010101010101011101
010101010101011010
PLATFORM APIs
Native Web
Hybrid
Progressive
BROWSER
<html>
<head>
</head>
<body>
...
Service
workers

Ivano Malavolta
VRIJE
UNIVERSITEIT
AMSTERDAM
The journey of a PWA
1. The user accesses the website as
usual
https://goo.gl/KIZydg

Ivano Malavolta
VRIJE
UNIVERSITEIT
AMSTERDAM
usual
2. After the 3rd-4th visit, the website
asks to be installed

Ivano Malavolta
VRIJE
UNIVERSITEIT
AMSTERDAM
usual
3. The user can decide to add the app
to the home screen

Ivano Malavolta
VRIJE
UNIVERSITEIT
AMSTERDAM
usual
3. The user can decide to add the app
to the home screen
4. From now on, the app is top-level,
full-screen, and can receive push
notifications

Ivano Malavolta
VRIJE
UNIVERSITEIT
AMSTERDAM
Components of a PWA
HTTPS
Web
Manifest
Service
workers
{
"name": "MyApplication",
"short_name": "MyApp",
"scope": "./webApp/",
"orientation": "portrait",
"display": "fullscreen",
"background_color": "#fff",
"description": "A simple application for testing.",
"icons": [{
"src": "images/touch/homescreen48.png",
"sizes": "48x48",
"type": "image/png"
}, ...
}],
...
}

Ivano Malavolta
VRIJE
UNIVERSITEIT
AMSTERDAM
Service workers
Implemented in JavaScript
Multithreading
→ runs in a separate thread w.r.t.
the main thread
Used for:
• push notifications
• background operations
• content caching
– offline functionality

Ivano Malavolta
VRIJE
UNIVERSITEIT
AMSTERDAM
Offline-first experience
Web App
Service
worker
response
response
request
Backend
Offline cache
this.addEventListener('fetch', function(event) {
event.respondWith(
caches.match(event.request).then(function(response) {
return response || fetch(event.request);
});
);
});

Ivano Malavolta
VRIJE
UNIVERSITEIT
AMSTERDAM
Energy consumption
(of progressive web apps)
Ivano Malavolta, Giuseppe Procaccianti, Paul Noorland, Petar Vukmirovic. Assessing the Impact of Service
Workers on the Energy Efficiency of Progressive Web Apps. In Proceedings of the International
Conference on Mobile Software Engineering and Systems, MOBILESoft 2017,

Ivano Malavolta
VRIJE
UNIVERSITEIT
AMSTERDAM
PWAs have been advertised as:
• performance boosters
• network savers
• providers of better UX
However…
How does the use of service workers impact the
energy efficiency of PWAs under different network
conditions?
How does the use of service workers impact the
energy efficiency of PWAs?RQ1
RQ2

Ivano Malavolta
VRIJE
UNIVERSITEIT
AMSTERDAM
PWAs selection
• Real PWAs from the pwa.rocks1 repository
• Pseudo-random selection
– no toy examples
– data-driven PWAs (aka no videogames)
1 https://pwa.rocks
Name Category Total
size
SW size
(loc)
Ali Express Shopping 2.1Mb 69
Google I/O 2016 Events 4.2Mb 358
The Washington Post News 4.0Mb 85
Flipkart Shopping 3.8Mb 907
Babe News News 1.2Mb 156
Wiki offline Knowledge 800Kb 1009
The Billings Gazette News 2.1Mb 60

Ivano Malavolta
VRIJE
UNIVERSITEIT
AMSTERDAM
Experiment design
What we measure
Energy consumption of the device in Joules
Variable name Treatments
SW status <on, off>
Android device <high-end, low-end>
Network condition <2G, WiFi>
What we control
What we measure

Ivano Malavolta
VRIJE
UNIVERSITEIT
AMSTERDAM
Experiment design
• full 2x2x2 factorial à all possible combinations of
treatments
• 8 combinations x 7 PWAs x 8 runs
à
• each run executes a typical usage
scenario (10-15 gestures)
448 runs
SW status Device Network
on low-end 2G
on low-end WiFi
on high-end 2G
on high-end WiFi
off low-end 2G
off low-end WiFi
off high-end 2G
off high-end WiFi

Ivano Malavolta
VRIJE
UNIVERSITEIT
AMSTERDAM
7a. HTTP
requests as part
of the scenario
Mobile device
Server
Measurement infrastructure
Orchestration
script
Monkey
runner
Trepn
profiler
Chrome
Monkeyrunner
1. HTTP requests
impersonating phone
2. HTTP responses (recorded)
9. save
collected
data
3. Start experiment run
5. start 6. start
7b. HTTP
responses
(possibly altered)
8. collect data
Fiddler
proxy
Hosted
PWA
ADB
OS
4. start
scenario
run

Ivano Malavolta
VRIJE
UNIVERSITEIT
AMSTERDAM
Results - devices
Overall energy consumption across devices
Low-end High-end
High difference across devices

Ivano Malavolta
VRIJE
UNIVERSITEIT
AMSTERDAM
Results: SW-on VS SW-off
Low-end High-end
Smaller difference in the high-end device
Service workers DO NOT influence the energy
consumption of a PWA running on a mobile device

Ivano Malavolta
VRIJE
UNIVERSITEIT
AMSTERDAM
Results – network conditions
High-end
+ 2G
Low-end
+ 2G
Low-end
+
WiFi
High-end
+
WiFi
PWAs consume less energy on WiFi
Same device + same network condition à low impact of SWs

Ivano Malavolta
VRIJE
UNIVERSITEIT
AMSTERDAM
PWA-specific trends
Low-end
2G
WiFi
High-end
Different PWAs
à different
impact of SWs
Same PWA
à SWs have a
different impact
under different
conditions
- - - - + + +
+
-
+

Ivano Malavolta
VRIJE
UNIVERSITEIT
AMSTERDAM
How does each SW look like?

Ivano Malavolta
VRIJE
UNIVERSITEIT
AMSTERDAM
Results of manual review
No specific trend here
Name Listened
events
Caching Obfuscation/
minification
Complexity
Ali Express P, N ✓ ✓ 12
Google I/O 2016 I, A, F, M ✓ 9
The Washington Post I, A, P, N ✓ 131
Flipkart I, A, F ✓ ✓ 5
Babe News I, A, F, P, N ✓ 16
Wiki offline I, A, F, S, M, N ✓ ✓ 7
The Billings Gazette I, A, F ✓ 194

Ivano Malavolta
VRIJE
UNIVERSITEIT
AMSTERDAM
Conclusions
Ivano Malavolta
VRIJE
UNIVERSITEIT
AMSTERDAM
PWAs have been advertised as:
• performance boosters
• network savers
• providers of better UX
However…
Ivano Malavolta
VRIJE
UNIVERSITEIT
AMSTERDAM
7a. HTTP
requests as part
of the scenario
Mobile device
Server
Orchestration
script
Monkey
runner
Trepn
profiler
Chrome
Monkeyrunner
1. HTTP requests
impersonating phone
9. save
collected
data
5. start 6. start
7b. HTTP
responses
(possibly altered)
8. collect data
Fiddler
proxy
Hosted
PWA
ADB
OS
4. start
scenario
run
Ivano Malavolta
VRIJE
UNIVERSITEIT
AMSTERDAM
Results: SW-on VS SW-off
Low-end High-end
Smaller difference in the high-end device
Service workers DO NOT influence the energy
consumption of a PWA running on a mobile device

Ivano Malavolta
VRIJE
UNIVERSITEIT
AMSTERDAM
Performance
(of native apps)
Teerath Das, Massimiliano Di Penta, Ivano Malavolta. A Quantitative and Qualitative Investigation of
Performance-Related Commits in Android Apps. In 2016 IEEE International Conference on Software
Maintenance and Evolution (ICSME 2016)

Ivano Malavolta
VRIJE
UNIVERSITEIT
AMSTERDAM
Goal
Quantitative and qualitative characterization of
(documented) performance-related commits
for Android apps
Developer
?
App

Ivano Malavolta
VRIJE
UNIVERSITEIT
AMSTERDAM
Research questions
What are the concerns that developers have when
dealing with performance issues of Android apps?
To what extent developers consider performance
issues of Android apps?RQ1
RQ2

Ivano Malavolta
VRIJE
UNIVERSITEIT
AMSTERDAM
Dataset?

Ivano Malavolta
VRIJE
UNIVERSITEIT
AMSTERDAM
Dataset

Ivano Malavolta
VRIJE
UNIVERSITEIT
AMSTERDAM
How to identify performance-related commits?

Ivano Malavolta
VRIJE
UNIVERSITEIT
AMSTERDAM
Results (RQ1)
Out of 68,025 commits of 2,443 apps, we discovered a
total of 457 performance-related commits (0.67%) spread
across 180 apps

Ivano Malavolta
VRIJE
UNIVERSITEIT
AMSTERDAM
Open card sorting
– 2 people performed the task, a third one checked the results
1st phase
commits tagged based on keywords
e.g., read from file system, swipe lag
2nd phase
commits clustered into meaningful,
labeled groups

Ivano Malavolta
VRIJE
UNIVERSITEIT
AMSTERDAM
Results (RQ2)

Ivano Malavolta
VRIJE
UNIVERSITEIT
AMSTERDAM
User interface
• Applied solutions:
– use of Android’s recycled views instead of plain list views
– render images in slices
– ...
Problems related to swipe lags, screen layout drawing, lists
scrolling responsiveness
FIX layouts for better rendering performance

Ivano Malavolta
VRIJE
UNIVERSITEIT
AMSTERDAM
Code smells
– use more efficient regular expressions
– avoid recurrent computations of constant data
– avoid usage of deprecated decryption algorithms
– ...
Symptoms of poor design and implementation choices
fixed string concatenation performance issue

Ivano Malavolta
VRIJE
UNIVERSITEIT
AMSTERDAM
Memory
– stopping auxiliary services when available memory gets low
– avoiding to load potentially unused data
– ...
Related to the memory footprint of the app
Fixed major memory leak;
should improve responsiveness on older devices

Ivano Malavolta
VRIJE
UNIVERSITEIT
AMSTERDAM
Local database access
– perform queries in an asynchronous task
– add indexes to specific fields
– ...
Access to local database can be highly inefficient
Added indexes for post.blogID to improve
performance of several lookups

Ivano Malavolta
VRIJE
UNIVERSITEIT
AMSTERDAM
As a developer I can exploit this emerging collective knowledge
for improving the performance of MY mobile app

Ivano Malavolta
VRIJE
UNIVERSITEIT
AMSTERDAM
User perceptions
(of hybrid apps)
Ivano Malavolta, Stefano Ruberto, Tommaso Soru, Valerio Terragni. Hybrid Mobile Apps in the Google
Play Store: An Exploratory Investigation. 2nd ACM International Conference on Mobile Software
Engineering and Systems (MOBILESoft 2015).
Ivano Malavolta, Stefano Ruberto, Valerio Terragni, Tommaso Soru. End Users’ Perception of Hybrid
Mobile Apps in the Google Play Store. IEEE International Conference on Mobile Services (MS 2015).

Ivano Malavolta
VRIJE
UNIVERSITEIT
AMSTERDAM
Pros
• cross-platform portability
• reuse of existing knowledge of
web developers
• simpler and less expensive
development processes
Hybrid mobile apps
Cons
• restricted access to hardware
features
• decrease in performance
• variations on user experience
As of today, limited empirical investigations
have been performed on hybrid mobile apps
Strong debate about benefits and drawbacks

Ivano Malavolta
VRIJE
UNIVERSITEIT
AMSTERDAM
Research goal
Developer
End users
creates
download
& use
App
What is the difference between hybrid and
native mobile apps as perceived by end users?
Are hybrid mobile apps published in the Google Play
Store? What are their main traits?S1
S2

Ivano Malavolta
VRIJE
UNIVERSITEIT
AMSTERDAM
Data extraction
Classified apps
(hybrid vs native)
Hybrid apps
classifier*
top-500 most popular free apps for
each category of the Google Play
Store
~11k app binaries
Apps and
reviews
mining
* analysis tool available here:
http://github.com/GabMar/ApkCategoryChecker

Ivano Malavolta
VRIJE
UNIVERSITEIT
AMSTERDAM
Results
Data-
intensive
mobile apps[2]
Apps with closer interaction
with the Android platform
Winners, in line with
informal claims[3,4,5]

Ivano Malavolta
VRIJE
UNIVERSITEIT
AMSTERDAM
Quick test

Ivano Malavolta
VRIJE
UNIVERSITEIT
AMSTERDAM
Data extraction
Classified apps
(hybrid vs native)
Hybrid apps
classifier*
Reviews
analyzer
each category of the Google Play
Store
~11k app binaries
50 pages (~255) of
reviews for each app
~3M user
reviews
apps scores
Apps and
reviews
mining
perceived value: 0.5
users sentiment: 0.6
#reviews: 243
performance: 0.6
bugginess: 0.1
size: 3,456 kb* analysis tool available here:
http://github.com/GabMar/ApkCategoryChecker

Ivano Malavolta
VRIJE
UNIVERSITEIT
AMSTERDAM
Reviews analysis
Stopwords
removal
manually performed
by 2 domain experts
Single review
Single review
score
polaritypos: 0.8 performancepos: 0.6
polarityneg: 0.1 performanceneg: 0.05
bugginess: 0.2
300 random
reviews
Keywords
extraction
Relevant keywords
Lemmatization
Tf-idf based
vectors similarity
computation

Ivano Malavolta
VRIJE
UNIVERSITEIT
AMSTERDAM
Perceived value
Average of the ratings as provided by end users
3.35 3.75
Rating = real number in [1, 5]
Certain balance, with neglectable differences

Ivano Malavolta
VRIJE
UNIVERSITEIT
AMSTERDAM
Perceived value
Polarity of sentiment of end users
where posa = #positive reviews
nega = #negative reviews
Balance between hybrid and
native apps, with some exceptions
Non data-intensive or
requiring multimedia capabilities

Ivano Malavolta
VRIJE
UNIVERSITEIT
AMSTERDAM
Perceived value
Average review count
where Ra ∈ ℕ
Native apps have been reviewed in average 6.5
times more than hybrid mobile apps
Possible interpretation:
hybrid mobile apps are neither perceived as too
satisfying nor dissatisfying w.r.t. native ones

Ivano Malavolta
VRIJE
UNIVERSITEIT
AMSTERDAM
Perceived performance
where posa = #positive reviews w.r.t. performance of the app
nega = #negative reviews w.r.t. performance of the app
Balance between hybrid and native apps,
with some exceptions

Ivano Malavolta
VRIJE
UNIVERSITEIT
AMSTERDAM
Perceived bugginess
where buga = #reviews signalling the presence of bugs or failures
reviewsa = #reviews of the app
The highest unbalance between the two
development strategies in our study
bugginessa = buga / reviewsa
Possible interpretation:
absence of full-fledged testing frameworks for hybrid
apps, such as those provided by native apps IDEs like
Eclipse and Android Studio

Ivano Malavolta
VRIJE
UNIVERSITEIT
AMSTERDAM
Results – initial download size
6,586 kb4,625 kb
In line with the average size of
Android apps
sizea = file size in kilobytes of the app APK file

Ivano Malavolta
VRIJE
UNIVERSITEIT
AMSTERDAM
Data extraction
Classiﬁed apps
(hybrid vs native)
Hybrid apps
classifiers
Reviews
analyzer
each category of the Google Play Store
~11k app binaries
50 pages (~255) of
reviews for each app
~3M app
reviews
apps scores
Apps and
reviews
mining
perceived value: 0.5
users sentiment: 0.6
#reviews: 243
performance: 0.6
bugginess: 0.1
size: 3,456 kb
Apache Cordova (258) and Appcelerator Titanium (116)
Developers reuse JavaScript frameworks for the desktop web
End users value hybrid and native apps similarly
Hybrid may be good for data-intensive apps, whereas it performs poorly when
dealing with low-level, platform-specific features
Reviews analysis
Stopwords
removal
manually performed
by 2 domain experts
Single review
Single review
score
polaritypos
: 0.8 performancepos
: 0.6
polarityneg
: 0.1 performanceneg
: 0.05
bugginess: 0.2
300 random
reviews
Keywords
extraction
Relevant keywords
Lemmatization
Tf-idf based
vectors similarity
computation

Ivano Malavolta
VRIJE
UNIVERSITEIT
AMSTERDAM
Wrap up

Ivano Malavolta
VRIJE
UNIVERSITEIT
AMSTERDAM
Ivano Malavolta
VRIJE
UNIVERSITEIT
AMSTERDAM
7a. HTTP
requests as part
of the scenario
Mobile device
Server
Orchestration
script
Monkey
runner
Trepn
profiler
Chrome
Monkeyrunner
1. HTTP requests
impersonating phone
9. save
collected
data
5. start 6. start
7b. HTTP
responses
(possibly altered)
8. collect data
Fiddler
proxy
Hosted
PWA
ADB
OS
4. start
scenario
run
Ivano Malavolta
VRIJE
UNIVERSITEIT
AMSTERDAM
Reviews analysis
Stopwords
removal
manually performed
by 2 domain experts
Single review
Single review
score
polaritypos: 0.8 performancepos: 0.6
polarityneg: 0.1 performanceneg: 0.05
bugginess: 0.2
300 random
reviews
Keywords
extraction
Relevant keywords
Lemmatization
Tf-idf based
vectors similarity
computation
Ivano Malavolta
VRIJE
UNIVERSITEIT
AMSTERDAM
Open card sorting
– 2 people performed the task, a third one checked the results
1st phase
commits tagged based on keywords
e.g., read from file system, swipe lag
2nd phase
commits clustered into meaningful,
labeled groups
Ivano Malavolta
VRIJE
UNIVERSITEIT
AMSTERDAM
BROWSER
<html>
<head>
</head>
<body>
...
NATIVE
WRAPPER
<html>
<head>
</head>
<body>
...
PLATFORM APIs
NATIVE
APP
01010101010101101010
1010101011011010
010101010101011101
010101010101011010
PLATFORM APIs
Native Web
Hybrid
Progressive
BROWSER
<html>
<head>
</head>
<body>
...
Service
workers

Ivano Malavolta
VRIJE
UNIVERSITEIT
AMSTERDAM
Contact
Ivano Malavolta |
Vrije Universiteit Amsterdam
iivanoo
i.malavolta@vu.nl
www.ivanomalavolta.com
A few of the contents of this presentation are from co-authors’ slides

Mobile Apps quality - a tale about energy, performance, and users’ perception

Recommended

Recommended

More Related Content

Viewers also liked

Viewers also liked (12)

Similar to Mobile Apps quality - a tale about energy, performance, and users’ perception

Similar to Mobile Apps quality - a tale about energy, performance, and users’ perception (20)

More from Ivano Malavolta

More from Ivano Malavolta (20)

Recently uploaded

Recently uploaded (20)

Mobile Apps quality - a tale about energy, performance, and users’ perception