Essential Applications and Usage: Exploring Mozilla Firefox Features
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This report provides a comprehensive analysis of Mozilla Firefox, covering its essential applications and usage. It begins by examining Firefox's affordances, particularly its user experience across different platforms, making it suitable for businesses like Westfield Corporation. The report then delves into filter bubbles, explaining their impact and how Firefox attempts to mitigate them. It explores the browser's monetization strategies, including revenue sources and market share. The open-source nature of Firefox is discussed, highlighting contributions from developers and the various skills involved. The report also details the algorithms used by Firefox, such as the Gecko layout engine and Quantum, and the server-side TLS configuration. Finally, it examines the open data practices of the Mozilla Firefox team, explaining how user activity, behavior, and hardware configurations are collected and shared for empowerment and transparency. The report concludes with a list of references used throughout the analysis.

Running head: ESSENTIAL APPLICATIONS AND USAGE
Essential Applications and Usage
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Essential Applications and Usage
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1ESSENTIAL APPLICATIONS AND USAGE
Table of Contents
Affordances................................................................................................................................2
Filter bubbles..............................................................................................................................2
Monetization..............................................................................................................................3
Open Source...............................................................................................................................4
Algorithms..................................................................................................................................5
Open Data...................................................................................................................................5
References..................................................................................................................................7
Table of Contents
Affordances................................................................................................................................2
Filter bubbles..............................................................................................................................2
Monetization..............................................................................................................................3
Open Source...............................................................................................................................4
Algorithms..................................................................................................................................5
Open Data...................................................................................................................................5
References..................................................................................................................................7

2ESSENTIAL APPLICATIONS AND USAGE
Affordances
The designers of Mozilla Firefox have always looked at browsing from tablet specific
usage scenarios and therefore the overall UX and UI provided through Mozilla Firefox can
easily be compatible and easy to use through desktops as well as smartphones (Pandya &
Andrei, 2017). They ensure that switching to other tabs adding a new one or managing
existing ones can be done fluidly across all platforms. This has enabled the developers to
easily carve out a tablet specific variant of the Firefox efficiently without sacrificing any of
the features and services offered by the PC version. This thus makes the browser optimal
browsing application for an ecommerce specific business like Westfield Corporation. This is
because ecommerce businesses are also heavily reliant on smartphone and mobile devices
carried by many of their personnel. The simplicity of using Firefox in both PC and
smartphones while still being power packed with various features and solutions make the
application ensure quality, performance and reliability (Vikne, 2018). The Mozilla Firefox
browser is being continuously developed and being supported by the core group, idea
submitters, promoters and the end users too thus helping the browser get better with every
iteration (Frank, 2017). The developers follow four key values when going about creating or
upgrading the Mozilla Firefox browsing application. These are a) to keep it small, b) not to
keep too many cookies, c) patches to the application need not be equal and d) type of users of
the browser can vary. This is why, Westfield Corporation can rest assured all their needs
from a browsing application gets looked into and are being worked upon.
Filter bubbles
A filter bubble refers to the term introduced by Internet activist Eli Pariser and the
term is used to describe intellectual isolation which is bound to happen when applications like
try too much to offer a personalized environment (An, Castelluccio & Khomh, 2019). In the
Affordances
The designers of Mozilla Firefox have always looked at browsing from tablet specific
usage scenarios and therefore the overall UX and UI provided through Mozilla Firefox can
easily be compatible and easy to use through desktops as well as smartphones (Pandya &
Andrei, 2017). They ensure that switching to other tabs adding a new one or managing
existing ones can be done fluidly across all platforms. This has enabled the developers to
easily carve out a tablet specific variant of the Firefox efficiently without sacrificing any of
the features and services offered by the PC version. This thus makes the browser optimal
browsing application for an ecommerce specific business like Westfield Corporation. This is
because ecommerce businesses are also heavily reliant on smartphone and mobile devices
carried by many of their personnel. The simplicity of using Firefox in both PC and
smartphones while still being power packed with various features and solutions make the
application ensure quality, performance and reliability (Vikne, 2018). The Mozilla Firefox
browser is being continuously developed and being supported by the core group, idea
submitters, promoters and the end users too thus helping the browser get better with every
iteration (Frank, 2017). The developers follow four key values when going about creating or
upgrading the Mozilla Firefox browsing application. These are a) to keep it small, b) not to
keep too many cookies, c) patches to the application need not be equal and d) type of users of
the browser can vary. This is why, Westfield Corporation can rest assured all their needs
from a browsing application gets looked into and are being worked upon.
Filter bubbles
A filter bubble refers to the term introduced by Internet activist Eli Pariser and the
term is used to describe intellectual isolation which is bound to happen when applications like
try too much to offer a personalized environment (An, Castelluccio & Khomh, 2019). In the
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3ESSENTIAL APPLICATIONS AND USAGE
case of browsers, almost all browsers including Mozilla Firefox processes the search history
of the user and try showing interesting and previously visited websites in thumbnails, by
suggesting commonly used search keywords earlier browsed url when they should instead be
suggesting a neutral list of the best matches based on the letters typed in the address bar or
search boxes and try to show related pages and articles in thumbnails instead of ending up
showing the previously visited ones. Firefox despite being among the browsers that happens
to suffer from this issue, is coming forward to instead suggest the end user in ensuring ways
to avoid filter bubbles if that negatively affects them. This is a wise move as many other users
may like some of the recent history to persist in the thumbnails or suggestion of full
previously typed words with just one or two entered letters. Filter bubbles can especially
benefit companies like Westfield Corporation as they seem to perform similar activities
through common webpages on a regular basis. Still the measures that are suggested by
Firefox to avoid filter bubbles are i) knowing the digital neighbors, ii) maintaining a balanced
set of browsing activities with variation in type of content and iii) scrolling through different
feeds also.
Monetization
Most of the financial revenue that Mozilla, the organization responsible for building
and continuing the development of the web browsing application Firefox comes from the
partnership deals of various search engines as well as several distribution deals. To be exact,
94% of all the revenue generation made by Mozilla derives from the royalties the
organization receive for featuring all the different search engines on their web browser. Thee
revenue generation of Mozilla however have impacted heavily as just over decade ago the
browser dominated the market with more than 26% market share. But now, due to heavy
completion from browsers like Google Chrome and Apple Safari, the market share of Mozilla
Firefox has fallen to only 5% (Keizer, 2017). The different avenues of revenue generation
case of browsers, almost all browsers including Mozilla Firefox processes the search history
of the user and try showing interesting and previously visited websites in thumbnails, by
suggesting commonly used search keywords earlier browsed url when they should instead be
suggesting a neutral list of the best matches based on the letters typed in the address bar or
search boxes and try to show related pages and articles in thumbnails instead of ending up
showing the previously visited ones. Firefox despite being among the browsers that happens
to suffer from this issue, is coming forward to instead suggest the end user in ensuring ways
to avoid filter bubbles if that negatively affects them. This is a wise move as many other users
may like some of the recent history to persist in the thumbnails or suggestion of full
previously typed words with just one or two entered letters. Filter bubbles can especially
benefit companies like Westfield Corporation as they seem to perform similar activities
through common webpages on a regular basis. Still the measures that are suggested by
Firefox to avoid filter bubbles are i) knowing the digital neighbors, ii) maintaining a balanced
set of browsing activities with variation in type of content and iii) scrolling through different
feeds also.
Monetization
Most of the financial revenue that Mozilla, the organization responsible for building
and continuing the development of the web browsing application Firefox comes from the
partnership deals of various search engines as well as several distribution deals. To be exact,
94% of all the revenue generation made by Mozilla derives from the royalties the
organization receive for featuring all the different search engines on their web browser. Thee
revenue generation of Mozilla however have impacted heavily as just over decade ago the
browser dominated the market with more than 26% market share. But now, due to heavy
completion from browsers like Google Chrome and Apple Safari, the market share of Mozilla
Firefox has fallen to only 5% (Keizer, 2017). The different avenues of revenue generation
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4ESSENTIAL APPLICATIONS AND USAGE
that Mozilla now makes are from royalties, interest and dividend income, total realized and
unrealized gains and losses from investments, contributions, exchange of foreign currency,
sale of assets, assets released from restrictions and a few others. In the year of 2016 the total
unrestricted revenue and support amounted to $520,373 which was seen as an increase of
about $100,000 from that of the previous year that is 2015. Based on the philanthropic
programs and activities of Mozilla, they are also publicly supported through individual
donors and foundations which amount to near about the $14 million mark. Today in the
market of web browsers Firefox sits behind Google Chrome (60%), Safari (14.85%), UC
Browser (5.42%) but at 5.01% it manages to stay ahead of Opera (3.38%) and Internet
Explorer (2.85%).
Open Source
The Mozilla Firefox web browsing application is a free to use and open source
browser that has been developed by Mozilla. This began as an experiment by both the
Mozilla foundation and its subsidiary – the Mozilla Corporation through the hands of Blake
Ross, Dave Hyatt and Joe Hewitt. These individuals had the common belief that the
commercial requirements of sponsorship conducted by Netscape and the rich features
provided by their development will significantly compromise the utilization of the Mozilla
web browsing application being developed. To negate the problem they identified the
bloating features of the Mozilla Suite and created this standalone browser intending to
replace the services of the Mozilla Suite. Though the Firefox browser project underwent a
myriad of name changes, originally the browser was given the name – Phoenix. Mozilla
Firefox being an open source project is still obtaining contributions from individual
developers (JENSEN, 2018). The various set of skills with which these developers are
contributing to the continuous development of the browser are C, C++, JavaScript,
HTML/CSS, Kotlin, Swift, Python, Make, Shell, Perl and Rust. Developers with knowledge
that Mozilla now makes are from royalties, interest and dividend income, total realized and
unrealized gains and losses from investments, contributions, exchange of foreign currency,
sale of assets, assets released from restrictions and a few others. In the year of 2016 the total
unrestricted revenue and support amounted to $520,373 which was seen as an increase of
about $100,000 from that of the previous year that is 2015. Based on the philanthropic
programs and activities of Mozilla, they are also publicly supported through individual
donors and foundations which amount to near about the $14 million mark. Today in the
market of web browsers Firefox sits behind Google Chrome (60%), Safari (14.85%), UC
Browser (5.42%) but at 5.01% it manages to stay ahead of Opera (3.38%) and Internet
Explorer (2.85%).
Open Source
The Mozilla Firefox web browsing application is a free to use and open source
browser that has been developed by Mozilla. This began as an experiment by both the
Mozilla foundation and its subsidiary – the Mozilla Corporation through the hands of Blake
Ross, Dave Hyatt and Joe Hewitt. These individuals had the common belief that the
commercial requirements of sponsorship conducted by Netscape and the rich features
provided by their development will significantly compromise the utilization of the Mozilla
web browsing application being developed. To negate the problem they identified the
bloating features of the Mozilla Suite and created this standalone browser intending to
replace the services of the Mozilla Suite. Though the Firefox browser project underwent a
myriad of name changes, originally the browser was given the name – Phoenix. Mozilla
Firefox being an open source project is still obtaining contributions from individual
developers (JENSEN, 2018). The various set of skills with which these developers are
contributing to the continuous development of the browser are C, C++, JavaScript,
HTML/CSS, Kotlin, Swift, Python, Make, Shell, Perl and Rust. Developers with knowledge

5ESSENTIAL APPLICATIONS AND USAGE
in Java help with development of the browser for Android based platforms and the Firefox
for Fire TV project. Those with JavaScript or HTML/CSS knowledge help with the front end
development of Firefox. Swift developers help with development of Firefox for iOS
platforms. Python programmers help with web services that include Firefox Sync and Firefox
Accounts. C programmers can help with the NSS, Opus and Daala which corresponds to the
networking aspect and audio, video related codecs.
Algorithms
The web browser is using the gecko layout engine for the rendering of web pages and
is relied upon by the browser for implementing the currently anticipated standardizations of
web browsing. Since 2017, Firefox started to integrate a new technique, which they named
Quantum for promoting greater parallelism and a highly intuitive user interface (Bonnin,
2016). Other major algorithms used by Firefox are the URL Bar algorithm, frequency
algorithm and other sorting algorithms. The server side TLS configuration is followed by all
deployments of Firefox (Bhavaraju, Smith & Zhang, 2018). This helps the browser determine
how the different algorithms being used will be prioritized and ensure optimal compatibility.
Open Data
The Mozilla Firefox team collects public data reports of Firefox users on a weekly
basis and this consists of user activity, user behaviour and even hardware configuration of the
users (Rahman & Rigby, 2018). The main purposes behind sharing the data are
empowerment and transparency. By empowerment, Firefox seeks to provide the developers,
the journalists and thus the overall public in better understanding the present state of web
browsing, the recent trends and the direction towards which web browsing is headed (Mani,
Sankaran & Aralikatte, 2019). Through transparency Firefox wants to especially highlight
that they follow an open design and are focussed on open usage of the web. Therefore, the
in Java help with development of the browser for Android based platforms and the Firefox
for Fire TV project. Those with JavaScript or HTML/CSS knowledge help with the front end
development of Firefox. Swift developers help with development of Firefox for iOS
platforms. Python programmers help with web services that include Firefox Sync and Firefox
Accounts. C programmers can help with the NSS, Opus and Daala which corresponds to the
networking aspect and audio, video related codecs.
Algorithms
The web browser is using the gecko layout engine for the rendering of web pages and
is relied upon by the browser for implementing the currently anticipated standardizations of
web browsing. Since 2017, Firefox started to integrate a new technique, which they named
Quantum for promoting greater parallelism and a highly intuitive user interface (Bonnin,
2016). Other major algorithms used by Firefox are the URL Bar algorithm, frequency
algorithm and other sorting algorithms. The server side TLS configuration is followed by all
deployments of Firefox (Bhavaraju, Smith & Zhang, 2018). This helps the browser determine
how the different algorithms being used will be prioritized and ensure optimal compatibility.
Open Data
The Mozilla Firefox team collects public data reports of Firefox users on a weekly
basis and this consists of user activity, user behaviour and even hardware configuration of the
users (Rahman & Rigby, 2018). The main purposes behind sharing the data are
empowerment and transparency. By empowerment, Firefox seeks to provide the developers,
the journalists and thus the overall public in better understanding the present state of web
browsing, the recent trends and the direction towards which web browsing is headed (Mani,
Sankaran & Aralikatte, 2019). Through transparency Firefox wants to especially highlight
that they follow an open design and are focussed on open usage of the web. Therefore, the
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6ESSENTIAL APPLICATIONS AND USAGE
public data in general as well as insights needs to be made known for the benefit of everyone
involved. As already mentioned, the three key sections of the report are user activity, user
behaviour and hardware specifications of those browsing the web with Firefox. User activity
represent metrics of the overall user base, user behaviour on the other hand shows the ways in
which the Firefox web browser is getting used and hardware specifications represent the
system configuration of Firefox users. All of these data get derived from a sample consisting
of 10% of Firefox users which includes the full release, the beta version, the ESR variant as
also other channels of Firefox. This report covers the data worth evaluating usage of every
week unless specified otherwise.
public data in general as well as insights needs to be made known for the benefit of everyone
involved. As already mentioned, the three key sections of the report are user activity, user
behaviour and hardware specifications of those browsing the web with Firefox. User activity
represent metrics of the overall user base, user behaviour on the other hand shows the ways in
which the Firefox web browser is getting used and hardware specifications represent the
system configuration of Firefox users. All of these data get derived from a sample consisting
of 10% of Firefox users which includes the full release, the beta version, the ESR variant as
also other channels of Firefox. This report covers the data worth evaluating usage of every
week unless specified otherwise.
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7ESSENTIAL APPLICATIONS AND USAGE
References
An, L., Castelluccio, M., & Khomh, F. (2019). An empirical study of DLL injection bugs in
the Firefox ecosystem. Empirical Software Engineering, 24(4), 1799-1822.
Bhavaraju, S., Smith, T., & Zhang, B. (2018). Security Analysis of Firefox WebExtensions.
Bonnin, J. M. (2016). Firefox OS Ecosystem.
Frank, F. (2017). Activity of Core and Peripheral Developers: A Case Study on Mozilla
Firefox.
JENSEN, R. T. (2018, October). Revitalising Openness at Mozilla: A Mixed Method
Research Approach. In Ethnographic Praxis in Industry Conference
Proceedings (Vol. 2018, No. 1, pp. 518-536).
Keizer, G. (2017). FAQ: How Apple, Google, Microsoft and Mozilla will eliminate Adobe
Flash. ComputerWorld, July, 31.
Mani, S., Sankaran, A., & Aralikatte, R. (2019, January). Deeptriage: Exploring the
effectiveness of deep learning for bug triaging. In Proceedings of the ACM India
Joint International Conference on Data Science and Management of Data (pp. 171-
179).
Pandya, V., & Andrei, S. (2017). About the Design of QUIC Firefox Transport
Protocol. BRAIN. Broad Research in Artificial Intelligence and Neuroscience, 8(2),
26-32.
Rahman, M. T., & Rigby, P. C. (2018, October). The impact of failing, flaky, and high failure
tests on the number of crash reports associated with Firefox builds. In Proceedings of
References
An, L., Castelluccio, M., & Khomh, F. (2019). An empirical study of DLL injection bugs in
the Firefox ecosystem. Empirical Software Engineering, 24(4), 1799-1822.
Bhavaraju, S., Smith, T., & Zhang, B. (2018). Security Analysis of Firefox WebExtensions.
Bonnin, J. M. (2016). Firefox OS Ecosystem.
Frank, F. (2017). Activity of Core and Peripheral Developers: A Case Study on Mozilla
Firefox.
JENSEN, R. T. (2018, October). Revitalising Openness at Mozilla: A Mixed Method
Research Approach. In Ethnographic Praxis in Industry Conference
Proceedings (Vol. 2018, No. 1, pp. 518-536).
Keizer, G. (2017). FAQ: How Apple, Google, Microsoft and Mozilla will eliminate Adobe
Flash. ComputerWorld, July, 31.
Mani, S., Sankaran, A., & Aralikatte, R. (2019, January). Deeptriage: Exploring the
effectiveness of deep learning for bug triaging. In Proceedings of the ACM India
Joint International Conference on Data Science and Management of Data (pp. 171-
179).
Pandya, V., & Andrei, S. (2017). About the Design of QUIC Firefox Transport
Protocol. BRAIN. Broad Research in Artificial Intelligence and Neuroscience, 8(2),
26-32.
Rahman, M. T., & Rigby, P. C. (2018, October). The impact of failing, flaky, and high failure
tests on the number of crash reports associated with Firefox builds. In Proceedings of

8ESSENTIAL APPLICATIONS AND USAGE
the 2018 26th ACM Joint Meeting on European Software Engineering Conference
and Symposium on the Foundations of Software Engineering (pp. 857-862).
Vikne, A. S. (2018). Cross-Site Scripting Protection in Firefox. Creating a filter for Firefox
protecting against Reflected cross-site scripting attacks (Master's thesis, The
University of Bergen).
the 2018 26th ACM Joint Meeting on European Software Engineering Conference
and Symposium on the Foundations of Software Engineering (pp. 857-862).
Vikne, A. S. (2018). Cross-Site Scripting Protection in Firefox. Creating a filter for Firefox
protecting against Reflected cross-site scripting attacks (Master's thesis, The
University of Bergen).
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