How Maintainability Issues of Android Apps Evolve [ICSME 2018]
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The document analyzes the evolution of maintainability issues in Android applications, focusing on the types and frequencies of these issues as well as the development activities that contribute to them. It identifies duplication and unit size as the most common issues, and notes that the density of issues changes over time, influenced by developer activities. The research uses a dataset of GitHub repositories and employs a software analysis toolkit to characterize the maintainability of these applications.
![VRIJE
UNIVERSITEIT
AMSTERDAM
Extracted maintainability issues
Software Analysis Toolkit
Developed by SIG
7
SAT tool
Maintainability issue Description
Unit size Methods exceeding 30 lines of code
Unit complexity Methods whose McCabe Cyclomatic Complexity exceeds 10
Unit interfacing Methods having more than 4 formal parameters
Module coupling Classes exceeding 20 incoming dependencies
Duplication Code clones of at least 6 lines of code
Maintainability The total count of the previous issue types
1. Fully automatic
2. No need to build the apps
3. Close contact with SAT developers
4. Its supported metrics are correlated with the
speed at which issues are solved by developers[1]
Why SAT
[1] Bijlsma, D., Ferreira, M. A., Luijten, B., & Visser, J. (2012). Faster issue resolution with
higher technical quality of software. Software quality journal, 20(2), 265-285.](https://image.slidesharecdn.com/icsme2018-180928081558/85/How-Maintainability-Issues-of-Android-Apps-Evolve-ICSME-2018-7-320.jpg)
![VRIJE
UNIVERSITEIT
AMSTERDAM
Developers’ activities (RQ3)
14
Which are the most recurrent types of maintainability issues in Android apps?
How does the density of Android maintainability issues evolve over time?
What are the development activities in which maintainability hotspots occur?
RQ1
RQ2
RQ3
0
10
20
30
40
Weeks
Maintainability(MT)
0
10
20
30
40
Weeks
Maintainability(MT)
App time series
Identify
hotspots
0
10
20
30
40
Weeks
Maintainability(MT)
Hotspots do not occur often in the app lifetime
(max: 8), average of ~1 hotspot per app
Content
analysis
sessions
Taxonomy of Android
developers activities [1]
Hotspots occur independently of the type of
developer’s activities
2,112 commits
sampling
[1] Pascarella, Geiger, Palomba, Di Nucci, Malavolta, Bacchelli.
Self-Reported Activities of Android Developers. MOBILESoft 2018
3,374
Counts](https://image.slidesharecdn.com/icsme2018-180928081558/85/How-Maintainability-Issues-of-Android-Apps-Evolve-ICSME-2018-14-320.jpg)
![VRIJE
UNIVERSITEIT
AMSTERDAM
Conclusions
VRIJE
UNIVERSITEIT
AMSTERDAM
3
Why apps maintainability is important
High expectations
Continous feedback
Frequent updates
Continuous maintenance
VRIJE
UNIVERSITEIT
AMSTERDAM
Most recurrent maintainability issues (RQ1)
8
020406080100
MT US UC UI MC DP
Type of maintainability issue
Density
M
aintainability
(TO
TAL)
Unit size
Unit com
plexity
Unit interfacing
M
odule
coupling
Code
duplication
Density
of issues
#issues at commit c
NKLOC of the app after c
Average of 18 issues every 1k
LOCs
DUPLICATION and UNIT SIZE
are the most recurring issues
in Android apps
Is DUPLICATION really
an issue in Android?
VRIJE
UNIVERSITEIT
AMSTERDAM
Evolution trends by maintainability issue type
(RQ2)
12
DP
MC
UI
UC
US
MT
I SI IP PI D SD DP PD H V A C
10
20
30
40
Maintainability
Unit size
Unit complexity
Unit interfacing
Module coupling
Code duplication
Growth Reduction Mixed Constant
Increasing
plateau
Hill
Mainly a growth in time
• with recurrent plateau
Are developers resolving unit
interfacing and duplication issues?
Maintainability issues
rarely decrease!
VRIJE
UNIVERSITEIT
AMSTERDAM
Developers’ activities (RQ3)
14
0
10
20
30
40
Weeks
Maintainability(MT)
0
10
20
30
40
Weeks
Maintainability(MT)
App time series
Identify
hotspots
0
10
20
30
40
Weeks
Maintainability(MT)
Hotspots do not occur often in the app lifetime
(max: 8), average of >1 hotspot per app
Content
analysis
sessions
Taxonomy of Android
developers activities [1]
Hotspots occur independently of the type of
developer’s activities
2,112 commits
sampling
[1] Pascarella, Geiger, Palomba, Di Nucci, Malavolta, Bacchelli.
Self-Reported Activities of Android Developers. MOBILESoft 2018
Replication package
https://github.com/S2-group/ICSME2018ReplicationPackage](https://image.slidesharecdn.com/icsme2018-180928081558/85/How-Maintainability-Issues-of-Android-Apps-Evolve-ICSME-2018-15-320.jpg)
How Maintainability Issues of Android Apps Evolve [ICSME 2018]
- 1. How Maintainability Issues of Android Apps Evolve Ivano Malavolta - Vrije Universiteit Amsterdam Roberto Verdecchia - Vrije Universiteit Amsterdam | Gran Sasso Science Institute Bojan Filipovic – Vrije Universiteit Amsterdam Magiel Bruntink – Software Improvement Group - Amsterdam Patricia Lago – Vrije Universiteit Amsterdam VRIJE UNIVERSITEIT AMSTERDAM
- 2. VRIJE UNIVERSITEIT AMSTERDAM Android 2 3.3 million Android apps available on the Google Play store >1k apps published everyday >1.5 billion apps downloaded every month
- 3. VRIJE UNIVERSITEIT AMSTERDAM 3 Why apps maintainability is important High expectations Continous feedback Frequent updates Continuous maintenance
- 4. VRIJE UNIVERSITEIT AMSTERDAM Goal and research questions 4 To empirically characterize how maintainability issues of Android apps evolve Which are the most recurrent types of maintainability issues in Android apps? How does the density of Android maintainability issues evolve over time? What are the development activities in which maintainability hotspots occur? RQ1 RQ2 RQ3
- 5. VRIJE UNIVERSITEIT AMSTERDAM Building the dataset 5 Union App published in Google Play? 9,400 Remove duplicates Has manifest? Has proper Android source code? Active GitHub repo? Remove impurities Enough commits frequency? 8,049 6,619 6,454 4,756 2,238 1,410 GitHub repos (434) Commits metadata (106,689) Collect commits metadata • Kotlin code • Missing Java code • Android libraries • #commits >= 6 • lifespan >= 8 weeks • changed dates • forks • not analyzable • Keep weeks with at least 1 commit • #weeks >= 8
- 6. VRIJE UNIVERSITEIT AMSTERDAM Data extraction 6 GitHub repos (434) Clone all repositories Locally-cloned repos Identify snapshots Maintainability issues Weekly snapshots (9,945) Run static analysis For each snapshot SAT tool Checkout at last commit
- 7. VRIJE UNIVERSITEIT AMSTERDAM Extracted maintainability issues Software Analysis Toolkit Developed by SIG 7 SAT tool Maintainability issue Description Unit size Methods exceeding 30 lines of code Unit complexity Methods whose McCabe Cyclomatic Complexity exceeds 10 Unit interfacing Methods having more than 4 formal parameters Module coupling Classes exceeding 20 incoming dependencies Duplication Code clones of at least 6 lines of code Maintainability The total count of the previous issue types 1. Fully automatic 2. No need to build the apps 3. Close contact with SAT developers 4. Its supported metrics are correlated with the speed at which issues are solved by developers[1] Why SAT [1] Bijlsma, D., Ferreira, M. A., Luijten, B., & Visser, J. (2012). Faster issue resolution with higher technical quality of software. Software quality journal, 20(2), 265-285.
- 8. VRIJE UNIVERSITEIT AMSTERDAM Most recurrent maintainability issues (RQ1) 8 Which are the most recurrent types of maintainability issues in Android apps? How does the density of Android maintainability issues evolve over time? What are the development activities in which maintainability hotspots occur? RQ1 RQ2 RQ3 020406080100 MT US UC UI MC DP Type of maintainability issue Density M aintainability (TO TAL) Unit size Unit com plexity Unit interfacing M odule coupling Code duplication Density of issues #issues at commit c NKLOC of the app after c Average of 18 issues every 1k LOCs DUPLICATION and UNIT SIZE are the most recurring issues in Android apps Is DUPLICATION really an issue in Android?
- 9. VRIJE UNIVERSITEIT AMSTERDAM How do maintainability issues evolve? (RQ2) 9 Which are the most recurrent types of maintainability issues in Android apps? How does the density of Android maintainability issues evolve over time? What are the development activities in which maintainability hotspots occur? RQ1 RQ2 RQ3 Does the density of maintainability issues actually change over time? Weekly snapshots 1 time series for each pair <app, issue type> Check stationarity NON-stationarity for 93% of the apps Android developers’ activities can impact the maintainability of their apps over time Weeks Density
- 10. VRIJE UNIVERSITEIT AMSTERDAM Evolution trends identification (RQ2) 10 Which are the most recurrent types of maintainability issues in Android apps? How does the density of Android maintainability issues evolve over time? What are the development activities in which maintainability hotspots occur? RQ1 RQ2 RQ3 Time series Seasonal Trend Remainder 1,230 distinct trends Open card sorting Taxonomy of 12 evolution trends sampling ADCPU−16Emu (I) AttysScope (SI) SGit (IP) AndroidBootcampProject (PI) BitcoinChecker (D) Ursmu (SD) BirdWalk (DP) MLManager (PD) CineTime (H) RadyoMenemenPro (V) PixelDungRemix (A) android−simple−gameapi (C) Increase Stable increase Increasing plateau Plateau increasing Decrease Stable decrease Decreasing plateau Plateau decreasing Hill Valley Anomalous Constant Growth ReductionMixed Constant Weeks Density Weeks
- 11. VRIJE UNIVERSITEIT AMSTERDAM The taxonomy of evolution trends (RQ2) Which are the most recurrent types of maintainability issues in Android apps? How does the density of Android maintainability issues evolve over time? What are the development activities in which maintainability hotspots occur? RQ1 RQ2 RQ3 ADCPU−16Emu (I) AttysScope (SI) SGit (IP) AndroidBootcampProject (PI) BitcoinChecker (D) Ursmu (SD) BirdWalk (DP) MLManager (PD) CineTime (H) RadyoMenemenPro (V) PixelDungRemix (A) android−simple−gameapi (C) Increase Stable increase Increasing plateau Plateau increasing Decrease Stable decrease Decreasing plateau Plateau decreasing Hill Valley Anomalous Constant Growth MixedReduction Constant
- 12. VRIJE UNIVERSITEIT AMSTERDAM Evolution trends by maintainability issue type (RQ2) 12 Which are the most recurrent types of maintainability issues in Android apps? How does the density of Android maintainability issues evolve over time? What are the development activities in which maintainability hotspots occur? RQ1 RQ2 RQ3 DP MC UI UC US MT I SI IP PI D SD DP PD H V A C 10 20 30 40 Maintainability Unit size Unit complexity Unit interfacing Module coupling Code duplication Growth Reduction Mixed Constant Increasing plateau Hill Mainly a growth in time • with recurrent plateau Counts Increase Stable increase Plateau increasing Decreasing plateau Decrease Stable decrease Plateau decreasing Valley M ix Constant Are developers resolving unit interfacing and duplication issues? SGit (IP) CineTime (H)
- 13. VRIJE UNIVERSITEIT AMSTERDAM Developers’ activities (RQ3) 13 Which are the most recurrent types of maintainability issues in Android apps? How does the density of Android maintainability issues evolve over time? What are the development activities in which maintainability hotspots occur? RQ1 RQ2 RQ3 0 10 20 30 40 Weeks Maintainability(MT)Maintainabilityissuesdensity Weeks Maintainability hotspots
- 14. VRIJE UNIVERSITEIT AMSTERDAM Developers’ activities (RQ3) 14 Which are the most recurrent types of maintainability issues in Android apps? How does the density of Android maintainability issues evolve over time? What are the development activities in which maintainability hotspots occur? RQ1 RQ2 RQ3 0 10 20 30 40 Weeks Maintainability(MT) 0 10 20 30 40 Weeks Maintainability(MT) App time series Identify hotspots 0 10 20 30 40 Weeks Maintainability(MT) Hotspots do not occur often in the app lifetime (max: 8), average of ~1 hotspot per app Content analysis sessions Taxonomy of Android developers activities [1] Hotspots occur independently of the type of developer’s activities 2,112 commits sampling [1] Pascarella, Geiger, Palomba, Di Nucci, Malavolta, Bacchelli. Self-Reported Activities of Android Developers. MOBILESoft 2018 3,374 Counts
- 15. VRIJE UNIVERSITEIT AMSTERDAM Conclusions VRIJE UNIVERSITEIT AMSTERDAM 3 Why apps maintainability is important High expectations Continous feedback Frequent updates Continuous maintenance VRIJE UNIVERSITEIT AMSTERDAM Most recurrent maintainability issues (RQ1) 8 020406080100 MT US UC UI MC DP Type of maintainability issue Density M aintainability (TO TAL) Unit size Unit com plexity Unit interfacing M odule coupling Code duplication Density of issues #issues at commit c NKLOC of the app after c Average of 18 issues every 1k LOCs DUPLICATION and UNIT SIZE are the most recurring issues in Android apps Is DUPLICATION really an issue in Android? VRIJE UNIVERSITEIT AMSTERDAM Evolution trends by maintainability issue type (RQ2) 12 DP MC UI UC US MT I SI IP PI D SD DP PD H V A C 10 20 30 40 Maintainability Unit size Unit complexity Unit interfacing Module coupling Code duplication Growth Reduction Mixed Constant Increasing plateau Hill Mainly a growth in time • with recurrent plateau Are developers resolving unit interfacing and duplication issues? Maintainability issues rarely decrease! VRIJE UNIVERSITEIT AMSTERDAM Developers’ activities (RQ3) 14 0 10 20 30 40 Weeks Maintainability(MT) 0 10 20 30 40 Weeks Maintainability(MT) App time series Identify hotspots 0 10 20 30 40 Weeks Maintainability(MT) Hotspots do not occur often in the app lifetime (max: 8), average of >1 hotspot per app Content analysis sessions Taxonomy of Android developers activities [1] Hotspots occur independently of the type of developer’s activities 2,112 commits sampling [1] Pascarella, Geiger, Palomba, Di Nucci, Malavolta, Bacchelli. Self-Reported Activities of Android Developers. MOBILESoft 2018 Replication package https://github.com/S2-group/ICSME2018ReplicationPackage
- 17. VRIJE UNIVERSITEIT AMSTERDAM Demographics 17 10 20 50 100 200 500 1000 2000 Number of commits per app 1 2 5 10 20 50 100 200 Number of commits per snapshot 1 2 5 10 20 50 100 Number of unique contributors per app 10 20 50 100 200 Number of snapshots per app 2008 2009 2011 2012 2013 2014 2015 2016 Development start date per app
- 19. VRIJE UNIVERSITEIT AMSTERDAM SAT processing time and resources 19 Average execution time = 8.73s per snapshot Total processing time = ~12 days LOCs processed = ~800 million Checked-out resources = ~7 terabytes