You use Swift everyday to create great client apps, but have you ever wondered what can it do more for you? Swift Superpowers will provide you with small tips of great - and unconventional - use cases for Swift, from cross-platform network code to scripting, prototyping and more...

Often when users ask for some features, they don’t understand how long it takes to make them. When features are related to security, developers also often don’t understand how long it will take.

I will show the real case about implementing end-to-end encryption of users' notes for Bear application. I'll illustrate the process from the eyes of security engineer – starting with the security design scheme, selecting the proper encryption library, implementing the flow, and preparing for incidents. Now — think about it — cryptography is only chapter 3 in OWASP MASVS (8 chapters in general). Even the best cryptography will fail if basic security controls are badly implemented.

You use Swift everyday to create great client apps, but have you ever wondered what can it do more for you? Swift Superpowers will provide you with small tips of great - and unconventional - use cases for Swift, from cross-platform network code to scripting, prototyping and more...

There are lots of things around us that make our lives easier every day, but we never really think about how they work. How does a train make turns? How do fridges work? Why do we need specific adapters to charge our devices? How does sunscreen protect our skin? and so on. It’s a relief that we don’t need to know the answers to take advantage of those things! But wouldn’t it be fun to find out anyway? In this short talk, we’ll try to figure out how Pubgrub—the new dependency resolver of Swift Package Manager—resolves our dependencies and makes our lives easier.

Did you notice that, during the past two years, there has been in proportion much more CoreML talks in iOS conferences than mobile applications actually using CoreML ? Why is that ?

The thing is, banking or CRM or health mobile applications hardly need dog/cat image classifiers… AI in mobile apps is not really about training CoreML models.

Most of us iOS developers are front-end developers. Not data scientists. Yet, AI and machine learning can certainly help us build better applications. Not with computer vision ; but with UITextFields, serendipity and adaptive behaviors.

So, this talk will advocate for what could be called : “boring AI”. Boring AI is every day AI. It’s the AI behind Gmail’s smart replies or Netflix recommendation algorithm. You hardly notice it - but it transforms user experience.

Year after year, Apple provided us with many tools to implement boring AI features - let’s get on with them !

After an introduction of the “glossy vs. boring AI” debate, I will draw a parallel between AI and animations (same difficulty to “sell” them to customers ; same debate between fancy transitions and discreet loading views ; and a customer/developer/ux-designer triangle that could inspire customer/developer/data-scientist relationships).

Then, we’ll dive into various iOS frameworks, and show how we could use them to improve concretely a commonplace mobile app (e.g a social network client).

Among those frameworks are :

- Speech, with SFSpeechRecognizer
- Natural language, with NLTagger and NLEmbedding
- AVFoundation with AVSpeechSynthesizer
- SiriKit and intents
- (not an iOS framework) but we’ll also discuss text translation.

Okayyy, if you insist we’ll also have a look at Core/CreateML to see if it’s difficult to classify some text (“does an email contain a request for action ?”)
Throughout the talk, we’ll also pay special attention to privacy considerations.

When we think about developing features that are voice-forward, we think about existing voice assistants such as Alexa and Siri. What about the fully-capable computers that we have with us all the time, our smartphones? Some moments on our day to day life are very well suited for voice interactions: while in a car or cooking for example. Let’s not forget that voice interactions are extremely accessible, not only in a physical way (for people with dexterity or motion impediments) but also in a cognitive way (I think we all have a loved one in our lives that really struggles with technology, and people from some emerging countries have very limited access to computers and are not at ease with technology).

In this talk, I’ll explain what integrations can be done in iOS: - 1st-party solutions such as the Natural Language Framework and Siri Shortcuts - 3rd-party solutions such as Porcupine, Snips, Dialogflow, Amazon Lex, RASA and many others for each one, I’ll discuss the main characteristics - On device vs. Cloud - Open or Closed source - Pricing - Performance

In summary, this talk will help think about why you should implement conversational features on your app and how.

You use Swift everyday to create great client apps, but have you ever wondered what can it do more for you? Swift Superpowers will provide you with small tips of great - and unconventional - use cases for Swift, from cross-platform network code to scripting, prototyping and more...

When you write unit tests for your projects, there’s a fair chance that you do so by following the classical « Given-When-Then » paradigm, in which you set some input data, execute the code you’re testing, and finally assert that its outcome is indeed the one you expected.

While this approach is perfectly sound, it does suffer one downside: your program will only be tested on the static input data defined in your tests, and there is no real guarantee that this data does cover all edge cases. This can be especially problematic for SDK developers, who, by definition, have a very hard time anticipating all the different situations in which their code will be used.

To improve on this issue, another approach exists, and it is called property-based testing. The idea behind it is very simple: you write your tests by defining properties that must always be true for your program. For example, « an array reversed twice is always equal to itself ». The testing framework will then generate random input values and test wether the property holds or not. And, as you can imagine, this approach is extremely good at narrowing down on overlooked edge cases.

In Swift, we are lucky enough to already have a full-fledged implementation called SwiftCheck, that enables property-based testing (https://github.com/typelift/SwiftCheck). The goal of this talk is thus to explain how property-based testing can be a powerful addition to a testing suite, and give actual and actionable examples of how it can be added to a project using SwiftCheck.

Property Wrappers are one of the new hotness coming to Swift 5. They look like annotations, and they can do awesome things!

SwiftUI makes heavy use of them, so you will likely see plenty of them in the future; so better get used to them and understand them!

But besides explaining how they work and what they are for, this talk will also demonstrate how to create one yourself to benefit your own needs in your code!

There are plenty of interesting ideas, concepts and common patterns in your code that could greatly benefit from Property Wrappers, so come discover how you can create your own Property Wrappers to fit your own needs in your everyday job, from handling type-safe preferences, access tokens, constraints on acceptable values, and much more!

This talk will demonstrate how Property Wrappers are implemented and propose multiple interesting ideas for custom Property Wrappers for common patterns… but by the end of the talk you should also even be able to go wild and create your own to make your code more concise and magical!