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The State of Mozilla 2017 report is out and contains information on areas where Mozilla has made an impact and its activities in 2017-18. We look at some of the important details from the report. Towards building a healthier internet In the last two years, there have been scandals and news around big tech companies relating to data misuse, privacy hindrances and more. Some of these include the Cambridge Analytica scandal, Google tracking, and many others. Public and political trust from large tech companies has eroded following the uncovering of how some of these companies operate and treat user data. The Mozilla report says that now the focus is on how to limit these tech platforms and encourage them to adopt data regulation protocols. Mozilla seeks to fill the void where there is a lack of people who can decide correctly towards building a better internet. The State of Mozilla 2017 report reads: “When the United States Federal Communications Commission attacks net neutrality or the Indian government undermines privacy with Aadhaar, we see people around the world—including hundreds of thousands of members of the Mozilla community—stand up and say, Things should not work this way.” Read also: Is Mozilla the most progressive tech organization on the planet right now? The Mozilla Foundation and the Mozilla Corporation Mozilla was founded in 1998 as an open source project back when open source was truly open source, free of things like the Commons Clause. Mozilla has two organizations. The Mozilla Foundation which supports emerging leaders and mobilizes citizens towards better health of the internet. Second, the Mozilla Corporation which is a wholly owned subsidiary of the former and creates Mozilla products and advances public policy. The Mozilla Foundation Mozilla invests in people and organizations with a common vision other than building products. Another part of the State of Mozilla 2017 reads: “Our core program areas work together to bring the most effective ideas forward, quickly and where they have the most impact. As a result of our work, internet users see a change in the products they use and the policies that govern them.” Every year Mozilla Foundation creates the open source Internet Health Report to shed light on what’s been happening on the internet, specifically on its wellbeing. Their research includes data from multiple sources on areas like privacy and security, open innovation, decentralization, web literacy, and digital inclusion. Per the health report, Mozilla spent close to a million in 2017 on their agenda-setting work. Mozilla has also mobilized conscious internet users with campaigns around net neutrality in the US, India’s Aadhaar biometric system, copyright reform in the EU, and more. Mozilla has also invested in connecting internet health leaders and worked on data and privacy issues across the globe. It also invested about $24M in 2017 in this work. The Mozilla Corporation Mozilla says that to take the charge in changing internet culture they need to do more than building products. Post Firefox Quantum’s success, their focus is to better enable people in taking control of their online life. Another part of the State of Mozilla 2017 report highlights their vision stating that “Over the coming years, we will become the leading provider of user agency and online privacy by developing long-term trusted relationships with "conscious choosers" with a focus on helping people navigate their connected lives.” Mozilla pulled its ads from Facebook after the Cambridge Analytica scandal After learning about the Cambridge Analytica incident and guided by the Mozilla Manifesto, they decided to pull their ads from Facebook. Their Manifesto says “Individuals’ security and privacy on the Internet are fundamental and must not be treated as optional,”. After sending a message with this action, Mozilla also launched Facebook Container. It is a version of multi-account containers that prevent Facebook from tracking its users when they are not on the platform. They say that everyone has a right to keep their private information private and control their own web experiences. You can view the full State of Mozilla 2017 report at the Mozilla website. Mozilla shares plans to bring desktop applications, games to WebAssembly and make deeper inroads for the future web Mozilla criticizes EU’s terrorist content regulation proposal, says it’s a threat to user rights Is Mozilla the most progressive tech organization on the planet right now?

Yesterday, the Rust Survey team published the results of their annual Rust survey of 2018. This year’s survey was launched in 14 different languages which helped in increasing the number of responses to 5991. The survey highlights that there is a slight increase in medium to large investments in Rust, most of the users prefer Linux over Windows for development, and more. Growth in the number of Rust users Rust is seeing a steady growth in the number of Rust users. Nearly 23% of these users have been using it for 3 months or less and up to a quarter of them are using it for at least 2 years. Talking about how much time it takes to get productive in Rust, 40% of Rust users said it takes less than a month of use, and over 70% felt productive in their first year of use itself. Over 22% of the Rust users do not feel productive, out of which only about 25% are in their first month of use. Larger overall investments in Rust projects Rust projects are seeing larger overall investments and trending to larger sizes. The percentage of medium to large investments in Rust has increased from 8.9% in 2016, to 16% in 2017, to 23% this year. There is also some growth in the Rust daily usage from 17.5% last year to nearly a quarter of users this year. In total, Rust weekly total usage has risen from 60.8% to 66.4%. Difficulty level of common Rust concepts Most of the Rust users consider themselves to be intermediates in terms of expertise in Rust. The users felt that Enums and Cargo are the easiest concepts to learn, followed by Iterators, Modules, and Traits, Trait Bounds, and Unsafe. The most difficult concepts are Macros, Ownership & Borrowing, and Lifetimes. Usage Patterns of Rust tools Same as last year, users are preferring the current stable release of Rust. There is a slight increase in the number of the Nightly compiler users, which is now over 56% (up from 51.6% of last year). Users are opting Nightly for accessing 2018 edition, asm, async/await, clippy, embedded development, rocket, NLL, proc macros, and wasm. The percentage of users who see a breakage during a routine compiler update remains the same as last year (7.4%). These breakages generally required minor fixes, though some reported having moderate or major fixes to upgrade to the next stable compiler. 90% of the users voted rustup as their first choice for installing Rust. Linux distros is the second option with only 17% of Rust installs. Tools like rustfmt and rustdoc got lots of positive support, following these is the clippy tool. The IDE support tools Rust Language Server and racer also had positive support but unfortunately, of the tools surveyed, generated a few more dislike votes and comments. The bindgen tool has relatively small userbase. Preferred development platforms of Rust users While there is some increase in Windows usage from 31% last year to 34% this year, Linux platform continues to be popular among Rust developers with 80% of users opting it. While there is not much change from the last year for other target platforms, WebAssembly is an exception. It has shown nearly doubled up growth from last year’s 13% to this year’s 24%. In editors, VSCode has bested Vim, the front-runner in editors for two years, which grew from 33.8% of Rust developers to 44.4% this year. Increase in commercial use of Rust Rust’s part-time usage at the workplace has increased from 16.6% to 21.2%. Its full-time commercial has doubled from 4.4% to 8.9%. In total, its commercial use has grown from 21% to just over 30% of Rust users. Though there is an increase in the commercial use, over a third of Rust users aren’t sure their companies will invest in Rust. To know more in detail, read the annual Rust Survey 2018. Rust Beta 2018 is here 3 ways to break your Rust code into modules Red Hat announces full support for Clang/LLVM, Go, and Rust

The team at Gradle has now released Gradle 5.0 after Gradle 4.9 was released in July this year. Gradle 5.0 is faster, safer and more capable than the previous ones. Gradle is a build tool which accelerates developer productivity as it helps teams build, automate and deliver software faster. This tool focuses on build automation and support for multi-language development. Improvements in Gradle 5.0 Gradle 5.0 comes incremental compilation and annotation processing to enhance caching and up-to-date checking. Gradle 5.0 also brings features such as Kotlin DSL, dependency version alignment, version locking, task timeouts, Java 11 support, and more. The Kotlin DSL helps the IDE users in code completion and refactoring. Faster builds with build cache Users can experience faster builds the moment they upgrade to Gradle 5.0. Gradle 5.0 allows developers and business executives to build only what is needed by using the build cache and incremental processing features. The build cache reuses the results of previous executions and makes the process faster. It also reduces the build time by approximately 90%. Incremental Java compilation and annotation processing Gradle 5.0 features an incremental compiler. Now, there is no need for CompileJava tasks to recompile all the source files except for the the first time This compiler is default in this version and is highly optimized. It also supports incremental annotation processing which increases the effectiveness of incremental compilation in the presence of annotation processors. Users have to upgrade to the latest version (5.0) of the processors to experience the annotation processing. The new annotationProcessor configuration is used to manage the annotation processors and for putting them on the annotation processor path. Fine-grained transitive dependency management Gradle 5.0 comes with new features for customizing dependencies and features for improved POM and BOM support. Gradle 5.0 supports dependency constraints that are used to define versions or version ranges to restrict direct and transitive dependency versions. In this version, the platform definitions or Maven BOM dependencies are natively supported which allows the use of Spring Boot platform definition without using an external plugin. The dependency alignment aligns the modules in a logical group. With this release, the dynamic dependency versions can now be locked for better build reproducibility. This version can import bill of materials (BOM) files. Writing Gradle build logic Users can now write Gradle build scripts in Kotlin. The functionality of Static-typing in Kotlin allows tools to provide better IDE assistance to the users. More memory efficient Gradle execution The lower memory requirements and cache cleanup reduces Gradle’s overhead on the system. In Gradle 5.0, many caching mechanisms have been optimized for reducing the default memory for Gradle processes. New Gradle invocation options This version supports JUnit 5: JUnit Platform, JUnit Jupiter, and JUnit Vintage which helps in enabling test grouping and filtering. The tasks for non-interactive environments like continuous integration execution group the log messages. It’s now easy to identify if a test has failed with arich command-line console as it shows a colored build status. One can now work on interdependent projects with the help of composite builds in Gradle 5.0. This release of Gradle supports custom arguments which help in running Java applications faster and easier. New Gradle task and plugin APIs This version of Gradle features a new Worker API for safe parallel and asynchronous execution. Gradle 5.0’s new Configuration Avoidance APIs allow  users to configure projects together. The task timeout API helps to specify a timeout duration for a task, after which it will be interrupted. Custom CLI args in Gradle 5.0 helps the users to configure their custom tasks.   To know more about Gradle 5.0. check out Gradle’s official blog. Gradle 4.9 released! Android Studio 3.2 Beta 5 out, with updated Protobuf Gradle plugin Setting Gradle properties to build a project [Tutorial]

Researchers have developed a new iBCI (intracortical brain-computer interface) that allows people with paralysis to control an unmodified, commercially available tablet. This research was based on the fact that most general-purpose computers have been difficult to use for people with some form of paralysis.  In their study, three research participants with tetraplegia who had multielectrode arrays implanted in motor cortex as part of the BrainGate2 clinical trial were invited. Using the iBCI, their neural activity was decoded in real time with a point-and-click wireless Bluetooth mouse. This allowed participants to use common and recreational applications (web browsing, email, chatting, playing music on a piano application, sending text messages, etc.). iBCI also allowed two participants to “chat” with each other in real time.   The architecture of the setup  Participants used seven common applications on the tablet: an email client, a chat program, a web browser, a weather program, a news aggregator, a video sharing program, and a streaming music program.   The system consisted of a NeuroPort recording system to record neural signals from the participant’s motor cortex.   These signals were routed into a real-time computer running the xPC/Simulink Real-Time operating system for processing and decoding. The output of the decoding algorithm was passed to a Bluetooth interface configured to work as a wireless computer mouse using the Bluetooth Human Interface Device (HID) Profile.   This virtual Bluetooth mouse was paired with a commercial Android tablet device with no modifications to the operating system.   Participants performed real-time “point-and-click” control over a cursor that appeared on the tablet computer once paired through the Bluetooth interface.  The cursor movements and clicks by participants were decoded from neural activity using Kalman filters. 2D cursor velocities were estimated using a Recalibrated Feedback Intention Trained Kalman Filter (ReFIT-KF) and a cumulative closed-loop decoder. Click intentions were classified using a hidden Markov model and a linear discriminant analysis classifier.  Future work  The researchers want to expand the control stock with additional decoded signals, leveraging more optimized keyboard layouts, exploring accessibility features, and controlling other devices and operating systems. They also want to extend the output of the iBCI to support additional dimensions that may be used to command advanced cursor features.   For detailed analysis, go through the research paper.  What if buildings of the future could compute? European researchers make a proposal.  Babysitters now must pass Perdictim’s AI assessment to be “perfect” to get the job  Mozilla introduces LPCNet: A DSP and deep learning-powered speech synthesizer for lower-power devices 

An announcement post yesterday said that Rust 2018 beta is now in the final phase before release. A new beta has just been released with updates. After bug fixes, the final release will take place on December 6. In comparison to the Rust 2018 Edition Preview 2, the new Rust 1.31.0 beta includes all of the features stabilized in v1.31.0 207 and many bug fixes. Those new features are as follows. Changes in Rust Beta The new lifetime elision rules now allow eliding lifetimes in functions and impl headers. Lifetimes are still needed to be defined in structs. const functions can now be defined and used. These const functions right now are a strict minimal subset of the const fn RFC. Tool lints can now be used, which allow scoping lints from external tools by using attributes. With this release, the #[no_mangle] and #[export_name] attributes can be located anywhere in a crate. Previously they could only be located in exported functions. Parentheses can now be used in pattern matches. The compiler change includes updating musl to 1.1.20. There are some library changes and API stabilizations. Now, cargo will download crates in parallel using HTTP/2 protocol. The packages in Cargo.toml can also be renamed now. You can know more about these changes on GitHub. Changes in tooling Rust Beta 2018 also includes a number of improvements in the area of tooling. Rustfmt is now at version 1.0. RLS and Clippy will no longer be installed via “preview” components after a rustup update. The developers have listed two focus areas to find the bugs, namely the module system implementation and the RLS. Work for next release In Rust Preview 2, two variants for the module system were evaluated—“anchored paths” vs “uniform paths”. This evaluation continues in this beta release. This means that the compiler accepts only code that both variants would accept. You can read the announcement post for more details. Rust 2018 RC1 now released with Raw identifiers, better path clarity, and other changes GitHub Octoverse: The top programming languages of 2018 Red Hat announces full support for Clang/LLVM, Go, and Rust

Last week, Google brought the popular coding competitions Code Jam, HashCode and Kick Start together on a single website. This brand new UI will make the navigation better to make it user friendly. The user profile will now show notifications which will make the user experience better. Code Jam Google’s global coding competition, Code Jam, gives an opportunity to programmers around the world to solve tricky algorithmic puzzles. The first round includes three sub rounds. Next, the top 1,500 participants from each sub-round then get a chance to compete for a spot in round 2. Top 1,000 contestants are chosen out of them and they get an opportunity to move to the third round. Top 25 contestants will get selected from the third round and they will compete for the finals. The winners get the championship title and $15,000. HashCode HashCode is a team-based programming challenge organized by Google for students and professionals around the world. After registering for the contest, the participants will get an access to the Judge System. The Judge System is an online platform where one can form the team, join a hub, practice, and compete during the rounds. One can choose their team and programming language and the HashCode team assigns an engineering problem to the teams by live streaming on Youtube. The teams can compete either from a local hub or any another location of their choice. The selected teams will compete for the final round at Google’s office. Kick Start Kick Start, also a global online coding competition, consists of a variety of algorithmic challenges designed by Google engineers. Participants can either participate in one of the online rounds or in all of them. The top participants will get a chance to be interviewed at Google. The best part about KickStart is that it is open to all participants and there is no pre-qualification needed. If you are competing in a coding competition for the first time, then KickStart is the best option. What can you expect with this unified interface? Some good competition and some amazing insights coming from each of the rounds. Personalized certificate of completion. A chance to practice coding and experience new challenges A lot of opportunities To stay updated with the registration dates and details, one can sign up on Google’s coding competition’s official page. To know more about the competitions, check out Google’s blog. Google hints shutting down Google News over EU’s implementation of Article 11 or the “link tax” Recode Decode #GoogleWalkout interview shows why data and evidence don’t always lead to right decisions in even the world’s most data-driven company Google Dart 2.1 released with improved performance and usability

Yesterday, the team at Gitlab released GitLab 11.5. GitLab, an application for the DevOps lifecycle helps the developer teams work together efficiently to secure their code. Group Security Dashboard and Operations-Focused Dashboard To strengthen security, the security teams need to have access to information about the security status of all their projects. It is important for them to understand what the most important task is to take up next. It is also equally important for directors of security in any organization, as they need to have a high-level view of possible critical issues which might affect the development. GitLab 11.5 introduced a new Group Security Dashboard launched at the group level. This security dashboard gives a summary of all the SAST (Static Application Security testing) vulnerabilities in the projects in a particular group, and also provides a list of actionable entries that could be used for starting a remediation process. This dashboard also has a new look and has new visualizations. The goal is to have a single tool that security teams can use instead of using multiple tools. GitLab 11.5 also comes with a new, operations-focused dashboard, which is responsible for providing a summary of the key operational metrics for each project where a user is interested. This dashboard comes with some interesting features, including, the most recent commit, time since the last deployment, and active alerts. A user can also set this dashboard as their preferred homepage. GitLab 11.5 brings control access to Gitlab Pages GitLab Pages is a feature that helps users to publish static websites directly from a repository in GitLab. GitLab Pages is also used to serve static content on the web easily. GitLab 11.5 brings control access to GitLab Pages. The access control permissions applied to issues and code can now also be applied to static webpages. This way the access can be restricted and given only to those permitted by the user. The users who lack permission will get a 404 when visiting the link for those webpages. Knative is a Kubernetes-based platform used for building, deploying, and managing modern serverless workloads. With GitLab 11.5, users can deploy Knative to their existing Kubernetes cluster by using the GitLab Kubernetes integration. Tasks such as routing and managing traffic, source-to-container builds, and scaling-to-zero have now become easy. GitLab 11.5 comes with improvements to Issue Boards cards Issue Boards is central place of collaboration in GitLab, where teams can organize, and view planned and ongoing work. In GitLab 11.5, issue cards have been redesigned and it now shows relevant information in a simple and organized manner. The issue cards now show the issue title, confidentiality, time-tracking information, due date, labels, weight, and assignee. To read full GitLab updates, check out the official post by GitLab. GitLab 11.4 is here with merge request reviews and many more features GitLab 11.3 released with support for Maven repositories, protected environments and more  GitLab raises $100 million, Alphabet backs it to surpass Microsoft’s GitHub

ClojureCUDA is a CUDA that supports parallel computations on the GPU with CUDA in the Clojure programming language. With this library, you can access high-performance Computing and GPGPU in Clojure. Installation ClojureCUDA 0.6.0 now has support for the new CUDA 10. To start using it: Install the CUDA 10 Toolkit Update your drivers Update the ClojureCUDA version in project.clj All the existing code should work without requiring any changes. CUDA and libraries CUDA is the most used environment for high-performance computing on NVIDIA GPUs. You can now use CUDA directly from the interactive Clojure REPL without having to wrangle with the C++ toolchain. High-performance libraries like Neanderthal take advantage of ClojureCUDA to deliver speed dynamically to Clojure programs. With these higher-level libraries, you can perform fast calculations with just a few lines of Clojure. You don’t even have to write the GPU code yourself. But writing the lower level GPU code is also not so difficult in an interactive Clojure environment. ClojureCUDA features The ClojureCUDA library has features like high performance and optimization for Clojure. High-performance computing CUDA enables various hardware optimizations on NVIDIA GPUs. Users can access the leading CUDA libraries for numerical computing like cuBLAS, cuFFT, and cuDNN. Optimized for Clojure ClojureCUDA is built with a focus on Clojure. The interface and functions fit into a functional style. They are also aligned to number crunching with CUDA. Reusable The library closely follows the CUDA driver API. Users translate examples from best CUDA books easily. Free and Open Source It is licensed under the Eclipse Public License (EPL) which is the same license used for Clojure. ClojureCUDA and other libraries by uncomplicate are open source. You can choose to contribute on GitHub or donate on Patreon. For more details and code examples, visit the dragan Blog. Clojure 1.10.0-beta1 is out! Stable release of CUDA 10.0 out, with Turing support, tools and library changes NVTOP: An htop like monitoring tool for NVIDIA GPUs on Linux

Yesterday, the JetBrains community announced IntelliJ IDEA 2018.3, this year’s third major update. The IntelliJ IDEA 2018.3 is a massive new update that delivers Java 12 support, Multiline TODO comments, GitHub Pull Requests, Git submodules, Accessibility improvements, and more. Major updates in the IntelliJ IDEA 2018.3 Java Updates Support for Java 12: The 2018.3 version adds an initial support for the upcoming Java 12. Users can preview the Raw String Literals (JEP 326) in the IDE. Quickly spot duplicates: Users can now quickly spot duplicates in more complicated cases using this IDE. Java Stream API improvements: Redundant sorted calls made before the subsequent min call are now easily detected. New data-flow-based inspection: The new inspection known as ‘Condition is covered by further condition’ detects situations where the first condition is unnecessary as it’s covered by the second one. The new IDE provides a quick-fix to remove such redundant conditions. Detection of redundant usages of the @SuppressWarning annotation: The IDE now identifies situations where a suppressed inspection no longer addresses any warnings in the associated method body, class, or statement. Editor Updates Issues in code are highlighted: The IDE highlights the first and all subsequent TODO comment lines in the editor and displays them in the TODO tool window. New indentation status bar: A new indentation status bar displays the size of the indent in the current file. Improvements in the EditorConfig support: You can create a scope to disable code formatting from being done on specific files and folders. Go to the ‘Formatter Control’ tab in Preferences / Settings | Editor | Code Style. Syntax highlighting and code completion are now available for EditorConfig files. Version Control Updates Initial support for GitHub Pull Requests:  With this users can now view PRs in their IDE. Support for Git submodules: update your project, commit changes, view diffs, and resolve conflicts. New GitHub Pull Requests tool window: With this tool window, users can preview all the pull requests in your GitHub repository. Advanced navigation in VCS Log: Users can use the Forward and Back navigation actions while they are in the VCS Log after they navigate from the commit hashes to the commit in the VCS Log tab, or after they use the Go to hash/branch/tag action. Simply use the left and right arrow keys to navigate to the child or parent commit. Preview differences in the File History tab: Diff Preview is now available in the File History tab of the Version Control tool window. Kotlin Updates Kotlin 1.3 support: IntelliJ IDEA can help you migrate Kotlin project to Kotlin 1.3 and perform all the required changes in obsolete code to make it compliant with the latest state of the libraries. Enhancements in multiplatform project support: In Kotlin 1.3, the model of multiplatform projects has been completely reworked in order to improve expressiveness and flexibility, and to make sharing common code easier. IntelliJ IDEA provides a set of project examples that cover the most common use cases. New Kotlin Inspections & Quick-fixes: Since the release of IntelliJ IDEA 2018.2, the Kotlin plugin has got over 30 new inspections, quick-fixes, and intentions that helps write a code much more effectively. Spring & Spring Boot Updates Spring Boot 2.1 support: IntelliJ IDEA 2018.3 fully supports Spring Boot 2.1. Configuration values annotated with @DataSize are validated using the default @DataSizeUnit if specified. Spring Initializr improvements: While creating a project using Spring Initializr, the IDE will suggest installing or enabling appropriate plugins to ensure that support for all selected technologies is present. Better JPA and Spring Data support for Kotlin: Now the IDE can automatically inject JPQL into query strings, providing completion for entity names and parameters. Users can write Spring Data interfaces in Kotlin, and IntelliJ IDEA will understand the entities used. The IDE provides smart completion for method names and quick-fixes for parameters. Maven Updates Users can now easily delegate all their build and run actions to Maven. They simply have to go to Preferences (Settings) | Build, Execution, Deployment | Build Tools | Maven | Runner and select the new Delegate IDE build/run actions to maven option. JVM Debugger Updates Attach to Java processes that were started without a debug agent:  After attaching to a process, users will be able to view the current thread’s state and variable values, and use the memory view. If users want to attach the debugger to their local process, they can use the handy new Attach Debugger action, which is available in the Run Tool Window Async stack traces in remote JVMs: IntelliJ IDEA 2018.3 now supports async stack traces in remote JVMs. To start using the agent remotely: copy /lib/rt/debugger-agent.jar to the remote machine. add -javaagent:debugger-agent.jar to the remote JVM options. Action to remove all breakpoints: IntelliJ IDEA 2018.3 comes with handy new actions that remove all the breakpoints in a project, or all the breakpoints in the file. JavaScript & TypeScript Updates Improved Angular support: This includes much more accurate code completion and Go to definition for variables, pipes and async pipes, and template reference variables. Autoimports in JavaScript: IntelliJ IDEA can now automatically add imports for symbols from the project’s dependencies, in JavaScript files. This works as long as there’s a TypeScript definition file inside the package, or the package contains sources written as ES module. Support for Node.js worker threads: Users can now debug Node.js workers in IntelliJ IDEA. Users should be cautious of using Node.js 10.12 or above and the experimental-worker flag. The IDE provides code completion for the worker threads’ API. Improved flexibility with ESLint and TSLint: Users can override severity levels from the linter’s configuration file and see all problems from the linter as errors or warnings. Kubernetes Update Support for Helm resource files: The IDE now resolves the Helm resource template files and provides with editing support, which includes code completion, rename refactoring, and inspections and quick-fixes. Navigation in Helm resource files: The IDE lets users navigate from a value’s usage to its declaration in the chart’s values.yaml file. Helm template result preview: The IDE can now preview the result of the Helm template rendering in the diff. Helm dependency update: A new Helm Dependency Update action is available to download the external tgz dependencies (or update the existing ones) and display them in the project tree. Database Updates Added support for Cassandra database: With this release, the team has added support for the NoSQL database, Cassandra. Improvements in SQL code completion: Now code completion works for: non-aggregated fields in GROUP BY, all the columns are listed in SELECT, MERGE, and INSERT INTO table variable, named parameters of stored procedures, numeric fields in SUM() and AVG(), FILTER (WHERE) clause, and field types in SQLite. Introduction to table alias: One can now use the Introduce table alias action to create an alias directly on the table, and this alias will automatically replace usages of the table’s name. Single connection mode: In IntelliJ IDEA 2018.3 users can view any temporary objects in the database tree. Also, it’s possible to use the same transaction in different consoles. To know more about these and other updates in detail, visit the JetBrains blog. IntelliJ IDEA 2018.3 Early Access Program is now open! What’s new in IntelliJ IDEA 2018.2 How to set up the Scala Plugin in IntelliJ IDE [Tutorial]  

Yesterday, Bob Davis, Senior Product Manager at Red Hat announced that Clang/LLVM, Go, and Rust will now enter “Full Support Phase”. The support lifecycle is changed after the General Availability (GA) of Clang/LLVM 6.0, Go 1.10, and Rust 1.29. Previously, these languages and tools were in “Technology Preview” status. They were provided for users to test their functionality and provide feedback. This was during the development process and there was no full supported under the Red Hat Subscription Level Agreements. They were not guaranteed to be functionally complete and were not intended for live production use. GA means that these products have now officially entered a phase to receive full support. Their website states that: “During the Full Support Phase, qualified Critical and Important Security errata advisories (RHSAs) and Urgent and Selected High Priority Bug Fix errata advisories (RHBAs) may be released as they become available. Other errata advisories may be delivered as appropriate.” On availability, support for new hardware and some enhanced software functionality may also be provided at the sole discretion of Red Hat. These are generally in minor releases. The minor releases will focus only on resolving defects/bugs. New installation images of the minor releases will be provided during this full support phase. As these packages are evolving fast, the support lifecycle will also have short intervals. This means that there will be quarterly updates to Rust, and updates every 6 months to LLVM and Golang. The support for them will be different than the usual long-term support LTS approach. For LLVM, Rust, and Go only the most recent build will be maintained. If an older version has a bug, the most recent build will be updated to fix it. If a bug is present in the current build, it will be addressed in the next scheduled build. That will be the next schedules minor release. For more details, visit the Red Hat Blog. The LLVM project is ditching SVN for GitHub. The migration to Github has begun. Golang just celebrated its ninth anniversary Rust 1.30 releases with procedural macros and improvements to the module system

In October, Kotlin’s framework Ktor 1.0 beta was released. It delivered high performance and an idiomatic API. Yesterday Ktor 1.0 was released as the first major version of the Kotlin-based framework. Ktor, a JetBrains project, builds asynchronous servers and clients in connected systems coroutines and also delivers good runtime performance. Ktor version 1.0 includes few essential features like sessions, authentication, JSON serialization, popular template engines, Web sockets, metrics, and many others. Ktor 1.0 feature highlights Ktor 1.0 has two main parts, namely, HTTP server framework and a multiplatform HTTP client. HTTP server framework The HTTP server framework built on Netty, Jetty and Java servlets runs on the JVM. Netty and Jetty, the lightweight engines make the processing faster as it helps in receiving connections within a second. It is container-friendly and can easily be embedded into desktop/Android applications. It could be run in an application server, for example,Tomcat. Multiplatform HTTP client Multiplatform HTTP client is asynchronous and is built using coroutines and IO primitives which are responsible for driving the server. It is implemented as a multiplatform library. The client is used for building asynchronous microservice architectures and for connecting all the backend functionalities into asynchronous pipelines. The multiplatform HTTP client makes it easy to retrieve data without blocking application execution on mobile devices and web pages uniformly. It supports JVM, JS, Android and iOS. Features Ktor’s built-in support for serving static content is useful for serving style sheets, scripts, images, etc. Ktor provides a mechanism for constructing URLs and reading the parameters to create routes in a typed way. Ktor’s Metrics feature helps in configuring the Metrics to get useful information about the server and the requests. It also has a mechanism called session useful for persisting data between different HTTP requests. Session also helps servers to keep a piece of information associated with the client during a sequence of HTTP requests and responses. Ktor’s Compression feature is used for compressing outgoing content using gzip, deflate or custom encoder. This helps in reducing the size of the response. Ktor provides Call Logging feature which is used for logging client requests. Ktor 1.0 introduced WebSockets mechanism to keep a bi-directional, real-time and ordered connection between the server and the client. Major improvements Ktor 1.0 comes with improved performance and documentation It uses Kotlin 1.3.10 Ktor 1.0 has fixed client response cancelation via receive<Unit>() and response.cancel() In Ktor 1.0 there are improvements to test client and mock engine The DevelopmentEngine has been renamed to EngineMain There is an improved serialization client feature Bug fixes Fixes to Cookies dates, domains, and dupicate parameters processing. Websocket session lifecycle has been fixed in Ktor 1.0 Timeouts in WebSockets have been fixed with jetty To know more about this news, check out the announcement on Jetbrains blog. Kotlin 1.3 released with stable coroutines, multiplatform projects and more How to avoid NullPointerExceptions in Kotlin [Video] Implementing Concurrency with Kotlin [Tutorial]

Last week Microsoft announced that developers using Visual Studio now have access to officially supported SDK and tools for creating 64-bit ARM (ARM64) apps. The Microsoft Store is now also accepting submissions for apps built for the ARM64 architecture. Lenovo and Samsung are coming up with new Windows 10 ARM devices featuring the Qualcomm Snapdragon 850 chip. An x86 emulation layer lets these devices run Windows applications. Developers can use Visual Studio 15.9 to recompile apps both on UWP and C++ Win32. These apps can run natively on ARM devices running Windows 10. Running natively allows the applications to take complete advantage of the processing power and capabilities of Windows 10. This results in the best possible experience for users. Instructions to enable Windows 10 64-bit ARM apps support You need to update your Visual Studio to version 15.9. Ensure that you have installed the individual component “Visual C++ compilers and libraries for ARM64” if you plan to build ARM64 C++ Win32 apps. ARM64 will be seen as an available build configuration after updating for new UWP projects. For existing projects and C++ Win32 projects, an ARM configuration needs to be added to the project. This can be done via the Configuration properties in Configuration Manager. Add a new Active solution platform and name it ARM64. Then copy the settings from ARM or x64 and check the box to Create new project platforms. Hitting build should ready the ARM binaries. You can use remote debugging to debug your app. This is fully supported on ARM64. You can alternatively create a package for sideloading or directly copy binaries to run the app. The Windows Store is now accepting ARM64 UWP apps, both on C++ and .NET Native. You can also use the Desktop Bridge to wrap ARM64 binaries into a package to submit to the Windows Store. You can also host dedicated ARM64 versions of Win32 apps on your own website or integrate ARM64 into existing multi-architecture installers. For more instructions, visit the Windows Blog. Another bug in Windows 10 October update that can cause data loss Microsoft announces .NET standard 2.1 Microsoft bring an open-source model of Component Firmware Update (CFU) for peripheral developers

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After the GitHub Octoverse report last month, GitHub released an analysis of the top programming languages of 2018 on its platforms. There are various ways to rank the popularity of a programming language. In the report published on the GitHub Blog, the number of unique contributors to both public and private repositories tagged with the primary language was used. In addition, the number of repositories tagged with the appropriate primary programming language was also used. JavaScript is the top programming language by repositories The most number of repositories are created in JavaScript. The number of repositories created has a steady rise from 2012. Around this time, GitHub was housing nearly 1 million repositories in total. New JavaScript frameworks like Node.js were launched in 2009. This made it possible for developers to create client and server sides with the same code. Source: GitHub Blog JavaScript also has the most number of contributors JavaScript tops the list for the language having the most number contributors in public and private repositories. This is the case for organizations of every size in all regions of the world. New languages have also been on the rise on GitHub. In 2017, TypeScript entered the top 10 programming languages for all kinds of repositories across all regions. Projects like DefinitelyTyped help in using common JavaScript libraries with TypeScript which encourages its adoption. Some languages have also seen a decline in popularity. Ruby has sunk in the charts over the last couple of years. Even though the number of contributors in Ruby is on the rise, other languages like JavaScript and Python have grown faster. Newer projects not likely to be written in Ruby. This is especially true for projects owned by individual users or small organizations. Such projects are likely written in popular languages like JavaScript, Java, or Python. Source: GitHub Blog Languages by contributors in different regions Across regions, there haven’t been many variations in languages used. Ruby is at the bottom for all regions. TypeScript ranks higher in South America and Africa compared to North America and Europe. The reason could be the developer communities being relatively new in Africa and South America. The repositories in Africa and South America were younger than the repositories in North America and Europe. Fastest growing language by contributors PowerShell is climbing the list. Go also continues to grow across repository type with rank 7. It’s rank is 9 for open source repositories. Statically-typed languages which focus on type safety and interoperability like Kotlin, TypeScript, and Rust are growing quickly. So what makes a programming language popular on GitHub? There are three factors for top programming languages to climb ranks—type safety, interoperability, and being open source. Type safety: There’s a rise in static typing except for Python. This is because of the security and efficiency static typing offers individual developers and teams. The optional static typing in TypeScript adds safety. Kotlin, offers greater interactivity while creating trustworthy, type-safe programs. Interoperability: One of the reasons TypeScript climbed the rankings was due to its ability to coexist and integrate with JavaScript. Rust and Kotlin which are also on the rise, find built-in audiences in C and Java, respectively. Python developers can directly call Python APIs from Swift which displays its versatility and interoperability. Open source: These languages are also open source projects with active commits and changes. Strong communities that contribute, evolve, and create resources for languages can positively impact its life. For more details and charts, visit the GitHub Blog. What we learnt from the GitHub Octoverse 2018 Report Why does the C programming language refuse to die? Julia for machine learning. Will the new language pick up pace?

Dart 2.1, an increment over Dart 2 is released with changes for performance and usability. New features in Dart 2.1 include smaller code size, faster type checks, better usability for type errors, and new language features to improve productivity. Support for int-to-double conversion in Dart 2.1 Developers new to Flutter often face obstacles in the form of analysis errors when specifying padding, setting font sizes, etc. These errors make sense from a system point of view. For example, the API expects a type say, a double, and the developer specifies the value in a different type say, an int. From a usability point of view, it seems foolish as there is a trivial conversion from int to double. So, Dart 2.1 now infers the line where applicable and silently evaluates an int as a double. Language support for mixins in Dart 2.1 Dart 2.1 comes with a new syntax for mixins. It features a new mixin keyword that can be used to define classes which can exclusively be used as mixins. Support is also added so that mixins can extend other classes and invoke methods in their superclass. Previously, mixins could only extend Object. An example of extending non-Object classes is from Flutter’s animation APIs. The SingleTickerProviderStateMixin which is a framework class that provides a ticker for advancing an animation by a single frame declares a mixin that implements the general TickerProvider interface. The animations are applicable only to stateful widgets since the position in the animation is considered state. The new mixin support in Dart 2.1 allows expressing this by declaring that only classes that extend the Flutter State class can use the mixin. Compile-time type checks The type system in Dart 2 protects users during development, indicating violations of the contract specified by the types. Such checks at edit time were added in Dart 2 powered by the Dart Analyzer. There is another place where developers might expect type checks. Like compile time, when performing a Flutter release build. Such checks were incomplete in Dart 2, which potentially leading to usability issues where bad source code could compile without errors. In Dart 2.1, these checks are complete. Now, the Analyzer and Dart compiler both contain the same checks. Performance improvements for Flutter developers In a few cases, though, the comprehensive checks in Dart 2 caused undesirable overheads of 20–40%. Dart 2.1 has greatly reduced cost of type checks. This is applicable to both, AOT-compiled code and code run in the VM with JIT compilation. The developer tools which run using the VM, benefit from this. Performing code analysis of one large benchmark app used to take about 41 seconds, it now takes only around 25 seconds. Performance improvements for web developers The code size and compile time is also improved for Dart code running on the web. The output size of dart2js were in focus. This yielded good results, such as a 17% reduction in minified output size and a 15% improvement in compilation time in one of the tested samples. Other changes There are also some changes made outside the core Dart SDK. One is protocol buffers (protobuf) which are a platform-neutral mechanism for serializing structured data. Dart is now an officially protobuf supported language. They have created a small sample for knative—a platform based on Kubernetes for building, deploying, and managing serverless workloads. For more details, visit the Dart Blog post. Google’s Dart hits version 2.0 with major changes for developers C# 8.0 to have async streams, recursive patterns and more Golang just celebrated its ninth anniversary