ng generate – Starting Projects the Right Way

ng build The ng build command is intended to prepare your application bundle to be executed by the production web server of your choice. It performs a series of optimizations

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ng add – Starting Projects the Right Way

This command has the function of adding an Angular library to your project. You might be wondering, Doesn’t npm install do the same thing? and you’d be right. However, when

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Angular Language Service – Starting Projects the Right Way

Configuring your development environment A well-organized environment with the right tools is the first step toward excellence and productivity; now, let’s set this environment up in your workspace. After installing

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Karma and Jasmine – Starting Projects the Right Way

TypeScript TypeScript is a superset of the JavaScript language that adds type checking and other features to the language, ensuring a better developer experience and security for web development. It

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Google support – Starting Projects the Right Way

Angular was created and maintained by the Angular team at Google. Although excellent frameworks such as Vue.js and Svelte are maintained only by their communities, having such a big tech

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CROSS-COMPILING ON OTHER SYSTEMS – Beyond Instruction Selection

Some distributions, such as Fedora, only provide cross-compiling support for bare-metal targets such as the Linux kernel, but the header and library files needed for user land applications are not

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Targeting a different CPU architecture – Beyond Instruction Selection

Today, many small computers, such as the Raspberry Pi, are in use despite having only limited resources. Running a compiler on such a computer is often not possible or it

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Implementing the toolchain support for M88k within clang – Beyond Instruction Selection-2

StringRef m88k::getM88kTargetCPU(const ArgList &Args) {Arg *A = Args.getLastArg(options::OPT_m88000, options::OPT_m88100, options::OPT_m88110, options::OPT_mcpu_EQ);if (!A)return StringRef();switch (A->getOption().getID()) {case options::OPT_m88000:return “mc88000”;case options::OPT_m88100:return “mc88100”;case options::OPT_m88110:return “mc88110”;case options::OPT_mcpu_EQ:return normalizeCPU(A->getValue());default:llvm_unreachable(“Impossible option ID”);}} StringRef m88k::getM88kTuneCPU(const ArgList &Args) {if

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Implementing ABI support for M88k within clang – Beyond Instruction Selection

Now, we need to add ABI support within the frontend for clang, which allows us to produce code specific to the M88k target from the frontend: std::unique_ptr createM88kTargetCodeGenInfo(CodeGenModule &CGM); Now,

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Implementing the driver integration within clang – Beyond Instruction Selection-3

bool M88kTargetInfo::setCPU(const std::string &Name) {StringRef N = Name;CPU = llvm::StringSwitch(N).Case(“generic”, CK_88000).Case(“mc88000”, CK_88000).Case(“mc88100”, CK_88100).Case(“mc88110”, CK_88110).Default(CK_Unknown);return CPU != CK_Unknown;} static constexpr llvm::StringLiteral ValidCPUNames[] = {{“generic”}, {“mc88000”}, {“mc88100”}, {“mc88110”}};void M88kTargetInfo::fillValidCPUList(SmallVectorImpl &Values) const {Values.append(std::begin(ValidCPUNames),

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