SAMOA – A Visual Software Analytics Platform for Mobile Applications [ICSM2013]

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We present Samoa, a visual web-based software analytics platform for mobile applications. It mines software repositories of apps and uses a set of visualization techniques to present the mined data. We describe Samoa, detail the analyses it supports, and describe a methodology to understand apps from a structural and historical perspective.

Education Technology Business

A Visual Software Analytics Platform
for Mobile Applications
MOA AS
Roberto Minelli and Michele Lanza
REVEAL @ Faculty of Informatics – University of Lugano, Switzerland

Software
Analytics
Mobile
Applications
for

Software
Analytics
Mobile
Applications
for
Explore and analyze
the data to obtain
insightful information
about software systems,
users, and software
development process.

Software
Analytics
Explore and analyze
the data to obtain
insightful information
about software systems,
users, and software
development process.
Mobile
Applications
Software systems
aimed at smartphones,
tablet PCs, and other
handheld devices
for

The world of apps is
heterogeneous
Programming
Languages
AppStores

$4.5 billions
in 2009
$17.5 billionsin 2012
$25 billionsin 2015

Software systems
aimed at smartphones,
tablet PCs, and other
handheld devices
Mobile
Applications
Apps evolve
Maintenance
is crucial

Existing approaches were devised
before apps existed

oftware nalytics
for bile pplicationsMO
A
A
S
R. Minelli and M. Lanza
“Soware Analytics for Mobile Applications
Insights & Lessons Learned” CSMR 2013

Delta with largest snapshot in history
Number of
external calls
Number of
internal calls
The whole app (in terms of LOC)
The CORELOC Other LOC
Activity Main Activity
Default
Main Activity
Service
Phantom
Element
Core Circle Colors
Call Ring Colors
Android calls Java calls
JavaX calls Apache calls
Unclassiﬁed
calls
All other calls
The White Ring
The App Circle
The Core Circle
The Call Ring
The History Circle

Violating guidelines
“[...] an application usually consists of multiple
activities that are loosely bound to each other.
Typically, one activity in an application is speciﬁed
as the "main" activity, which is presented to the user
when launching the application for the ﬁrst time”.
In case of multiple main activities, developers have
to specify in the manifest a default Activity.

Core Circle Colors
Activity
Main Activity
Service
Phantom element
Default Main Activity
Violating guidelines

Use of third-party APIs
Java project
Source
code

...
- 2.3
kLOC
+ 7 kLOC
Use of third-party APIs

Software
Analytics
Mobile
Applications
for
Software systems
aimed at smartphones,
tablet PCs, and other
handheld devices
Mobile
Applications
Maintenance
is crucial
Apps evolve
Insights &
Lessons Learned
R. Minelli and M. Lanza
“Soware Analytics for Mobile Applications –
Insights & Lessons Learned” CSMR 2013
MOA AS
http://samoa.inf.usi.ch

FRONT-ENDBACK-END
SVN
SVN
SVN
SVN
Data acquisition
Java SVN
crawler
Source code model extraction
MSE generatorAST generator
MSE parserAST parser
Metrics extraction
AST-based
metrics
MSE-based
metrics
JSON
Files
SAMOA
d3.jsJSON retrieval
HTML/CSS
JavaScript/
jQuery/PHP
Internet

Mobile applications, known as apps, are software systems running on handheld devices, such as smartphones and tablet PCs. The market of apps has rapidly expanded in the past few years into a multi-billion dollar business. Being a new phenomenon, it is unclear whether approaches to maintain and comprehend traditional software systems can be ported to the context of apps. We present a novel approach to comprehend apps from a structural and historical perspective, leveraging three factors for the analysis: source code, usage of third-party APIs, and historical data. We implemented our approach in a web-based software analytics platform named SAMOA. We detail our approach and the supporting tool, and present a number of findings obtained while investigating a corpus of mobile applications. Our findings reveal that apps differ significantly from traditional software systems in a number of ways, which calls for the development of novel approaches to maintain and comprehend them.

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Modeling the power profile of mobile applications is a crucial activity to identify the causes behind energy leaks. To this aim, researchers have proposed hardware-based tools as well as model-based and software-based techniques to approximate the actual energy profile. However, all these solutions present their own advantages and disadvantages. Hardware-based tools are highly precise, but at the same time their use is bound to the acquisition of costly hardware components. Model-based tools require the calibration of parameters needed to correctly create a model on a specific hardware device. Software-based approaches do not need any hardware components, but they rely on battery measurements and, thus, they are hardware-assisted. These tools are cheaper and easier to use than hardware-based tools, but they are believed to be less precise. In this paper, we take a deeper look at the pros and cons of software-based solutions investigating to what extent their measurements depart from hardware-based solutions. To this aim, we propose a software- based tool named PETrA that we compare with the hardware- based Monsoon toolkit on 54 Android apps. The results show that PETrA performs similarly to M ONSOON despite not using any sophisticated hardware components. In fact, in all the apps the mean relative error with respect to M ONSOON is lower than 0.05. Moreover, for 95% of the analyzed methods the estimation error is within 5% of the actual values measured using the hardware-based toolkit.

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As part of their daily work, developers interact with Integrated Development Environments (IDE), generating thousands of events. Together with other aspects of development, this data also captures the modus operandi of the developer, including all the program entities she interacted with during a development session. This "working set" (or context) is leveraged by developers to create and maintain their mental model of the software system at hand. Understanding how developers navigate and interact with source code during a development session is an open question. We present a novel visual approach to understand how working sets evolve during a development session. The visualization incrementally depicts all the program entities involved in a development session, the intensity of the developer activity on them, and the navigation paths that occurred between them. We visualized about a thousand development sessions, and categorized them according to their visual properties.

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Integrated Development Environments (IDEs) lack effective support to browse complex relationships between source code elements. As a result, developers are often forced to exploit multiple user interface components at the same time, bringing the IDE into a complex, "chaotic" state. Keeping track of these relationships demands increased source code navigation and cognitive load, leading to productivity deficits documented in observational studies. Beyond small-scale studies, the amount and nature of the chaos experienced by developers in the wild is unclear, and more importantly it is unclear how to tame it. Based on a dataset of fine-grained interaction data, we propose several metrics to characterize and quantify the ``level of chaos'' of an IDE. Our results suggest that developers spend, on average, more than 30\% of their time in a chaotic environment, and that this may affect their productivity. To support developers, we devise and evaluate simple strategies that automatically alter the UI of the IDE. We find that even simple strategies may considerably reduce the level of chaos both in terms of effective space occupancy and time spent in a chaotic environment.

Walls, Pillars and Beams: A 3D Decomposition of Quality Anomalies (vissoft2016)

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Quality rules are used to capture important implementation and design decisions embedded in a software system’s architecture. They can automatically analyze software and assign quality grades to its components. To provide a meaningful evaluation of quality, rules have to stay up-to-date with the continuously evolving system that they describe. However one would encounter unexpected anomalies during a historical overview because the notion of quality is always changing, while the qualitative evolution analysis requires it to remain constant. To understand the anomalies in a quality history of a real-world software system we use an immersive visualization that lays out the quality fluctuations in three dimensions based on two co-evolving properties: quality rules and source code. This helps us to identify and separate the impact caused by the changes of each property, and allows us to detect significant mistakes that happened during the development process.

In this paper, The mobile application field has been receiving astronomical attention from the past few years due to the growing number of mobile app downloads and withal due to the revenues being engendered .With the surge in the number of apps, the number of lamentable apps/failing apps has withal been growing.Interesting mobile app statistics are included in this paper which might avail the developers understand the concerns and merits of mobile apps.The authors have made an effort to integrate all the crucial factors that cause apps to fail which include negligence by the developers, technical issues, inadequate marketing efforts, and high prospects of the users/consumers.The paper provides suggestions to eschew failure of apps. As per the various surveys, the number of lamentable/failing apps is growing enormously, primarily because mobile app developers are not adopting a standard development life cycle for the development of apps. In this paper, we have developed a mobile application with the aid of traditional software development life cycle phases (Requirements, Design, Develop, Test, and, Maintenance) and we have used UML, M-UML, and mobile application development technologies.

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Slides used for my PhD dissertation defense (13 November 2017). Thesis: “Interaction-Aware Development Environments enable novel and in-depth analyses of the behavior of software developers and set the ground to provide developers with effective and actionable support for their activities inside the IDE.” — Roberto Minelli, 2017 Abstract: Nowadays, software development is largely carried out using Integrated Development Environments, or IDEs. An IDE is a collection of tools and facilities to support the most diverse software engineering activities, such as writing code, debugging, and program comprehension. The fact that they are integrated enables developers to find all the tools needed for the development in the same place. Each activity is composed of many basic events, such as clicking on a menu item in the IDE, opening a new user interface to browse the source code of a method, or adding a new statement in the body of a method. While working, developers generate thousands of these interactions, that we call fine-grained IDE interaction data. In essence, this data captures the behavior of developers inside the IDE, but it is largely neglected by modern development environments. We believe that this data is a valuable source of information that can be leveraged to enable retrospective analyses and to offer novel support to developers. In this dissertation we propose the concept of "Interaction-Aware Development Environments": IDEs that collect, mine, and leverage the interactions of developers to support and simplify their workflow. We formulate our thesis as follows: Interaction-Aware Development Environments enable novel and in-depth analyses of the behavior of software developers and set the ground to provide developers with effective and actionable support for their activities inside the IDE. For example, by monitoring how developers navigate source code, the IDE could suggest the program entities that are potentially relevant for a particular task. Our research focuses on three main directions: 1. Modeling and Persisting Interaction Data. 2. Interpreting Interaction Data. 3. Supporting Developers with Interaction Data. Dissertation Committee: – Prof. Michele Lanza, Università della Svizzera italiana, Switzerland (Research Advisor) – Dr. Andrea Mocci, Università della Svizzera italiana, Switzerland (Research Co-Advisor) – Prof. Matthias Hauswirth, Università della Svizzera italiana, Switzerland (Internal Member) – Prof. Cesare Pautasso, Università della Svizzera italiana, Switzerland (Internal Member) – Prof. Serge Demeyer, University of Antwerp, Belgium (External Member) – Prof. Radu Marinescu, University of Timisoara, Romania (External Member)

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Letter from the Congress of the United States regarding Anti-Semitism sent June 3rd to MIT President Sally Kornbluth, MIT Corp Chair, Mark Gorenberg Dear Dr. Kornbluth and Mr. Gorenberg, The US House of Representatives is deeply concerned by ongoing and pervasive acts of antisemitic harassment and intimidation at the Massachusetts Institute of Technology (MIT). Failing to act decisively to ensure a safe learning environment for all students would be a grave dereliction of your responsibilities as President of MIT and Chair of the MIT Corporation. This Congress will not stand idly by and allow an environment hostile to Jewish students to persist. The House believes that your institution is in violation of Title VI of the Civil Rights Act, and the inability or unwillingness to rectify this violation through action requires accountability. Postsecondary education is a unique opportunity for students to learn and have their ideas and beliefs challenged. However, universities receiving hundreds of millions of federal funds annually have denied students that opportunity and have been hijacked to become venues for the promotion of terrorism, antisemitic harassment and intimidation, unlawful encampments, and in some cases, assaults and riots. The House of Representatives will not countenance the use of federal funds to indoctrinate students into hateful, antisemitic, anti-American supporters of terrorism. Investigations into campus antisemitism by the Committee on Education and the Workforce and the Committee on Ways and Means have been expanded into a Congress-wide probe across all relevant jurisdictions to address this national crisis. The undersigned Committees will conduct oversight into the use of federal funds at MIT and its learning environment under authorities granted to each Committee. • The Committee on Education and the Workforce has been investigating your institution since December 7, 2023. The Committee has broad jurisdiction over postsecondary education, including its compliance with Title VI of the Civil Rights Act, campus safety concerns over disruptions to the learning environment, and the awarding of federal student aid under the Higher Education Act. • The Committee on Oversight and Accountability is investigating the sources of funding and other support flowing to groups espousing pro-Hamas propaganda and engaged in antisemitic harassment and intimidation of students. The Committee on Oversight and Accountability is the principal oversight committee of the US House of Representatives and has broad authority to investigate “any matter” at “any time” under House Rule X. • The Committee on Ways and Means has been investigating several universities since November 15, 2023, when the Committee held a hearing entitled From Ivory Towers to Dark Corners: Investigating the Nexus Between Antisemitism, Tax-Exempt Universities, and Terror Financing. The Committee followed the hearing with letters to those institutions on January 10, 202

The simplified electron and muon model, Oscillating Spacetime: The Foundation...

RitikBhardwaj56

Discover the Simplified Electron and Muon Model: A New Wave-Based Approach to Understanding Particles delves into a groundbreaking theory that presents electrons and muons as rotating soliton waves within oscillating spacetime. Geared towards students, researchers, and science buffs, this book breaks down complex ideas into simple explanations. It covers topics such as electron waves, temporal dynamics, and the implications of this model on particle physics. With clear illustrations and easy-to-follow explanations, readers will gain a new outlook on the universe's fundamental nature.

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SAMOA – A Visual Software Analytics Platform for Mobile Applications [ICSM2013]

1. A Visual Software Analytics Platform for Mobile Applications MOA AS Roberto Minelli and Michele Lanza REVEAL @ Faculty of Informatics – University of Lugano, Switzerland

2. Software Analytics Mobile Applications for

3. Software Analytics Mobile Applications for Explore and analyze the data to obtain insightful information about software systems, users, and software development process.

4. Software Analytics Explore and analyze the data to obtain insightful information about software systems, users, and software development process. Mobile Applications Software systems aimed at smartphones, tablet PCs, and other handheld devices for

5. The world of apps is heterogeneous Programming Languages AppStores

7. $4.5 billions in 2009 $17.5 billionsin 2012 $25 billionsin 2015

8. Software systems aimed at smartphones, tablet PCs, and other handheld devices Mobile Applications Apps evolve Maintenance is crucial

9. Existing approaches were devised before apps existed

10. oftware nalytics for bile pplicationsMO A A S R. Minelli and M. Lanza “Soware Analytics for Mobile Applications Insights & Lessons Learned” CSMR 2013

11. MOA AS http://samoa.inf.usi.ch DEMO

12. Delta with largest snapshot in history Number of external calls Number of internal calls The whole app (in terms of LOC) The CORELOC Other LOC Activity Main Activity Default Main Activity Service Phantom Element Core Circle Colors Call Ring Colors Android calls Java calls JavaX calls Apache calls Unclassiﬁed calls All other calls The White Ring The App Circle The Core Circle The Call Ring The History Circle

13. Insights & Lessons Learned

14. Violating guidelines “[...] an application usually consists of multiple activities that are loosely bound to each other. Typically, one activity in an application is speciﬁed as the "main" activity, which is presented to the user when launching the application for the ﬁrst time”. In case of multiple main activities, developers have to specify in the manifest a default Activity.

15. Core Circle Colors Activity Main Activity Service Phantom element Default Main Activity Violating guidelines

16. Use of third-party APIs Java project Source code

17. Use of third-party APIs Java project Source code

18. Use of third-party APIs Java project Source code

19. ... - 2.3 kLOC + 7 kLOC Use of third-party APIs

20. Software Analytics Mobile Applications for Software systems aimed at smartphones, tablet PCs, and other handheld devices Mobile Applications Maintenance is crucial Apps evolve Insights & Lessons Learned R. Minelli and M. Lanza “Soware Analytics for Mobile Applications – Insights & Lessons Learned” CSMR 2013 MOA AS http://samoa.inf.usi.ch

21. FRONT-ENDBACK-END SVN SVN SVN SVN Data acquisition Java SVN crawler Source code model extraction MSE generatorAST generator MSE parserAST parser Metrics extraction AST-based metrics MSE-based metrics JSON Files SAMOA d3.jsJSON retrieval HTML/CSS JavaScript/ jQuery/PHP Internet

SAMOA – A Visual Software Analytics Platform for Mobile Applications [ICSM2013]

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