Big Data. Big Decisions
InformationWeek
Special Coverage Series


Tips For Writing Multiplatform Mobile Apps

Write once, run anywhere is the dream. Cross-platform tools can help, but problems remain.

InformationWeek Green - Jul. 11, 2011
InformationWeek Green
Download the entire July 2012 InformationWeek supplement on Mobile Appplication Development, distributed in an all-digital format as part of our Green Initiative
(Registration required.)

Threats Vs. Readiness

As smartphone and tablet use skyrockets, companies are developing mobile applications for customers and end users. Sixty-four percent of respondents to InformationWeek's 2011 Mobile Device Management and Security Survey say they're developing or planning to develop business apps.

More Insights

Webcasts

More >>

White Papers

More >>

Reports

More >>

If your company is considering creating its own mobile apps, you must understand the development landscape. The platform you target, be it Android, BlackBerry, iOS, or Windows, has a preferred language. If you want to write an app that will run on multiple platforms, you can either write it in each platform's preferred language or use a third-party tool to generate code for different platforms. This second approach can save time and effort, though it may affect usability.

To help you determine your best approach, we'll examine development tools offered by Apple, Google, Microsoft, and Research In Motion, as well as at two popular cross-platform tools: Air and PhoneGap.

The Test Environment

I used four smartphones to test the development tools: Motorola Droid running Android 2.3.5, Apple's iPhone version 4.2.1, Windows Phone version 7.5, and BlackBerry Bold version 7. I also looked at the BlackBerry PlayBook version 1 tablet. In general, the devices offer a similar user experience. The real distinctions are on the developer side; when it comes to writing applications native to each platform, the differences are stark.

The four mobile platforms offer virtual devices that let developers write and debug programs without the actual mobile hardware. The virtual devices run on a developer's PC, emulate the mobile hardware, and execute the mobile environment. The developer interacts with the virtual device via the keyboard and mouse.

Because all four platforms contain a built-in browser, they support applications that use Web standards. Instead of accessing the app from a Web server, the Web files (HTML/JavaScript/CSS) are packaged for the device and executed in a browser container on the device. A number of third-party tools such as PhoneGap take advantage of this feature by creating a common JavaScript API with platform-specific code underneath, giving programmers access to multiple platforms with a single code base.

Android provides developers with the most freedom to choose an OS on which to develop applications. Developers can use Windows, Mac, or Linux. BlackBerry users can choose between Mac or Windows, and a Linux option is on the way. If you want to develop for iOS or Windows devices, your only option is Mac and Windows, respectively. Let's take a look at each platform's development tools.

To read the rest of the article,
Download InformationWeek's July supplement on mobile application development.

Our full report on mobile app development is free with registration.

This report includes 16 pages of action-oriented analysis. What you'll find:
  • A breakdown of development environments for the major mobility platforms
  • Insight on cross-platform tools and secure coding
Get This And All Our Reports




Related Reading




Currently we allow the following HTML tags in comments:

Single tags

These tags can be used alone and don't need an ending tag.

<br> Defines a single line break

<hr> Defines a horizontal line

Matching tags

These require an ending tag - e.g. <i>italic text</i>

<a> Defines an anchor

<b> Defines bold text

<big> Defines big text

<blockquote> Defines a long quotation

<caption> Defines a table caption

<cite> Defines a citation

<code> Defines computer code text

<em> Defines emphasized text

<fieldset> Defines a border around elements in a form

<h1> This is heading 1

<h2> This is heading 2

<h3> This is heading 3

<h4> This is heading 4

<h5> This is heading 5

<h6> This is heading 6

<i> Defines italic text

<p> Defines a paragraph

<pre> Defines preformatted text

<q> Defines a short quotation

<samp> Defines sample computer code text

<small> Defines small text

<span> Defines a section in a document

<s> Defines strikethrough text

<strike> Defines strikethrough text

<strong> Defines strong text

<sub> Defines subscripted text

<sup> Defines superscripted text

<u> Defines underlined text

BYTE encourages readers to engage in spirited, healthy debate, including taking us to task. However, BYTE moderates all comments posted to our site, and reserves the right to modify or remove any content that it determines to be derogatory, offensive, inflammatory, vulgar, irrelevant/off-topic, racist or obvious marketing/SPAM. BYTE further reserves the right to disable the profile of any commenter participating in said activities.

Disqus Tips To upload an avatar photo, first complete your Disqus profile. | View the list of supported HTML tags you can use to style comments. | Please read our commenting policy.

Follow InformationWeek

By The Numbers

What Are Your Primary Concerns About Using Big Data Software?

Base: 417 respondents at organizations using or planning to deploy data analytics, BI or statistical analysis software
Data: InformationWeek 2013 Analytics, Business Intelligence and Information Management Survey of 541 business technology professionals, October 2012

What Do You Think?

What's your attitude about SQL analysis on top of Hadoop?
We want fast, standard SQL analysis capabilities on Hadoop ASAP
Hadoop is for unstructured data; SQL is for relational databases
We'll give SQL on Hadoop a try, but relational DBs will remain the mainstay
Given strong SQL support on Hadoop, we'd nix the data warehouse
We're not interested in Hadoop
No opinion



Related Content

From Our Sponsor

Five Big Data Challenges and How to Overcome Them with Visual Analytics

Five Big Data Challenges and How to Overcome Them with Visual Analytics

Business leaders often need a visual snapshot of data to quickly grasp and use it. This paper identifies five challenges in presenting data and how visual analytics can resolve them. Solutions are suggested to overcome the challenges of: speed, data clarity, data quality, displaying meaningful results, and dealing with outliers.

Game-Changing Analytics: How IT Executives Can Use Analytics to Create Innovation and Business Success

Game-Changing Analytics: How IT Executives Can Use Analytics to Create Innovation and Business Success

Today's competitive advantage requires a deeper understanding of your business, your market and your customers. As an IT executive, you can drive that knowledge transformation. In this white paper, learn how to make decisions as a strategic business leader and three steps to begin an analytics initiative within your enterprise.

Data Visualization Techniques: From Basics to Big Data with SAS Visual Analytics

Data Visualization Techniques: From Basics to Big Data with SAS Visual Analytics

High-performance data visualization turns sophisticated analyses into meaningful graphics, leading to faster and smarter decision making. In this white paper, learn how visual analytics can transform big data, with additional features such as real-time functionality, mobile compatibility, robust applications for technical groups and accessibility for nontechnical users.

Big Data: Lessons from the Leaders

Big Data: Lessons from the Leaders

Financial performance, competitive advantage, operational efficiency, strategic decision making - every business goal can extract value from big data, and the time for doubt or inaction has long passed. In this Economist Intelligence Unit report, in-depth interviews with data pioneers reveal the link between the effective use of big data and the bottom line among other results.

Decision-Driven Data Management: A Strategy for Better Decisions with Better Data

Decision-Driven Data Management: A Strategy for Better Decisions with Better Data

Which came first, the data or the decision? This white paper makes the case for having a decision in mind, then tailoring big data's volume, variety and velocity to achieve business results such as overcoming customer dissatisfaction or creating well-informed strategies in real time.

Informationweek Reports

Research: The Big Data Management Challenge

Research: The Big Data Management Challenge

The challenge of big data is real, but most organizations don't differentiate 'big data' from traditional data, and nearly 90% of respondents to our survey use conventional databases as the primary means of handling data. We'll help you understand what constitutes big data (it's not just size) and the numerous management challenges it poses.