fidzu : LISP

Lately I've been playing with writing a chatbot library in Common Lisp.

My previous gemini bindings were getting unweildy. I wanted to add the ability to run LLMs on my local machine but it turned out to be really kind of kludgy, so I decided to start from scratch with multiple back ends in mind.

I've got it to the point where in supports multiple back ends, so now I can prompt local LLMs from Lisp.

Recently I added the ability to recursively launch chatbots that can call each other. Since the chatbots do not share their contexts, this greatly reduces the context bloat of thet main chat because it can spawn off subtasks to a minion and not pollute the main context. This also allows you to create a federation of chatbots, each of which specializes in some topic and is overseen by a controlling chatbot that talks to the user.

Chatbots can be serialized and checkpointed, so if one is carrying out an agentic task and Lisp crashes, when we restart the agentic tasks are restarted as well and pick up where they left off.

IT turns out that recursive chats are a useful abstraction once you figure out how to use them. Basically any prompt you may issue may also want to be issued by an llm and this enables that to happen. It allows you to run subprocesses that would otherwise put junk in your context, for example reading the contents of a lange number of files. If you put that into a rocursive chatbot, it could slurp up the files into its context without adding tokens to the parent chat.

You can use a recursive chat as a `smart component'. The recursive chat can have a specialized system instruction and can preload its context with relevant information specific to it. It's context doesn't get diluted by the caller's context

28 Jun 2026 10:52pm GMT

I saw that there was some argument over how much slower slot access is than struct access, so I just decided to measure it naively. I made a two slot sruct and a CLOS version of a CONS cell with car and cdr slots and I ran LTAK using regular lists, `lists' made from CLOS conses, and `lists' made from structs. Here are the results:

D:\repositories\clos-benchmark>sbcl --script run-benchmarks.lisp
Benchmark: ltak over native cons cells, CLOS my-cons nodes, and my-cons-struct nodes
Inputs: x=15 y=9 z=4 repeats=35

Scenario                   min-ms     mean-ms      max-ms      ratio
--------------------------------------------------------------------
native standard               0.129      0.146      0.186
clos standard                 1.346      1.365      1.475       9.37x
struct standard               0.172      0.175      0.179       1.20x
native optimized              0.068      0.069      0.073
clos optimized                0.411      0.414      0.419       6.04x
struct optimized              0.068      0.069      0.073       1.01x

In this naive use case, structs are same as native cons cells, but CLOS objects are one ninth the speed of a struct or cons cell if you just use it unoptimized, and one sixth the speed if optimizations are turned on.

But the CLOS instance is more functional than the cons cell in mimics. For instance, I could add a slot to the class and all the instances would be lazily updated with the new slot. I can also subclass the CLOS class and the selector functions will continue to work. Finally, I can redefine the CLOS closs while I'm developing it and all the instances will be uppdated. THe machinery to keep all this running is costing us our factor of 9.

But this might be worth the cost if we are running on a network where the bulk of the time will be transmitting the answer down the pipe once it is computed. Taking a few extra milliseconds to compute the answer might be worth the convenience features of CLOS.

25 Jun 2026 4:11pm GMT

Back in the day, the US government had a program called SBIR (Small Business Innovation Research) that funded small businesses to do research and development. I recall sitting in our dorm in college, reading through a giant printed catalog of SBIR grants just to amuse ourselves by brainstorming solutions over bad pizza.

.

So, I got curious the other day: what does the SBIR landscape look like now?

I can tell you right now: do not even try to read an SBIR solicitation on your local machine. You are opening yourself up to a world of absolute, unmitigated pain.

You might think, what harm could there be in simply opening a file?

Well, in the modern compliance panopticon, any manipulation of digital information that comes from the govenment has the potential to spawn CUI (Controlled Unclassified Information). CUI is basically a digital pathogen; once you download that file, *anything whatsover* derived from it, including notes and metadata, instantly becomes CUI by association. The moment you read an SBIR on your computer, you've infected your system, rendering you subject to a nightmare of Byzantine federal regulations.

These days, the amount of beurocratic red tape surrounding CUI is insane. To even look at the file legally, you need a dedicated, air-gapped machine completely disconnected from the internet, conforming to a massive, expensive slew of NIST standards covering everything from hardware-level encryption to strict access controls. Alternatively you could contract with a cloud company that offers a pre-certified "CUI-compliant" environment.

And assuming you actually shell out the cash and jump through the hoops to set up this digital containment zone just to read a PDF, you must meticulously audit and account for every single action you take in its presence. Under current federal auditing logic, you are explicitly assumed to be attempting to defraud the government unless you can produce a mountain of paper proving otherwise. Want to bring in a partner to bounce ideas around? You can't just "know a guy." You have to navigate a labyrinth of federal subcontracting regulations.

I had intended on amusing myself by reading some SBIRs and daydreaming about solutions that might involve Lisp (an impossibility in the modern enterprise stack for entirely separate, depressing reasons). Instead, I quickly discovered I did not even own the physical hardware required to even read an SBIR without running afoul of federal regulations.

I wanted to read some clever and inspiring engineering proposals. I ended up reading a lot of very dry and boring compliance regulations.

18 Jun 2026 11:48am GMT

Last year I wrote some Lisp related AI apps. There was a syntax highlighter that used the LLM to determine how to colorize and highlight syntax, and a prompt refiner that takes a wimpy LLM prompt and creates more elaborate prompt from them.

I took the apps down last week. They were `vibe coded' and therefore approximate and had bugs (but that's to be expected), but they had a security hole where you could hijack the LLM processing with your own prompt turning my app into an open relay using my API key. Last week I discovered that my AI spend on video creation was becoming serious. This is odd because I never create AI video. It turned out that my app was being hijacked by a proxy in Luxembourg and was generating videos on my dime.

So I shut down the apps. I knew they had the potential of being abused, and I was willing to tolerate a small amount of abuse, but it didn't occur to me that syntax highlighter could be hijacked to generate gigabytes of video at my expense. Future applications will be careful to obtain the API key from the user.

01 Jun 2026 7:00am GMT

Metaobject Protocol (MOP) Implementation in CLRHack

The Metaobject Protocol in CLRHack is a high-performance implementation of the Common Lisp Object System (CLOS) integrated into the .NET 8.0 Common Language Runtime (CLR). It provides a complete meta-compilation pipeline that bridges the gap between dynamic Lisp semantics and the static CIL (Common Intermediate Language) execution model.

Core Architecture

The MOP is implemented through three primary layers:

1. The Metaobject Hierarchy (C#): A set of foundational classes in LispBase representing classes, methods, generic functions, and slot definitions.
2. The Runtime Engine (MopRuntime): A centralized orchestrator that manages class finalization, method combination, dispatch caching, and instance allocation.
3. The Compiler Bridge (Lisp): Transformations in ast.lisp that translate high-level CLOS forms (defclass, defmethod) into optimized runtime calls.

Instance Representation

Because the CLR type system is strictly single-inheritance and statically defined, CLRHack decouples Lisp-level inheritance from C# inheritance. All CLOS instances are represented by the StandardObjectInstance class, which contains:

• A reference to its ClassMetaobject.
• A private object[] storage array for instance slots, indexed by locations calculated during class finalization.

The Dispatch Pipeline

Generic function invocation is the most complex part of the implementation. When a generic function is called:

1. Cache Lookup: The DiscriminatingFunction first checks a thread-safe dispatchCache using an InvocationCacheKey (a stack-allocated struct) to find a previously computed effective method.
2. Applicability & Precedence: If the cache misses, the runtime computes all applicable methods and sorts them based on specializer specificity and the Class Precedence List (CPL).
3. Method Combination: The ComputeEffectiveMethod logic builds a nested execution chain following the Standard Method Combination rules:
   • :around methods are called first, with call-next-method progressing to the next around method or the main chain.
   • The main chain executes all :before methods, the primary method, and finally all :after methods in reverse order.
4. Fast Invocation: The resulting effective method is compiled into a Func<object[], object> that uses direct delegate invocation to minimize overhead.

Challenges and Solutions

1. Thread-Safe Non-Local Exits (call-next-method)

Challenge: call-next-method and next-method-p require access to the current invocation's state (the remaining methods and original arguments). Passing this state through every function call would break compatibility with standard Lisp function signatures.

Solution: CLRHack utilizes [ThreadStatic] fields in MopRuntime to store the currentNextMethods and currentArguments. This ensures that even in highly concurrent environments (like a web server), each OS thread has its own isolated invocation context, allowing call-next-method to function correctly without state leakage.

2. Forward References and Lazy Finalization

Challenge: Lisp allows classes to refer to superclasses that haven't been defined yet. The runtime must handle these "zombie" classes without crashing the JIT compiler.

Solution: The system implements a ForwardReferencedClassMetaobject. When a class is defined, it is automatically finalized (computing its CPL and slot layout). If a superclass is missing, a forward reference is created. The EnsureFinalized protocol ensures that inheritance is resolved and slot locations are assigned the moment the class is first instantiated or used in dispatch.

3. Performance Overhead of the "MOP Bridge"

Challenge: A naive implementation of slot-value or generic dispatch using C# reflection or linear searches is orders of magnitude slower than native C# member access.

Solution: Three distinct optimizations were applied:

• O(1) Slot Access: Each ClassMetaobject maintains a SlotDictionary. Slot names are mapped to physical array indices during finalization, allowing slot-value to perform a direct array access after a single dictionary lookup.
• Compiler Primitives: The compiler identifies SLOT-VALUE and MAKE-INSTANCE calls and emits direct CIL call instructions to optimized Lisp.MopRuntime methods, bypassing the general Funcall path.
• Zero-Allocation Cache Hits: By making InvocationCacheKey a readonly struct and avoiding the cloning of the argument array during cache probes, the hot-path for generic function dispatch generates zero garbage for the .NET Collector.

4. Bootstrapping the COMMON-LISP Package

Challenge: Core CLOS functions like make-instance must be available as symbols in the COMMON-LISP package before user code runs, but they rely on the MOP runtime being fully initialized.

Solution: A MopRuntime.Initialize() method is injected into the entry point (Main) of every generated assembly. This method interns the necessary symbols and binds them to GenericFunctionClosureAdapter objects, ensuring that the MOP is "alive" before the first line of Lisp code executes.

---

Vibe coding the MOP basically involved feeding chapters 4 and 5 of the Art of the Meta-Object Protocol into the LLM and telling it to make an implementation plan. It came up with a twenty-step plan to bootstrap CLOS. I then spent the rest of the day instructing an agent to take on each task of the twenty-step plan in sequential order. At the end of the day, I had a working MOP

This is the end of my series of posts on CLRHack.

31 May 2026 7:00am GMT

Implementation of SIGNAL and ERROR in CLRHack

In CLRHack, the condition signaling system is implemented in the Lisp.HandlerControl class within the LispBase library. It leverages .NET's [ThreadStatic] storage to maintain a per-thread dynamic stack of active condition handlers.

SIGNAL Implementation

The Signal(object condition) method performs the following logic:

1. Retrieval: It fetches the activeHandlers list for the current thread. This list is a chain of [LispBase]Lisp.Handler objects maintained by handler-bind.
2. Iteration: It iterates linearly through the list from the most recently bound handler to the oldest.
3. Type Matching: For each handler, it calls IsType(condition, handler.ConditionType).
   • If the condition is a symbol, it checks for symbol equality (supporting simple symbol-based conditions).
   • If the condition is a .NET object, it checks if the handler's type is assignable from the condition's runtime type (supporting interop with system exceptions).
   • It treats the symbols T or EXCEPTION as catch-all types.
4. Handler Invocation: If a match is found:
   • Recursive Signal Protection: Before calling the handler function, the current handler list is temporarily shadowed. activeHandlers is set to cell.rest (the handlers bound outside the current one). This ensures that if the handler itself calls signal, it won't trigger itself recursively.
   • Execution: The handler's Closure is invoked with the condition object as its argument.
   • Restoration: A finally block ensures the original activeHandlers list is restored if the handler returns normally.

   ERROR Implementation

   The Error(object condition) method build upon Signal:

   1. Signaling Pass: It first invokes Signal(condition). If a handler performs a non-local exit (e.g., via handler-case), the Error method never returns.
   2. Debugger Entry: If Signal returns normally (meaning all handlers declined), Error calls EnterDebugger(condition).
   3. Interactive Debugging: The debugger:
      • Prints the condition and a list of available restarts (retrieved via RestartControl.GetActiveRestarts()).
      • Provides a prompt for the user to select a restart, launch the system-level debugger (Visual Studio/Rider), or abort.
      • If a restart is selected, it is invoked interactively (potentially gathering arguments from the user).
   4. Final Fallback: If the debugger is exited without invoking a restart, Error throws a C# Exception to ensure that execution does not continue on an invalid path.

   Notable Implementation Decisions and Edge Cases

• Handler Shadowing: The decision to pop the handler list during invocation is critical for maintaining Common Lisp semantics. It prevents infinite loops and ensures that "outer" handlers can handle errors raised within "inner" handlers.
• Unified Exception Model: CLRHack attempts to unify Lisp conditions and .NET exceptions. IsType allows Lisp handlers to catch C# exceptions by their class name or Type object.
• Thread Isolation: By using [ThreadStatic] for activeHandlers, CLRHack ensures that condition signaling is thread-safe. One thread signaling an error will not interfere with the handler state of another thread.
• Debugger Capability: The SYSTEM-DEBUGGER option in EnterDebugger is a bridge to the underlying .NET environment, allowing developers to use professional IDE tools to inspect the state of the Lisp VM when an unhandled error occurs.

signal and error complete the Common Lisp condition system implementation for CLRHack

30 May 2026 7:00am GMT

In the CLRHack compiler, handler-bind is a primitive form used to register condition handlers in the dynamic environment. It operates by managing a thread-local list of active handler objects, ensuring that condition signaling follows the standard Common Lisp search and execution rules.

Handling of handler-bind

When the compiler processes a handler-bind form, it generates CIL code that performs the following steps:

1. Capture Previous State: It calls Lisp.HandlerControl::GetActiveHandlers() to retrieve the current list of active handlers and stores it in a frame-local variable.
2. Construct New List: For each binding, it evaluates the condition type and the handler function (which is typically a closure). It instantiates a new [LispBase]Lisp.Handler object and conses it onto the current handler list.
3. Install New State: It calls Lisp.HandlerControl::SetActiveHandlers(new_list) to update the dynamic environment for the current thread.
4. Protected Execution: The body of the handler-bind is wrapped in a CIL .try block.
5. Restoration: A finally block is emitted that calls SetActiveHandlers with the saved list. This ensures that handlers are properly uninstalled, regardless of whether the body completes normally, signals an error, or performs a non-local exit.

Lexical Non-Local Exits

Handlers in Common Lisp are executed in the dynamic environment of the signaller but have lexical access to the environment where they were defined. In CLRHack, if a handler function performs a non-local exit (such as a throw or return-from), the compiler utilizes its exception-based jump mechanism:

• If the exit is a throw, it uses the standard CatchThrowException mechanism.
• If the exit is a return-from to a block outside the handler closure, the compiler identifies this as a non-local exit during analyze-environment. It compiles the return-from into a throw of a BlockExitException, which is subsequently caught by the try/catch frame established by the target block.

Handler Search

The handler search is performed at runtime by the signal or error functions. These functions retrieve the active handlers list via HandlerControl.GetActiveHandlers() and iterate through them. For each handler, the runtime checks if the signaled condition is of the type (or a subtype of the type) the handler was registered for. If a match is found, the handler function is invoked. If the handler returns normally (declines), the search continues with the next applicable handler.

Dynamic Tags

The handler-bind implementation itself relies on the dynamic state of the thread-local activeHandlers list. However, when used in conjunction with handler-case, unique dynamic tags (typically fresh ListCell objects) are generated. These tags are used as the "target" for the throw performed by the handler, ensuring that the control flow returns exactly to the correct handler-case frame and doesn't conflict with other active handler or catch frames.

handler-case as an Extension of handler-bind

In CLRHack, handler-case is not a primitive but a macro that expands into a combination of block, catch, and handler-bind. It extends handler-bind by providing a mechanism to automatically exit the signaling context and execute a specific branch of code based on the condition caught.

The implementation details of the expansion are as follows:

• Exit Block: The entire form is wrapped in a block with a unique exit tag to allow the normal path to return immediately upon completion of the protected expression.
• Dynamic Setup: A unique dynamic tag is created for the catch frame. Local variables are established to store the captured condition and a unique ID identifying which clause was triggered.
• The Binding: A handler-bind is generated where each handler function is a closure that, when called:
  1. Saves the signaled condition into the local condition-var.
  2. Sets the id-var to a unique GENSYM representing that specific clause.
  3. Performs a throw to the dynamic tag.
• The Catch and Dispatch: A catch block surrounds the protected expression. If a handler performs the throw, the catch returns, and a cond statement (the dispatcher) checks the id-var. It then executes the body of the matching handler-case clause with the condition variable bound to the clause's parameter.

29 May 2026 7:00am GMT

In the CLRHack compiler, restart-bind is a primitive form that manages the dynamic lifecycle of Common Lisp restarts by manipulating a thread-local stack of active restart objects.

Handling of restart-bind

When the compiler encounters a restart-bind form, it generates CIL code that performs the following steps:

1. Capture Previous State: It calls Lisp.RestartControl::GetActiveRestarts() to retrieve the current list of active restarts and stores it in a frame-local variable.
2. Construct New List: For each binding, it evaluates the restart name, handler function, and optional keyword arguments (:report-function, :interactive-function, :test-function). It then instantiates a new [LispBase]Lisp.Restart object and conses it onto the existing list.
3. Install New State: It calls Lisp.RestartControl::SetActiveRestarts(new_list) to update the dynamic environment.
4. Protected Execution: The body of the restart-bind is wrapped in a CIL .try block.
5. Restoration: A finally block is emitted that restores the previously saved restart list using SetActiveRestarts, ensuring that restarts are properly uninstalled even if the body performs a non-local exit.

Lexical Non-Local Exits

The CLRHack compiler supports lexical non-local exits (e.g., return-from or go) through an exception-based mechanism. During the analyze-environment pass, the compiler identifies if a return-from target block is "non-local" (i.e., the return occurs within a nested closure). If so:

• The target block is wrapped in a try/catch for [LispBase]Lisp.BlockExitException.
• The block is assigned a unique string ID.
• The return-from form is compiled into a throw of a BlockExitException, which carries the target ID, the return value, and a captured array of multiple return values (retrieved via Lisp.Values::CaptureValues()).
• The catch handler verifies the target ID. If it matches, it restores any captured multiple values and resumes normal execution; otherwise, it rethrows the exception.

Restart Search

The search for an applicable restart is handled at runtime by Lisp.RestartControl::FindRestart. It performs a linear search through the current thread's activeRestarts list (stored in a [ThreadStatic] field). It can accept either a symbol name or a Restart object itself. If a name is provided, the search respects shadowing, returning the innermost (most recently bound) restart with that name.

Dynamic Tags

Dynamic tags are required for the catch and throw forms used in non-local control flow. In CLRHack, a dynamic tag is simply a fresh object (typically a ListCell or a new System.Object) used as a unique token. This ensures that a throw only matches the specific catch frame it was intended for, avoiding collisions between different invocations of the same function or different restart-case blocks.

restart-case as an Extension of restart-bind

In CLRHack, restart-case is implemented as a macro that expands into a combination of block, catch, and restart-bind. It extends the basic binding functionality by providing a built-in mechanism to jump back to the site of the restart-case when a restart is invoked.

The implementation details are as follows:

• Exit Block: The entire expansion is wrapped in a (block exit_tag ...) to allow normal completion of the expression.
• Dynamic Tag: A unique dynamic tag is created (e.g., (let ((tag (list nil))) ...)).
• Catch Frame: A (catch tag ...) is established around the restart-bind and the expression.
• Binding: The restart-bind creates restarts whose handler functions are closures. When invoked, these closures capture their arguments into local variables, set a unique clause ID, and then throw to the dynamic tag.
• Dispatch: When the throw is caught, the restart-case body executes a cond or case statement. This dispatcher checks the clause ID set by the handler and executes the corresponding forms provided in the restart-case clause, eventually returning the result from the exit_tag block.

28 May 2026 7:00am GMT

Handling of unwind-protect

The CLRHack compiler maps Lisp unwind-protect semantics directly onto the Structured Exception Handling (SEH) infrastructure of the .NET Common Language Runtime (CLR). Specifically, it utilizes the try...finally construct provided by the Common Intermediate Language (CIL).

Lisp semantics require that the cleanup forms in an unwind-protect block be executed regardless of how control leaves the protected form-whether via normal return, a non-local throw, or a lexical exit like return-from. The CLR guarantees that a finally block will execute during stack unwinding, which is exactly the hook required for Lisp. The implementation details are as follows:

• Protected Form: The compiler generates the code for the protected form inside a CIL try block. Upon successful completion, the primary return value is stored in a local variable, and a leave instruction is used to exit the try block, which automatically triggers the transition to the finally block.
• Side-Channel Preservation: A unique challenge in Lisp is that unwind-protect must return the values of the protected form, but cleanup forms may themselves perform operations that alter the Multiple Return Value (MRV) side-channel. CLRHack exploits method-local variables to save the ReturnCount and the contents of Value1 through Value63 at the very beginning of the finally block and restore them at the very end.
• Unwinding: If a throw or other exception occurs within the try block, the CLR stack walker identifies the finally block and executes it before propagating the exception further. This ensures Lisp's "cleanup guarantee" is maintained even during catastrophic or non-local control transfers.

Handling of catch and throw

Lisp's catch and throw are implemented as a Dynamic Non-Local Exit system built on top of .NET's exception propagation mechanism. While CLR exceptions are typically filtered by type, Lisp requires filtering by a dynamic "tag" object (compared via eq).

The throw Mechanism

When a (throw tag value) is evaluated, CLRHack does not simply perform a jump. Instead, it performs the following steps:

1. Evaluates the tag and the primary value.
2. Captures the current state of the MRV side-channel into an object[].
3. Instantiates a specialized exception class: [LispBase]Lisp.CatchThrowException. This object acts as a carrier for the tag, the primary value, and the captured MRV array.
4. Executes the CIL throw instruction. This initiates the CLR's SEH stack walk.

The catch Mechanism

The (catch tag body) form is compiled into a try...catch block where the catch handler specifically targets CatchThrowException:

1. Tag Setup: The catch tag is evaluated and stored in a method-local variable.
2. Body Execution: The body forms are executed within a try block.
3. The Catch Handler: When a CatchThrowException is intercepted, the handler performs a "Dynamic Filter":
   • It extracts the tag from the exception object and compares it to the local catch tag using System.Object.Equals (simulating Lisp's eq for reference types).
   • Match: If the tags match, the handler "claims" the exception. It extracts the primary value and the MRV array from the exception, restores them to the thread-local side-channel, and resumes normal execution after the catch block.
   • Mismatch: If the tags do not match, the handler executes the CIL rethrow instruction. This allows the exception to continue up the stack to find a matching catch tag in a higher frame.

Exploiting SEH for Lisp Semantics

CLRHack exploits the CLR's SEH in three fundamental ways to bridge the gap between .NET and Lisp:

• Automatic Stack Unwinding: By using throw and try...catch, the compiler delegates the complex task of cleaning up stack frames, registers, and intermediate states to the highly optimized .NET runtime.
• Guaranteed Cleanup: The finally block is the "silicon reality" of Lisp's unwind-protect. The CLR ensures it runs even if an exception is re-thrown multiple times or if a thread is being terminated.
• Payload-Heavy Exceptions: Unlike standard .NET exceptions which often carry only metadata, CatchThrowException is exploited as a transport mechanism. It carries the entire "return state" of a Lisp expression (primary value + MRV side-channel) across an arbitrary number of stack frames, allowing a throw to behave exactly like a multi-valued return to a dynamic point.

27 May 2026 7:00am GMT

Common Lisp is renowned for its excellent object system CLOS. Its implementation is often accompanied by the Metaobject Protocol that, while it is not part of the standard, allows programmers to customize the system underpinnings in numerous interesting ways. This level of customization doesn't come without a cost - some CLOS code paths will be slower compared to open-coding equivalent solutions without the use of standard objects.

The purpose of this blog post is to draw an intuition of differences between structure objects and standard objects when it comes to accessing their slots. From now on I'm going to refer to structure objects as structures, and standard objects as instances.

We could imagine a structure is represented in memory as a tuple (CLASS SLOTS), while an instance is represented as a tuple (CLASS STAMP SLOTS). Modifying the structure class has undefined behavior, while the instance's class may change. This is why the instance needs to track whether it is up-to-date or obsolete. In our simple scheme that information is represented by a stamp that represents the class generation.

Tracking whether the instance is obsolete is important, because the memory layout of slots may change - they may be deleted, added, or moved to different positions. This is convenient for long-running programs without downtime, for incremental development and for image-based workflows - the program may be modified at any time to account for changing requirements, without recompiling it from scratch.

But this doesn't come without a downside. The implementation may conformingly assume that structure accessors won't ever change and therefore they can be inlined. In this case, structure access is a simple memory reference.

(declaim (inline structure-reader-a))
(defun structure-reader-a (object)
  (svref (%slots object) 3))

On the other hand, this can't be assumed for objects, as they must be checked for obsolescence (at the very least), and because readers are more generic functions - another level of flexibility. Inlining generic functions is hard because new methods may be added at runtime and the effective method can change. Moreover, there may be different classes that have same reader names, so we need to include a piece of code that uses the correct class layout for an instance.

This is why calling instance readers involves:

• calling a function (can't be inlined)
• finding the memory layout (dispatch)
• verifying whether the instance is up-to-date

That is exemplified by the following pseudocode that ignores other generic function intrinsics. Depending on the implementation of generic functions, the test for obsolete instances may be evaded when instances are not obsolete.

(declaim (notinline instance-reader-a))
(define-reader-function instance-reader-a (object)
  (unless (%up-to-date-p object)
    ;; Among other things updates indexes for memory accesses. 
    ;; This is a slow path.
    (%recompile-reader-function #'instance-reader-a)
    (return-from instance-reader-a (instance-reader-a object)))
  (typecase object
    (standard-class-a (svref (%slots object) 3))
    (standard-class-b (svref (%slots object) 4))
    (custom-class-c (slot-value object 'a))
    (custom-class-d (slot-value object 'a))
    (otherwise (no-applicable-method #'instance-reader-a object))))

All this is assuming that we're dealing with standard readers. Using the metaobject protocol it is possible to store slot values anywhere - most notably, not in a vector bundled with the instance - or to add additional preprocessing. I'm not going to touch on MOP much here; this is just to signify that standard readers for standard classes may directly access the slot vector.

At minimum, assuming a single reader and a clever dispatch algorithm:

(declaim (notinline instance-reader-a))
(define-reader-function instance-reader-a (object)
  (if (eql (stamp object) 42)
      (svref (%slots object) 3)
      (if (%up-to-date-p object)
          (no-applicable-method #'instance-reader-a object)
          (progn
            (%recompile-reader-function #'instance-reader-a)
            (return-from instance-reader-a (instance-reader-a object))))))

In other words, comparing structure access with instance readers is comparing apples to oranges, because the former is a memory access, while the latter is a function call.

SLOT-VALUE will be even slower, because this function is a trampoline to a more involved SLOT-VALUE-USING-CLASS, and to do that we need to:

• read the object class
• find the slot definition in the class
• invoke a generic function SLOT-VALUE-USING-CLASS

The generic function SLOT-VALUE-USING-CLASS may be similar to the reader defined above, with the caveat that it has more arguments to dispatch on (so the dispatch procedure may be more involved). In any case, it is at least as slow as the optimal reader defined above (a single reader for the standard class).

(defun slot-value (object slot-name)
  (let* ((class (class-of object))
         (slots (mop:class-slots class))
         (slot (find slot-name slots :key #'mop:slot-definition-name)))
    (mop:slot-value-using-class class object slot)))

Tim Bradshaw recently made a blog post that claims that instance slot access is around 38x slower than structure access, but he compares inlined memory access to generic function dispatch. A fair comparison would use the operator STANDARD-INSTANCE-ACCESS.

The metaobject protocol defines MOP:STANDARD-INSTANCE-ACCESS, an optimized way to access instance slots that does not incur the overhead associated with dispatching generic functions. This function may be inlined and is similar to structure object accessors. A possible definition would look like this:

(declare (inline mop:standard-instance-access))
(defun mop:standard-instance-access (object location)
  (svref (%slots object) location))

The argument LOCATION is technically an opaque object, but for illustration purposes we assume that it is an index (it usually is!). Its value may be read using the function SLOT-DEFINITION-LOCATION.

Let's dig into benchmarks! We will measure access time to slots in equivalent structure and instance, each containing ten untyped slots initialized with fixnums.

(defpackage "FAR-FROM-MOP"
  (:import-from #+ccl "CCL"
                #+ecl "MOP"
                #+lispworks "CLOS"
                #+sbcl "SB-MOP"
                #-(or ccl ecl lispworks sbcl) "MOP"
                "FINALIZE-INHERITANCE"
                "CLASS-SLOTS"
                "SLOT-DEFINITION-LOCATION"
                "SLOT-DEFINITION-NAME"
                "STANDARD-INSTANCE-ACCESS"
                #+lispworks "FAST-STANDARD-INSTANCE-ACCESS")
  (:export "FINALIZE-INHERITANCE" "CLASS-SLOTS" "SLOT-DEFINITION-LOCATION"
           "SLOT-DEFINITION-NAME" "STANDARD-INSTANCE-ACCESS"
           #+lispworks "FAST-STANDARD-INSTANCE-ACCESS"))

(defpackage "EU.TURTLEWARE.SLOT-BENCH"
  (:use "CL")
  (:local-nicknames ("MOP" "FAR-FROM-MOP")))
(in-package "EU.TURTLEWARE.SLOT-BENCH")

(declaim (optimize (speed 3) (safety 0) (debug 0)))

(eval-when (:compile-toplevel :load-toplevel :execute)
  (defclass a ()
    ((a :initform (random 10) :reader a-a)
     (b :initform (random 10) :reader a-b)
     (c :initform (random 10) :reader a-c)
     (d :initform (random 10) :reader a-d)
     (e :initform (random 10) :reader a-e)
     (f :initform (random 10) :reader a-f)
     (g :initform (random 10) :reader a-g)
     (h :initform (random 10) :reader a-h)
     (i :initform (random 10) :reader a-i)
     (j :initform (random 10) :reader a-j)))

  (defstruct b
    (a (random 10)) (b (random 10)) (c (random 10)) (d (random 10)) (e (random 10))
    (f (random 10)) (g (random 10)) (h (random 10)) (i (random 10)) (j (random 10)))

  (defparameter *o1* (make-instance 'a))
  (defparameter *o2* (make-b))


  (defparameter *locations*
    (mapcar (lambda (slot-name)
              (let ((class (find-class 'a)))
                (mop:finalize-inheritance class)
                (mop:slot-definition-location
                 (find slot-name (mop:class-slots class)
                       :key #'mop:slot-definition-name))))
            '(a b c d e f g h i j))))

We will measure four slot reading patterns:

• structure: structure reader
• instance : reader, SLOT-VALUE and MOP:STANDARD-INSTANCE-ACCESS

Moreover, to put some pressure on a hypothesized method cache, we will randomize access to slots. The macro expand-body generates consecutive access forms:

(defmacro expand-body (type n-access)
  (flet ((random-a () (nth (random 10) '(a-a a-b a-c a-d a-e a-f a-g a-h a-i a-j)))
         (random-b () (nth (random 10) '(b-a b-b b-c b-d b-e b-f b-g b-h b-i b-j)))
         (random-s () (nth (random 10) '(a b c d e f g h i j)))
         (random-l () (nth (random 10) *locations*)))
    (ecase type
      (:reader
       `(progn
          ,@(loop repeat n-access
                  for read = `(,(random-a) object)
                  collect `(incf count (the fixnum ,read)))))
      (:slot-value
       `(progn
          ,@(loop repeat n-access
                  for read = `(slot-value object ',(random-s))
                  collect `(incf count (the fixnum ,read)))))
      (:instance-access
       `(progn
          ,@(loop repeat n-access
                  for read = #+lispworks `(mop:fast-standard-instance-access object ',(random-l))
                             #-lispworks `(mop:standard-instance-access object ',(random-l))
                  collect `(incf count (the fixnum ,read)))))
      (:structure-access
       `(progn
          ,@(loop repeat n-access
                  for read = `(,(random-b) object)
                  collect `(incf count (the fixnum ,read))))))))

Now our "benchmark tool" and the tests. It is a simple measurement that compares internal real times before and after the computation.

(defmacro do-bench (() &body body)
  `(let ((now (get-internal-real-time))
         (cnt (progn ,@body)))
     (values (- (get-internal-real-time) now) cnt)))

(macrolet ((frob (name object access-type)
             `(defun ,name (n &aux (object ,object))
                (declare (fixnum n)
                         (optimize (speed 3) (safety 0) (debug 0)))
                (do-bench ()
                  (let ((count 0))
                    (declare (fixnum count))
                    (dotimes (v n count)
                      (expand-body ,access-type 100)))))))
  (frob test-object-v1 *o1* :reader)
  (frob test-object-v2 *o1* :slot-value)
  (frob test-object-v3 *o1* :instance-access)
  (frob test-object-v4 *o2* :structure-access))

(defun test-batch (n)
  (list (test-object-v1 n)
        (test-object-v2 n)
        (test-object-v3 n)
        (test-object-v4 n)))

(defun do-benchmarks ()
  (list* (list (lisp-implementation-type)
               (lisp-implementation-version)
               (machine-type)
               internal-time-units-per-second)
         (loop for e from 17 upto 26
               for n = (expt 2 e)
               collect (let (b)
                         (format t "... (expt 2 ~a):~%" e)
                         (setf b (test-batch n))
                         (format t "~a~%" b)
                         b))))

I've run these tests on four implementations. This table presents ratios of the access pattern compared to the best result. Absolute timings are not included.

Implementation	reader / best	svalue / best	access / best	struct / best
CCL 1.12.2	17	12	2	1
ECL 26.5.5	616	719	1	175
LispWorks 8.1.2	22	79	1	1
SBCL 2.4.2	10	9	1	1

Edit: I've been asked a few times for a comparison between implementations, so I'm also including a bar chart comparing absolute timings between them:

Y-axis is in seconds and each bar represents 2^26 x 100 slot accesses in randomized order.

Conclusions:

Accessing slots using generic functions is indeed slower than a single memory access. This is because we can't inline these functions, and we must take care of many possibilities - most notably dispatching arguments of different classes and redefinitions of both the instance class and the reader generic function. All this cost buys us extensibility and runtime flexibility of the program.

Readers, under certain circumstances, can be better optimized than SLOT-VALUE, because they don't have to go through another function and access class slot definition. CCL and SBCL don't exploit this optimization opportunity.

Instance memory access and structure memory access times are roughly the same on SBCL and LispWorks, while instance access is two times slower on CCL.

ECL does a peculiar thing where structure readers are not inlined for some reason. That needs investigating, but hey, instance access is 175x faster ;-)! Instance access is also abnormally fast compared to other imlpementations and that also begs for investigation.

Notes:

To avoid external dependencies, I've defined a very basic time measurement and used MOP operators directly defined by a few hand-picked implementations. For more complete solutions look into "trivial-benchmark" by Yukari Hafner and "closer-mop" by Pascal Costanza.

Lispworks' CLOS::STANDARD-INSTANCE-ACCESS does not conform to MOP specification and errors when supplied with the slot location (it expects the slot name). That severely impacts the performance of instance access. The correct function to call is, for some reason, CLOS::FAST-STANDARD-INSTANCE-ACCESS.

ECL performance is poor in comparison, but I have good news! I'm implementing Fast Generic Function Dispatch algorithm and it will get better.

Somewhat a point of interest, but some implementations specialize slot-value-using-class and other CLOS protocols to structure classes too.

Plots were generated with Polyclot, work-in-progress McCLIM implementation of Grammar for Graphics.

I'd like to thank modula t. for reviewing this post and suggesting improvements.

27 May 2026 12:00am GMT