QtVirtualKeyboard on Wayland

QtVirtualKeyboard on Wayland

For the last couple of years my focus was on the Osmocom project to bring Free Software to the world of telecommunication. With a group of enthusiasts we have implemented the components necessary to run a complete network using Free Software. The Rhizomatica project is using the software to connecting people that were left behind. Our tools enabled high impact security research leading, leading to improvements to privacy and security for all of us….

But during the last months I had the opportunity to return to C++ and Qt work and it feels like coming home to the world of ARM powered hardware. When I left, the transition from consumer electronics (e.g. settop boxes) to automative (e.g. IVI) began and it seems it successfully completed! On Friday I explored a regression in OpenSSL and today I had the pleasure to understand input method handling of wayland a little bit better.

I wanted to see if I can use wayland and run QtVirtualKeyboard only in the Compositor. I couldn’t find answers in the documentation and started to read the code. Once I understood how it should work, I found a simple example in QtWayland. Isn’t Qt wonderful?

As I have gone down the rabbit hole let me try to share some of my reading. At the core is the unstable (API subject to change) text-input protocol. Upstream of wayland-protocols is still at v1 of the protocol but QtWayland includes a copy of v2 and has rather complete support for the compositor and client (thanks KDAB!).

Compositor/Server

To make it work the compositor needs to signal support for the “zwp_text_input_manager_v2” interface. In QML/Quick this needs to be done by adding the following inside the WaylandCompositor component:

...
TextInputManager {
}
...

This will instantiate a QWaylandTextInputManager and call ::initialize on it. Then auto-generated code will use wl_global_create to register the interface in the global registry. Clients will request a text_input and the manager will create one or use a QWaylandTextInput and then send events down to the client. E.g. if there is a soft keyboard set a breakpoint in QWaylandTextInput::sendKeyEvent in the compositor and see from where it is coming and how it will send the event to a client.

Client

Once the client starts the QWaylandIntegration will create a QWaylandDisplay and then query/initialize the registry. The answer will call QWaylandDisplay::registry_global for every registered interface. For the the zwp_text_input_manager_v2 interface the integration will initialize a QtWayland::zwp_text_input_manager_v2 and for each input device a QtWaylandClient::QWaylandTextInput (different namespace) will be created.

Communication

Now Compositor and Client will communicate through the wayland connection (no dbus). With Qt APIs the client will notice which element has been focused and will request the input method to be shown (QtWaylandClient::QWaylandInputContext::showInputPanel) and the Compositor  will forward this to the QInputMethod (see QWaylandTextInputPrivate::zwp_text_input_v2_show_input_panel)

Putting it together

In the end this is rather simple.. create a TextInputManager, use the InputPanel of the QtVirtualKeyboard and start your compositor with QT_IM_MODULE=qtvirtualkeyboard. Done!

 

Static binaries (for Go with Docker)

Static binaries (for Go with Docker)

These days Go is quite popular for server based systems (read “cloud”) and one of the nice attributes is that compiling an application results in a single binary with no external dependencies (there is no “runtime” it has to link to). This makes deploying (read “copy to machine”) super easy and is a big contrast to something like Ruby on Rails and its thousands of dependencies. IIRC this feature was attractive to the developers of Qt’s coin (continuous integration agent) as well.

Amusingly in contrast to Rust, Swift or other modern languages the compiler/assembler/linker isn’t powered by LLVM but is based on the Plan9 C compiler which was converted to Go. By setting the GOOS and GOARCH environment variables one can easily cross-compile the binary. E.g. on MacOs build a binary that runs on Linux/ARM64.

When using other system libraries (through cgo) this single binary needs to link to other libraries but this complicates the deployment. The right version and ABI of the library need to be present, if not the application might not start or behaves weirdly. I was in this situation for my tcapflow monitoring utility. I would like to be able to deploy it on any version of RHEL, Ubuntu, Debian without anyone having to install the right libraries.

Here is where musl, Alpine and Docker came to rescue me. Let me briefly elaborate. The dominant C library on GNU/Linux is GNU Libc (glibc) doesn’t support static linking for some good (security, PIE) and some IMHO lazy reasons (PIE could still work, iconv/nss). On the other hand the musl library does support static linking and the C library is quite compatible to glibc and Alpine Linux is a Linux distribution that is using musl instead of glibc. By making use of Alpine I avoid having to build musl and then compiling libpcap and other libraries myself. The final item is Docker. It solves fetching a runnable set of binaries/libraries and setting-up/running a chroot for me. The command line below should result in the alpine container being fetched and an interactive shell prompt coming up. During development I use it to quickly fetch/try the latest version of postgres, mysql, etc.

docker run -it alpine:3.6 /bin/sh

I ended up creating a simple build script that will use the Alpine package manager to install the needed dependencies and then make a static build. The magic for the static build is to pass ldflags to go build which looks like:

go build --ldflags '-linkmode external -extldflags "-static"'

Instead of using a Dockerfile to build a container/image that I will never use (but would still consume disk space) I trigger my compilation through two commands. One to build for i386 and the other for AMD64.

docker run --rm=true -itv $PWD:/mnt alpine:3.6 /mnt/build_static.sh
docker run --rm=true -itv $PWD:/mnt i386/alpine:3.6 /mnt/build_static.sh

In the end I will have two binaries in the out/ directory of my sourcecode. I am using the Binutils objdump to look at the ELF headers of the binary to check which libraries it wants to link to. Shared library dependencies are indicated with NEEDED but in this case there is no such line which means the libpcap dependency was statically linked. For me musl+alpine+docker is the easiest way to build static binaries.

$ objdump -x out/tcapflow-client
out/tcapflow-client:     file format elf32-i386
out/tcapflow-client
architecture: i386, flags 0x00000150:
HAS_SYMS, DYNAMIC, D_PAGED
start address 0x000c55b9

Program Header:
LOAD off 0x00000000 vaddr 0x00000000 paddr 0x00000000 align 2**12
filesz 0x004ecf5c memsz 0x004ecf5c flags r-x
LOAD off 0x004edc8c vaddr 0x004eec8c paddr 0x004eec8c align 2**12
filesz 0x0032ea17 memsz 0x0075df34 flags rw-
DYNAMIC off 0x007e2f1c vaddr 0x007e3f1c paddr 0x007e3f1c align 2**2
filesz 0x000000a8 memsz 0x000000a8 flags rw-
NOTE off 0x00000120 vaddr 0x00000120 paddr 0x00000120 align 2**5
filesz 0x00000038 memsz 0x00000038 flags r--
TLS off 0x004edc8c vaddr 0x004eec8c paddr 0x004eec8c align 2**2
filesz 0x00000000 memsz 0x00000004 flags r--
STACK off 0x00000000 vaddr 0x00000000 paddr 0x00000000 align 2**4
filesz 0x00000000 memsz 0x00000000 flags rw-
RELRO off 0x004edc8c vaddr 0x004eec8c paddr 0x004eec8c align 2**0
filesz 0x002f5374 memsz 0x002f5374 flags r--

Dynamic Section:
SYMBOLIC 0x00000000
INIT 0x000c54ac
FINI 0x0046eed5
GNU_HASH 0x00000158
STRTAB 0x000001d8
SYMTAB 0x00000188
STRSZ 0x00000021
SYMENT 0x00000010
DEBUG 0x00000000
PLTGOT 0x007e3fc4
REL 0x000001fc
RELSZ 0x000c52b0
RELENT 0x00000008
BIND_NOW 0x00000000
FLAGS_1 0x08000001
RELCOUNT 0x00018a56
Captain obvious: Sign a contract before starting to work

Captain obvious: Sign a contract before starting to work

I have worked as a freelancer for more than a decade and was very very fortunate with the projects and partners I had. I apparently let my guards down a little bit too much and this is a reminder what to look-out for.

I have nice memories working with the Trolltech PSO team and helping with architecture, performance and low-level debugging in South Korea but when Nokia stopped investing into Qt my work on Qt and QtWebKit halted and I moved to work exclusively on GSM/3G systems. Through linkedin I got approached by a Korean business owner that spent some time working in Norway and for some companies well known to (old) Qt developers with something that looked like an opportunity to pick-up my old work. Given the common background and my work in Korea I immediately trusted this person.

I have a thing for tight deadlines and some forms of death march projects and was curious of how much the landscape changed. I thought we agreed on times and material for an exploration phase to see if the rest of the project is feasible and depending on the result move on or not, HW was sent and while there was no signed agreement I began to work. The exploration was fun but the setting was difficult and turns out there was no intention to pay for the exploration phase.

Which brings me to things I have to remember and want to share with you:

  • Don’t start to work before there is a written and signed agreement
  • If there is a tight deadline the burden on making the contract is on your customer and not you. If the contract is too long to read, reject it.
  • Don’t take the risk of unpaid exploration if you have no influence on the final project
Analyze cellular problems using Quectel modules

Analyze cellular problems using Quectel modules

Introduction

Previously I have written about connectivity options for IoT devices and today I assume that a cellular technology (e.g. names like GSM, 3G, UMTS, LTE, 4G) has been chosen. Unless you are a big vendor you will end up using a module (instead of a chipset) and either you are curious what the module is doing behind its AT command interface or you are trying to understand a real problem. The following is going to help you or at least be entertaining.

The xgoldmon project was a first to provide air interface traces and logging to the general public but it was limited to Infineon baseband (and some Gemalto devices), needed special commands to enable and didn’t include all messages all the time.

In the last months I have intensively worked with modules of a vendor called Quectel. They are using Qualcomm chipsets and have built the GSM/UMTS Quectel UC20 and the GSM/UMTS/LTE Quectel EC20 modules. They are available as a variant to solder but for speeding up development they provide them as miniPCI express as well. I ended up putting them into a PCengines APU2, soldered an additional SIM card holder for the second SIM card, placed U.FL to SMA connectors and put it into one of their standard cases. While the UC20 and EC20 are pretty similar the software is not the same and some basic features are missing from the EC20, e.g. the SIM ToolKit support. The easiest way to acquire these modules in Europe seems to be through the above links.

The extremely nice feature is that both modules export Qualcomm’s bi-directional DIAG debug interface by USB (without having to activate it through an undocumented AT command). It is a framed protocol with a simple checksum at the end of a frame and many general (e.g. logging and how regions are described) types of frames are known and used in projects like ModemManager to extract additional information. Some parts that include things like Tx-power are not well understood yet.

I have made a very simple utility available on github that will enable logging and then convert radio messages to the Osmocom GSMTAP protocol and send it to a remote host using UDP or write it to a pcap file. The result can be analyzed using wireshark.

Set-up

You will need a new enough Linux kernel (e.g. >= Linux 4.4) to have the modems be recognized and initialized properly. This will create four ttyUSB serial devices, a /dev/cdc-wdmX and a wwanX interface. The later two can be used to have data as a normal network interface instead of launching pppd. In short these modules are super convenient to add connectivity to a product.

apu2_quectel_uc20_ec20
PCengines APU2 with Quectel EC20 and Quectel UC20

Building

The repository includes a shell script to build some dependencies and the main utility. You will need to install autoconf, automake, libtool, pkg-config, libtalloc, make, gcc on your Linux distribution.

[shell]
git clone git://github.com/moiji-mobile/diag-parser
cd diag-parser
./build/build_local.sh
[/shell]

Running

Assuming that your modem has exposed the DIAG debug interface on /dev/ttyUSB0 and you have your wireshark running on a system with the internal IPv4 address of 10.23.42.7 you can run the following command.

[shell]
./diag-parser -g 10.23.42.7 -i /dev/ttyUSB0
[/shell]

Exploring

Analyzing UMTS with wireshark. The below shows a UMTS capture taken with the Quectel module. It allows you to see the radio messages used to register to the network, when sending a SMS and when placing calls.

diag-parse_rantrace
Wireshark dissecting UMTS
Collecting network traffic, ØMQ and packetbeat

Collecting network traffic, ØMQ and packetbeat

As part of running infrastructure it might make sense or be required to store logs of transactions. A good way might be to capture the raw unmodified network traffic. For our GSM backend this is what we (have) to do and I wrote a client that is using libpcap to capture data and sends it to a central server for storing the trace. The system is rather simple and in production at various customers. The benefit of having a central server is having access to a lot of storage without granting too many systems and users access, central log rotation and compression, an easy way to grab all relevant traces and many more.
Recently the topic of doing real-time processing of captured data came up. I wanted to add some kind of side-channel that distributes data to interested clients before writing it to the disk. E.g. one might analyze a RTP audio flow for packet loss, jitter, without actually storing the personal conversation.
I didn’t create a custom protocol but decided to try ØMQ (Zeromq). It has many built-in strategies (publish / subscribe, round robin routing, pipeline, request / reply, proxying, …) for connecting distributed system. The framework abstracts DNS resolving, connect, re-connect and exposes very easy to build the standard message exchange patterns. I opted for the publish / subscribe pattern because the collector server (acting as publisher) does not care if anyone is consuming the events or data. The message I sent are quite simple as well. There are two kind of multi-part messages, one for events and one for data. A subscriber is able to easily filter for events or data and filter for a specific capture source.
The support for Zeromq was added in two commits. The first one adds basic zeromq context/socket support and configuration and the second adds sending out the events and data in a fire and forget manner. And in a simple test set-up it seems to work just fine.
Since moving to Amsterdam I try to attend more meetups. Recently I went to talk at the local Elasticsearch group and found out about packetbeat. It is program written in Go that is using a PCAP library to capture network traffic, has protocol decoders written in go to make IP re-assembly and decoding and will upload the extracted information to an instance of Elasticsearch.  In principle it is somewhere between my PCAP system and a distributed wireshark (without the same amount of protocol decoders). In our network we wouldn’t want the edge systems to directly talk to the Elasticsearch system and I wouldn’t want to run decoders as root (or at least with extended capabilities).
As an exercise to learn a bit more about the Go language I tried to modify packetbeat to consume trace data from my new data interface. The result can be found here and I do understand (though I am still hooked on Smalltalk/Pharo) why a lot of people like Go. The built-in fetching of dependencies from github is very neat, the module and interface/implementation approach is easy to comprehend and powerful.
The result of my work allows something like in the picture below. First we centralize traffic capturing at the pcap collector and then have packetbeat pick-up data, decode and forward for analysis into Elasticsearch. Let’s see if upstream is merging my changes.

 

Connectivity options for mobile M2M/IoT/Connected devices

Connectivity options for mobile M2M/IoT/Connected devices

Many of us deal or will deal with (connected) M2M/IoT devices. This might be writing firmware for microcontrollers, using a RTOS like NuttX or a full blown Unix (like) operating system like FreeBSD or Yocto/Poky Linux, creating and building code to run on the device, processing data in the backend or somewhere inbetween. Many of these devices will have sensors to collect data like GNSS position/time, temperature, light detector, measuring acceleration, see airplanes, detect lightnings, etc.The backend problem is work but mostly “solved”. One can rely on something like Amazon IoT or creating a powerful infrastructure using many of the FOSS options for message routing, data storage, indexing and retrieval in C++. In this post I want to focus about the little detail of how data can go from the device to the backend.

To make this thought experiment a bit more real let’s imagine we want to build a bicycle lock/tracker. Many of my colleagues ride their bicycle to work and bikes being stolen remains a big tragedy. So the primary focus of an IoT device would be to prevent theft (make other bikes a more easy target) or making selling a stolen bicycle more difficult (e.g. by easily checking if something has been stolen) and in case it has been stolen to make it more easy to find the current location.

Architecture

Let’s assume two different architectures. One possibility is to have the bicycle actively acquire the position and then try to push this information to a server (“active push”). Another approach is to have fixed installed scanning stations or users to scan/report bicycles (“passive pull”). Both lead to very different designs.

Active Push

The system would need some sort of GNSS module, a microcontroller or some full blown SoC to run Linux, an accelerator meter and maybe more sensors. It should somehow fit into an average bicycle frame, have good antennas to work from inside the frame, last/work for the lifetime of a bicycle and most importantly a way to bridge the air-gap from the bicycle to the server.

Push architecture

 

Passive Pull

The device would not know its position or if it is moved. It might be a simple barcode/QR code/NFC/iBeacon/etc. In case of a barcode it could be the serial number of the frame and some owner/registration information. In case of NFC it should be a randomized serial number (if possible to increase privacy). Users would need to scan the barcode/QR-code and an application would annotate the found bicycle with the current location (cell towers, wifi networks, WGS 84 coordinate) and upload it to the server. For NFC the smartphone might be able to scan the tag and one can try to put readers at busy locations.
The incentive for the app user is to feel good collecting points for scanning bicycles, maybe some rewards if a stolen bicycle is found. Buyers could easily check bicycles if they were reported as stolen (not considering the difficulty of how to establish ownership).
Pull architecture

 

Technology requirements

The technologies that come to my mind are Barcode, QR-Code, play some humanly not hearable noise and decode in an app, NFC, ZigBee, 6LoWPAN, Bluetooth, Bluetooth Smart, GSM, UMTS, LTE, NB-IOT. Next I will look at the main differentiation/constraints of these technologies and provide a small explanation and finish how these constraints interact with each other. 

World wide usable

Radio Technology operates on a specific set of radio frequencies (Bands). Each country may manage these frequencies separately and this can lead to having to use the same technology on different bands depending on the current country. This will increase the complexity of the antenna design (or require multiple of them), make mechanical design more complex, makes software testing more difficult, production testing, etc. Or there might be multiple users/technologies on the same band (e.g. wifi + bluetooth or just too many wifis).

Power consumption

Each radio technology requires to broadcast and might require to listen or permanently monitor the air for incoming messages (“paging”). With NFC the scanner might be able to power the device but for other technologies this is unlikely to be true. One will need to define the lifetime of the device and the size of the battery or look into ways of replacing/recycling batteries or to charge them.

Range

Different technologies were designed to work with sender/receiver being away at different min/max. distances (and speeds but that is not relevant for the lock nor is the bandwidth for our application). E.g. with Near Field Communication (NFC) the workable range is meters while with GSM it will be many kilometers and with UMTS the cell size depends on how many phones are currently using it (the cell is breathing).

Pick two of three

Ideally we want something that works over long distances, requires no battery to send/receive and the system is still pushing out the position/acceleration/event report to servers. Sadly this is not how reality works and we will have to set priorities.
The more bands to support, the more complicated the antenna design, production, calibration, testing. It might be that one technology does not work in all countries or that it is not equally popular or the market situation is different, e.g. some cities have city wide public hotspots, some don’t.
Higher power transmission increases the range but increases the power consumption even more. More current will be used during transmission which requires a better hardware design to buffer the spikes, a bigger battery and ultimately a way to charge or efficiently replace batteries.Given these constraints it is time to explore some technologies. I will use the one already mentioned at the beginning of this section.

Technologies

TechnologyBandsGlobal coverageRangeBattery neededScan Device neededCost of deviceArch.Comment
Barcode/QR-CodeOpticalYesCentimetersNoApp scanning barcode requiredextremely lowPullSticker needs to be hard to remove and visible, maybe embedded to the frame
Play audioNon human hearable audioYesCentimetersYesApp recording audiomoderatePullButton to play audio?
NFC13.56 MhzYesCentimetersNoYesextremely lowPullPrivacy issues
RFIDManyYes, but not on single bandCentimeters to metersYesReceiver requiredlowPullMany bands, specific readers needed
Bluetooth LE2.4 GhzYesMetersYesYes, but commonlowPull/PushCompetes with Wifi for spectrum
ZigBeeMultipleYes, but not on single bandMetersYesYesmidPushNot commonly deployed, software more involved
6LoWPANLike ZigBeeLike ZigBeeMetersYesYeslowPushUses ZigBee physical layer and then IPv6. Requires 6LoWPAN to Internet translation
GSM800/900, 1800/1900Almost besides South Korea, Japan, some islandsKilometersYesNomoderatePushAlmost global coverage, direct communication with backend possible
UMTSManyLess than GSM but South Korea, JapanMeters to Kilometers depends on usageYesNohighPushHigher power usage than GSM, higher device cost
LTEManyLess than GSMDesigned for kilometersYesNohighPushExpensive, higher power consumption
NB-IOT (LTE)ManyNot deployedKilometersYesNohighPushNot deployed and coming in the future. Can embed GSM equally well into a LTE carrier

Conclusion

Both a push and pull architecture seem to be feasible and create different challenges and possibilities. A pull architecture will require at least Smartphone App support and maybe a custom receiver device. It will only work in regions with lots of users and making privacy/tracking more difficult is something to solve.
For push technology using GSM is a good approach. If coverage in South Korea or Japan is required a mix of GSM/UMTS might be an option. NB-IOT seems nice but right now it is not deployed and it is not clear if a module will require less power than a GSM module. NB-IOT might only be in the interest of basestation vendors (the future will tell). Using GSM/UMTS brings its own set of problems on the device side but that is for other posts.
Leaving Berlin, saying hello to Amsterdam

Leaving Berlin, saying hello to Amsterdam

Berlin continues to gain a lot of popularity, culturally and culinarily it is an awesome place and besides increasing rents it still remains more affordable than other cities. In terms of economy Berlin attracts new companies and branches/offices as well. At the same time I felt the itch and it was time to leave my home town once again. In the end I settled for the bicycle friendly (and sometimes sunny) city of Amsterdam.

My main interest remains building reliable systems with Smalltalk, C/C++, Qt and learn new technology (Tensorflow? Rust? ElasticSearch, Mongo, UUCP) and talk about GSM (SCCP, SIGTRAN, TCAP, ROS, MAP, Diameter, GTP) or get re-exposed to WebKit/Blink.
If you are in Amsterdam or if you know people or companies I am happy to meet and make new contacts.
C++, Qt and Treefrog to build user facing web applications

C++, Qt and Treefrog to build user facing web applications

In the past I have written about my usage of Tufao and Qt to build REST services. This time I am writing about my experience of using the TreeFrog framework to build a full web application.

You might wonder why one would want to build such a thing in a statically and compiled language instead of something more dynamic. There are a few reasons for it:

  • Performance: The application is intended to run on our sysmoBTS GSM Basestation (TI Davinci DM644x). By modern standards it is a very low-end SoC (ARMv5te instruction set, single core, etc, low amount of RAM) and at the same time still perfectly fine to run a GSM network.
  • Interface: For GSM we have various libraries with a C programming interface and they are easy to consume from C++.
  • Compilation/Distribution: By (cross-)building the application there is  a “single” executable and we don’t have the dependency mess of Ruby.
The second decision was to not use Tufao and search for a framework that has user management and a template/rendering/canvas engine built-in. At the Chaos Computer Camp in 2007 I remember to have heard a conversation of “Qt” for the Web (Wt, C++ Web Toolkit) and this was the first framework I looked at. It seems like a fine project/product but interfacing with Qt seemed like an after thought. I continued to look and ended up finding and trying the TreeFrog framework.
I am really surprised how long this project exists without having heard about it. It is using/built on top of Qt, uses QtSQL for the ORM mapping, QMetaObject for dispatching to controllers and the template engine and resembles Ruby on Rails a lot. It has two template engines, routing of URLs to controllers/slots, one can embed any C++ in the template. The documentation is complete and by using the search on the website I found everything I was searching for my “advanced” topics. Because of my own stupidity I ended up single stepping through the code and a Qt coder should feel right at home.
My favorite features:
  • tspawn model TableName will autogenerate (and update) a C++ model based on the table in the database. The updating is working as well.
  • The application builds a libmodel.so, libhelper.so (I removed that) and libcontroller.so. When using the -r option of the application the application will respawn itself. At first I thought I would not like it but it improves round trip times.
  • C++ in the template. The ERB template is parsed and a C++ class will be generated and the ::toString() method will generate the HTML code. So in case something is going wrong, it is very easy to inspect.
If you are currently using Ruby on Rails, Django but would like to do it with C++, have a look at TreeFrog. I really like it so far.
A C++ project without Qt

A C++ project without Qt

My primary language is Smalltalk (Pharo and GNU Smalltalk) and I didn’t write much C++1x code yet and for a new project I decided to use C++ and experiment. The task was rather simple, receive a message, check if this message type needs to be re-written, start to parse it, make a MongoDB look-up, patch it, send it.

While looking for MongoDB drivers for Qt I only found the pure C++ driver that is working with std::string, exceptions and only offers a blocking interface. At this point I decided to see how painful using stl is these days and opted for a pure stl project. Many years ago the only online documentation came from SGI, there were no examples, no autocompletion in editors, etc…

The application is relatively trivial. It is using lambdas to hook two components (the receiver and the patcher) together, it is using std::thread with lambdas to spawn worker threads because of the blocking interface of the database driver, std::chrono for some ad-hoc StatsD code to add event counters and performance monitoring.

So how did this experiment go?

The C++11/C++14 documentation that is available has improved over the old times, it is still below the quality of the Qt documentation.

Once deploying this on Debian I immediately had odd crashes and I blame ABI issues as my application used C++1x but the mongo-cxx-driver was apparently not using it. I ended up packaging the latest stable (“legacy”) standalone driver for debian and made sure it is compiled with C++1x.

The std::chrono API has potential (as it allows me to control the resolution) but the API, specially in C++11 without the new literals, makes easy things difficult. All I wanted was something like QTimer::elapsed() or QElapsedTimer::elapsed(). So I think the Qt API is better designed for this usecase (my measurement resolution is milliseconds and not picoseconds).

For socket code I was using pure C/libc. As my database code was blocking I could make my socket code blocking as well.

I normally use vim but when working with an unknown API I totally enjoy the comfort QtCreator is providing. I was able to jump to the header files and explore the interface. I think it has saved me quite some time while wrangling with the stl.

New languages come with their own build tools these days (Rust/Cargo, Ruby/Rake, …) and C++1x doesn’t have anything to offer here. The options I considered where autotools, CMake or qmake. I think autotools are overkill here, I dislike CMake for various reasons and I like the simplicity of qmake.

In the past I had played with the Google C++ Unittest framework and actually liked it a lot. These days one is asked to copy and paste the framework into the code base. It is an ongoing struggle if one should embed third party libraries or not but as my application is rather small I decided it is a no go. I have used and enjoyed the Qt testlib. So my STL only application is tested using QObject and QCoreApplication.

Conclusion:

The STL (and the documentation) has improved. I still prefer the API design of Qt and when not just interfacing with an library that is using std::string Qt is still my first choice (as it provides event loops, signals/slots, networking, http, etc.).

Playing with QV4

Playing with QV4

QtDeclarative is where the fun is. Starting with Qt5.2 a JavaScript Engine written by Digia is used. Compared to JavaScriptCore and V8 this engine is very basic but tightly integrated with the QML and Quick code. Motivated by attending the Qt Developer Summit and my work on GNU Smalltalk I started to look at the VM.

There are some environment variables that help to see what the JavaScript VM is doing and also how it is doing things. The below table gives a quick overview of the available flags and what they do. Specially the usage of QV4_SHOW_IR and QV4_SHOW_ASM helps to understand what is going on.

NameFunction
QV4_NO_SSADo not convert the IR::Function to SSA representation. This disables optimizations as well.
QV4_NO_OPTDo not run the optimizer. This disables dead-code-elimination, constant propagation, copy propagation
QV4_SHOW_IRShow the Intermediate Representation at the various stages of the compilation/optimization.
QV4_SHOW_ASMShow the disassembled code. This requires QtDeclrative to be compiled with CONFIG+=disassembler and without PCH
QV4_NO_REGALLOCDo not use the linear register allocator
QV4_FORCE_INTERPRETERDo not use the JIT but force the interpreter
QV4_MM_AGGRESSIVE_GCRun the GC on every allocation
QV4_MM_STATSPrint the time it took to mark and sweep