Getting Started with STLport — Installation & Quick Examples

STLport: A Lightweight STL Implementation for Embedded C++Embedded C++ development often runs up against tight constraints: limited RAM and flash storage, lack of a full operating system, and sometimes an incomplete or nonstandard C++ runtime. Standard Template Library (STL) features—containers, iterators, algorithms, and functors—are invaluable for writing clear, generic, and maintainable code, but mainstream STL implementations (libstdc++, libc++, MSVC STL) can be too heavy or depend on platform features unavailable on microcontrollers and deeply embedded platforms. STLport is an alternative: a portable, lightweight STL implementation designed to make many STL features available in constrained environments.

This article explains what STLport is, why it can be a good fit for embedded projects, how it differs from other STL implementations, practical considerations for using it on constrained hardware, and migration and troubleshooting tips.

What is STLport?

STLport is a C++ Standard Template Library implementation that focuses on portability, compactness, and configurability. It was created to be usable across a wide range of compilers and platforms, including older or nonconforming compilers and embedded toolchains. STLport implements core STL components—containers (vector, list, deque, map, set), iterators, algorithms (sort, find, transform, etc.), allocators, string and iostream-like utilities—while offering configuration knobs to reduce footprint and adapt behavior to platform capabilities.

While STLport’s active development status is lower than modern mainstream libraries, it remains a practical choice in legacy or resource-constrained systems where newer library implementations are unavailable or too heavy.

Why use STLport for embedded C++?

• Small footprint and configurable features: STLport was designed to be trimmed. You can disable iostreams, locale support, and other optional subsystems to save memory and code size—important on microcontrollers with kilobytes of RAM/ROM.
• Broad compiler compatibility: It supports older and nonstandard compilers more readily than modern implementations which assume full C++11/14/17 support.
• Predictable behavior: STLport has mature, stable semantics for containers and algorithms; in embedded contexts this predictability matters for correctness and certification.
• Ease of porting legacy code: If you maintain or import older C++ code that expects classical STL behavior, STLport can reduce integration friction.
• Configurable allocators: Embedded systems often need custom allocation strategies. STLport can be built to work with custom allocator models (pool allocators, region-based, or static memory).

How STLport differs from modern STL implementations

• Modern libraries (libstdc++, libc++) are tightly integrated with current compilers, support the latest C++ standards, and are optimized heavily for performance on desktop/server hardware. They also implement many heavyweight features (locale, iostreams, regular expressions, threading support) which increase size.
• STLport focuses on portability and minimalism, not on providing the entire modern C++ feature set. It is typically compatible with older language standards (C++⁄₀₃) and may lack many C++11+ features.
• STLport’s configuration system lets you exclude optional modules; mainstream STL implementations usually build monolithically as part of the standard library shipped with the toolchain.
• For most embedded uses you need only a subset of STL functionality (containers + algorithms + simple string handling); STLport makes it simpler to include only what you need.

Key components and configurable options

The exact build and configuration options depend on the STLport version, but typical configurable areas include:

• Containers (vector, list, deque, map, set, stack, queue)
• String and basic character operations
• Algorithms (sort, partial_sort, for_each, transform)
• Allocators and memory model selection
• I/O stream subsystem (can be disabled to save space)
• Locale and internationalization (usually disabled on embedded)
• Exception handling support (some builds support compiling without exceptions)
• Debugging and iterator debugging checks (optional; toggle for release builds)

Selecting which subsystems to include is the main way to control code size and runtime footprint.

Practical integration steps for embedded projects

1. Evaluate requirements:

   • Which containers and algorithms does your project actually use?
   • Do you need iostreams, locales, exceptions, or RTTI?
   • What C++ standard and compiler features are available in your toolchain?

2. Build or obtain a trimmed STLport:

   • Get a source distribution or a prebuilt embedded-friendly variant.
   • Configure to disable streams/locales if not needed.
   • If your toolchain lacks proper headers, adapt the porting layer. Some embedded toolchains require small stubs for headers like or .

3. Provide or implement an allocator strategy:

   • Use a static pool allocator for deterministic behavior and zero-fragmentation.
   • If dynamic allocation is acceptable, ensure malloc/free are available or provide replacements.

4. Link and test incrementally:

   • Start with a small module using one container (e.g., vector) and verify size and correctness.
   • Use the linker’s size map to find which STL features pull in large transitive dependencies.

5. Optimize:

   • Remove RTTI or exceptions if not needed (but be aware of compatibility with language features).
   • Replace heavy usages (std::string with dynamic growth) with smaller fixed-capacity alternatives when appropriate.
   • Consider compile-time flags (e.g., -fno-exceptions) and rebuild STLport accordingly.

6. Tooling:

   • Use size analysis tools (nm, objdump, size) and link-time optimization (LTO) carefully; LTO can reduce size but sometimes increases complexity on constrained toolchains.

Memory and performance considerations

• Containers allocate memory differently; vector’s contiguous allocation is usually cache-friendly and efficient, but needs contiguous heap space. Linked lists avoid reallocation costs but increase per-element overhead.
• In constrained systems, prefer preallocated containers or custom allocators to avoid heap fragmentation.
• Avoid heavy use of std::string with frequent reallocations; prefer reserved capacity or fixed buffers.
• Algorithms are generally inlined and efficient, but template instantiation can increase code size—use only the algorithms you need.
• Use compiler optimizations (size-oriented flags such as -Os) and strip symbols for final builds.

Example: minimal workflow to get vector working

1. Configure STLport with streams and locales disabled.
2. Ensure and operator new/delete are available or provide replacements that work with your allocator.
3. Build a test program that uses std::vector, compile with -Os, link, and check the binary size.
4. If size is too large, inspect which object files pull in extra functionality and disable those subsystems or switch to a simpler allocator.

Migration tips from other STL implementations

• Map out used symbols: build with your current implementation and create a symbol list of STL types and algorithms used. Port only those to STLport.
• Replace heavy idioms (e.g., iostream-based logging) with lightweight alternatives (minimal printf wrappers, custom logging).
• If code relies on C++⁄₁₄ features not present in STLport, either backport those usages or add compatibility shims.
• Add unit tests to validate container behavior and iterator correctness on your platform.

Troubleshooting common issues

• Linker errors (missing symbols): confirm required STLport modules are built and linked; check allocator/new/delete hooks.
• Excessive size: turn off optional modules, disable debug checks, use -Os and strip.
• Compiler incompatibility: adapt small headers or use a thin compatibility layer for missing language features.
• Undefined behavior or crashes: check alignment assumptions, size_t and pointer-width assumptions, and ensure that exceptions/RTTI differences are accounted for.

Alternatives and when to choose them

• If your toolchain supports modern libstdc++ or libc++ and size isn’t a dominant constraint, prefer those for C++11+ feature support and active maintenance.
• For very small systems where even trimmed STL is too large, consider:
  • Abstractions implemented as C-style APIs with hand-rolled containers.
  • Header-only, minimal libraries designed for embedded (e.g., EASTL by EA for games, or really small single-header containers).
  • Custom fixed-size container classes.
• If you need modern C++ features (move semantics, constexpr, type traits), consider porting to a more current standard library or using microcontrollers toolchains that provide them.

Final thoughts

STLport fills a niche: it provides mature, portable STL facilities in environments where modern standard libraries are unsuitable due to size, lack of toolchain support, or legacy constraints. For embedded projects that need familiar STL semantics but must conserve memory and code size, a carefully configured STLport can provide a good balance of functionality and footprint. However, evaluate the tradeoffs—lack of modern C++ feature support and less active maintenance—and consider alternatives if you need up-to-date language features or long-term support.