Debugging and Profiling in Clozure CL: Tools and TechniquesDebugging and profiling are essential skills for any developer working with Clozure CL (CCL). Clozure CL is a high-performance, open-source Common Lisp implementation that runs on multiple platforms and provides a rich set of facilities for interactive development. This article covers practical tools and techniques for diagnosing runtime errors, inspecting program state, finding performance bottlenecks, and interpreting profiling data in CCL.
Overview of Clozure CL’s Development Model
Clozure CL embraces the interactive, image-based Common Lisp development model: you compile and load code into a running image, which you can inspect and modify on the fly. This model makes debugging and profiling especially effective because you can examine live objects, set breakpoints, trace functions, and recompile parts of the system without restarting.
Key primitives you’ll use regularly:
- The read-eval-print loop (REPL) for interactively running and testing code.
- The listener window (or terminal) to view diagnostic output.
- The debugger invoked automatically on unhandled errors.
- The inspector and stepper (where available) to examine objects and execution.
- Profiling tools and timing functions to measure performance.
The Debugger and Error Handling
When an error occurs, CCL typically invokes its debugger. The debugger presents a condition object and a backtrace, then offers a menu of options (such as abort, continue, invoke a listener, or enter the debugger).
Practical tips:
- Use the condition system: signal conditions with signal, warn, error, or simple-condition to provide informative errors.
- Use restartable errors: define restarts (restart-case, invoke-restart) so you can recover interactively from errors in the debugger.
- To programmatically inspect the stack/backtrace, use CCL-specific utilities (see the ccl:backtrace and related introspection functions in some versions) or rely on the backtrace printed in the debugger.
Example pattern (restartable operation):
(defun safe-open (file &key (mode :input)) (restart-case (open file :direction mode) (use-other-file (new-file) :report "Use a different file" (open new-file :direction mode)) (abort () :report "Return nil and do not signal an error" nil))) Inspecting Objects and Program State
Inspecting live objects is a common debugging step.
Tools and techniques:
- print, format, and pprint for textual inspection. Format can produce readable, structured output.
- The inspector (in the GUI build) provides a graphical view of objects, slots, and structure.
- class-of, type-of, and describe to learn about objects and functions.
- trace and untrace to instrument function entry/exit and arguments.
Example:
(trace my-critical-function) ;; Later, when you want to stop tracing: (untrace my-critical-function) Use trace sparingly; tracing hot functions can drastically slow execution and perturb timing.
Stepping and Breakpoints
CCL provides a stepper and breakpoint support in some builds or via add-on libraries. The stepper allows single-stepping through Lisp forms, examining variable values at each step. Breakpoints let you pause execution when particular code paths are reached.
- sldb: The SLDB (Superior Lisp Debugger) is available in many Common Lisp environments and interactive debuggers expose similar facilities.
- break, breakpoint, or implementation-specific functions can be used to trigger a break into the debugger from code.
Example:
;; Force a break when a certain invariant fails: (when (not (valid-state-p state)) (break "Invalid state encountered: ~a" state)) Logging and Tracing Strategies
Logging is indispensable for debugging production problems or long-running services.
Strategies:
- Use a logging library (e.g., trivial-logging or your own lightweight logger) to emit levels (debug, info, warn, error).
- Avoid excessive logging in tight loops to minimize overhead; add sampling or conditional logging.
- Use trace/spy for targeted tracing of functions and execution paths during development.
Simple logger sketch:
(defparameter *log-level* :info) (defun log (level &rest args) (when (not (eq level :debug)) ; example filter (format t "~&[~a] ~{~a~^ ~}~%" level args))) Profiling: Measuring Performance
Profiling identifies where your program spends time so you can optimize effectively. Clozure CL provides profiling facilities and also plays nicely with Common Lisp profiling libraries.
Options:
- ccl:profiler — CCL includes an internal profiler in some builds. Check your CCL version’s documentation for profiler entry points (start, stop, report).
- common-lisp-profiler libraries — third-party libraries can sample the running program and aggregate time by function.
- Timing macros — for small, targeted measurements use time, with-timeout, or custom timing using get-internal-real-time and room for repeated measurements.
Using time:
(time (my-function arg1 arg2)) This prints runtime statistics: real, user, and system time, and the number of garbage collections performed.
For repeated measurement, use:
(defun time-run (thunk n) (let ((start (get-internal-real-time))) (dotimes (i n) (funcall thunk)) (/ (float (- (get-internal-real-time) start)) internal-time-units-per-second))) Interpreting Profiler Output and Optimizing
When you have profiling data, follow these steps:
- Identify hotspots — functions or paths that consume the most time.
- Determine whether time is spent in Lisp code, foreign calls, or GC.
- Decide on optimization strategies:
- Algorithmic improvements first.
- Reduce consing (temporary allocations) to lower GC pressure.
- Type declarations and local declarations (declare (type …) (optimize …)) to help the compiler generate faster code.
- Inline small functions where appropriate.
- Use arrays or specialized data structures for tight loops.
- Move expensive computations out of frequently-called loops.
Example of declaring types:
(defun sum-vector (v) (declare (type simple-vector v) (optimize (speed 3) (safety 0))) (let ((sum 0.0)) (dotimes (i (length v) sum) (incf sum (aref v i))))) Be cautious: extreme optimization (turning safety off, heavy type declarations) can make debugging harder.
Garbage Collection and Memory Profiling
Long pauses or high CPU from GC can be a performance problem. CCL exposes control and stats for garbage collection.
Techniques:
- Monitor allocation rate and GC frequency (time and number of GCs printed by time and profiler).
- Reduce allocation in hot paths: reuse buffers, use preallocated vectors, and avoid creating short-lived conses.
- Tune CCL’s tunable parameters for heap sizes if needed (platform-dependent).
- Use the room function and inspect heap usage with implementation-specific introspection tools.
Example pattern:
;; Preallocate a vector and reuse it to avoid consing (defparameter *scratch* (make-array 1024 :initial-element 0)) (defun use-scratch (values) (replace *scratch* values) ;; operate on *scratch* ... ) Foreign Function Interface (FFI), Multithreading, and Concurrency
If your program uses FFI or multiple threads, debugging and profiling complexity increases.
FFI tips:
- Check calling conventions and types carefully; incorrect types lead to crashes or subtle bugs.
- Wrap FFI calls with error-checking and logging to isolate issues.
- Profile FFI calls separately — time spent in foreign code won’t show up as Lisp function time in some profilers.
Threads:
- Use locks or synchronization primitives intentionally to avoid races; deadlocks and races often require reproducing the interleaving or adding targeted logging.
- Use thread-aware tracing and ensure your profiling approach supports multi-threaded execution.
Useful Libraries and Tools
- trivial-logging — lightweight logging utilities.
- closer-mop — MOP utilities helpful for introspection.
- cl-debugger-enhancements or other community packages — check Quicklisp for up-to-date options.
- Profiling libraries in Quicklisp — search Quicklisp for profilers compatible with CCL.
Workflow Recommendations
- Reproduce the bug in a small test case where possible; unit tests make debugging and regression prevention easier.
- Use the REPL to iteratively test hypotheses and inspect live state.
- Profile before optimizing; optimize hotspots only after measurement.
- Keep logging levels adjustable so you can enable detailed logs in development without overwhelming production runs.
- Maintain a balance between optimization and maintainability — prefer clear, correct code unless profiling shows a real need for heavy tuning.
Example Session: From Bug to Fix (Concise)
- Reproduce at the REPL or with a unit test.
- Inspect the backtrace in the debugger to find the failing function.
- Enter the debugger or a listener, examine variables with describe/class-of/print.
- Add temporary trace/logs around suspect functions.
- If slow, run the profiler to locate hotspots.
- Apply targeted fixes (algorithm, reduce consing, declarations).
- Re-run tests and profiler to confirm improvement.
Conclusion
Debugging and profiling in Clozure CL combine Common Lisp’s interactive strengths with CCL-specific tools. Use the debugger, inspector, trace, and logging for correctness issues; use time-based measurements and profilers to find performance hotspots; and prefer algorithmic and allocation-focused optimizations. The REPL-centric workflow makes iteration fast—inspect live objects, add targeted instrumentation, and recompile on the fly to fix problems quickly.
For platform- or version-specific commands (e.g., exact profiler function names and GC tunables), consult your CCL build’s documentation or Quicklisp packages, since some utilities differ between releases.
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