DEV Community: Prog. Kanishk Raj

ProXPL Core Specification: Pillars 6-10

Prog. Kanishk Raj — Sun, 09 Aug 2026 14:13:56 +0000

6. Distributed-Native Primitives

Concept

The language runtime is cluster-aware. Variables are not just memory addresses; they can be distributed CRDTs (Conflict-free Replicated Data Types). The "network" is abstracted away.

Syntax

dist_decl ::= "let" identifier ":" "distributed" "<" type ">"
node_block ::= "node" "(" role_expr ")" "{" statement_list "}"
sync_op ::= "sync" "(" identifier ")"

Example:

// A counter synchronized across all nodes
let global_hits: distributed<counter> = 0;

node(role == "worker") {
    global_hits++; // Local increment, broadcast via Gossip
}

sync(global_hits); // Block until consistent (Output Consistency)

Runtime Behavior (Gossip & CRDT)

The ProXPL initializes a background DHT (Distributed Hash Table) and Gossip Protocol (e.g., SWIM).
distributed<int> is lowered to a G-Counter (Grow-only Counter) or PN-Counter CRDT.
Increments are non-blocking messages. sync creates a barrier.

Implementation Task (Rust - Runtime)

struct Distributed<T: Crdt> {
    local_state: T,
    peers: Vec<SocketAddr>,
}

impl<T: Crdt> Distributed<T> {
    fn update(&mut self, op: Op) {
        self.local_state.apply(op);
        self.gossip_queue.push(op);
    }

    // Background thread
    fn gossip_loop(&self) {
        while let Some(msg) = self.gossip_queue.next() {
            for peer in self.peers.iter().random(3) {
                send(peer, msg);
            }
        }
    }
}

7. Neuro-Symbolic Compiler

Concept

The compiler includes an embedded ONNX runtime. It gathers metrics from previous runs (profile-guided optimization on steroids) and uses a trained model to suggest optimizations or detect probability of bugs.

Syntax

ai_directive ::= "optimize" "with" "ai" [ "(" model_path ")" ]
predict_anno ::= "@predict" "(" goal_expr ")"

Example:

@predict(bug_probability > 0.8)
fn complex_calculation() {
    // ...
}

optimize with ai; // Compiler re-orders instructions based on inference

Compiler Logic (Inference Engine)

Feature Extraction: The compiler extracts AST features (branch depth, cyclomatic complexity, variable usage).
Inference: Pass features to model.onnx.
Action: Model predicts "Inline this", "Unroll loop 4x", or "Warn: Heap Fragmentation Risk".

Implementation Task (C++ - LLVM Pass)

void NeuroOptimizePass::run(Module &M) {
    auto features = ExtractGraphFeatures(M);
    auto tensor = OnnxSession.Run(features);

    float unroll_factor = tensor.get_output(0);
    if (unroll_factor > 0.8) {
        // Apply aggressive unrolling
        SetLoopMetadata(M, "llvm.loop.unroll.full");
    }
}

8. Constraint-Driven Execution

Concept

Instead of imperative steps ("do A, then B"), define the goal and constraints. The runtime uses a SAT/SMT solver to find a valid execution path.

Syntax

constraint_def ::= "constraint" identifier "{" logic_expr "}"
solve_block ::= "solve" "for" identifier [ "minimizing" expr ]

Example:

let x: int;
let y: int;

constraint Layout {
    x > 0;
    y > 0;
    x + y == 100;
}

solve for (x, y); // Runtime finds x=1, y=99 or any valid pair

Runtime Behavior (SMT Solver)

The runtime embeds a solver (like Z3 or localized MiniSat).
Execution pauses at solve. The variables are converted to symbolics, constraints asserted, and check-sat is called. The model values are written back to variables.

Implementation Task (Rust - Z3 Bindings)

fn execute_solve_block(constraints: Vec<Expr>) -> Env {
    let ctx = z3::Context::new(&cfg);
    let solver = z3::Solver::new(&ctx);

    for c in constraints {
        solver.assert(&c.to_z3(&ctx));
    }

    if solver.check() == z3::SatResult::Sat {
        let model = solver.get_model();
        return model.extract_values();
    } else {
        panic!("Unsatisfiable Constraints");
    }
}

9. Knowledge-Persistent Memory

Concept

Programs often restart (stateless microservices). ProXPL programs are stateful by default if requested. persistent scopes map variables to an on-disk embedded KV store (RocksDB/LMDB) automatically.

Syntax

persist_decl ::= "persistent" block

Example:

persistent {
    // Value survives process restart
    let run_count: int = 0; 
}
run_count++;

Runtime Behavior (Memory-Mapped Store)

Variables in persistent blocks are not allocated on the stack/heap. They are pointers into a memory-mapped file (mmap).
The runtime manages the layout and serialization.

Implementation Task (C++ - mmap)

void* persistent_alloc(size_t size, const char* var_name) {
    // Open pro.db
    int fd = open("pro.db", O_RDWR);

    // Find offset for var_name in header
    size_t offset = db_lookup(fd, var_name);

    // Map it
    void* ptr = mmap(0, size, PROT_READ|PROT_WRITE, MAP_SHARED, fd, offset);
    return ptr;
}

10. Jurisdictional Policy Enforcement

Concept

Compliance as Code. The compiler enforces data usage policies (GDPR/CCPA) by injecting compile-time checks on variable access based on tagged regions.

Syntax

policy_def ::= "policy" identifier "{" rules "}"
region_tag ::= "region" "(" identifier ")"

Example:

policy GDPR {
    forbid "US-Server" read user.email;
}

region("US-Server") {
    print(user.email); // COMPILER ERROR: Policy Violation
}

Compiler Logic (Policy Injection)

The compiler builds a "Policy Graph" mapping regions to allowed data access.
During the semantic analysis phase, every variable access is checked against the active Policy Graph.

Implementation Task (Rust - Semantic Check)

fn check_policy_access(current_region: &str, variable: &Var, operation: Op) {
    let policy = global_policy_table.get("GDPR");

    if let Some(rule) = policy.forbids(current_region, variable) {
        emit_error(
            "PolicyViolation", 
            format!("Access to {} forbidden in region {} by {}", variable.name, current_region, rule.name)
        );
    }
}

ProXPL Core Specification: Pillars 1-5

Prog. Kanishk Raj — Sun, 09 Aug 2026 14:12:31 +0000

1. Intent-Oriented Programming (IOP)

Concept

IOP decouples the definition of a capability from its implementation. The developer defines an intent, and the compiler or runtime resolves it to a concrete implementation based on environment, security constraints, or performance requirements.

Syntax (EBNF)

intent_decl ::= "intent" identifier "(" [param_list] ")" [ "->" type ] ";"
resolver_decl ::= "resolver" identifier "matches" identifier "{" block "}"

Example:

// Definition
intent secure_verify(user) -> bool;

// Implementation (Provider A)
resolver Auth0Provider matches secure_verify {
    return auth0.verify(user.token);
}

// Implementation (Provider B - Local)
resolver LocalHashProvider matches secure_verify {
    return crypto.bcrypt_verify(user.hash, user.input);
}

// Usage
let is_valid = secure_verify(current_user); // Compiler picks best resolver

Compiler Logic (The Solver)

Parsing: intent nodes are treated as unlinked symbols.
Semantic Analysis: The IOP Resolver Pass scans for all resolver blocks matching the signature.
Resolution Strategy:
- Static Resolution: If prople.toml specifies a provider (e.g., auth = "Auth0"), the compiler hard-links the call site to Auth0Provider.
- Dynamic Resolution: If ambiguous, the compiler generates a vtable-like lookup where the "Best" provider is chosen at startup.

Implementation Task (Rust - Compiler AST)

struct IntentNode {
    name: String,
    signature: FnSignature,
}

struct ResolverNode {
    target_intent: String,
    implementation: Block,
    cost_metric: u32,
}

fn resolve_intent(intent: &IntentNode, resolvers: &[ResolverNode], config: &Config) -> Option<ResolverNode> {
    // 1. Check strict config overrides
    if let Some(forced) = config.overrides.get(&intent.name) {
        return resolvers.find(|r| r.name == forced);
    }

    // 2. Default to lowest cost metric (static optimization)
    resolvers.iter().min_by_key(|r| r.cost_metric).cloned()
}

2. Context-Aware Polymorphism

Concept

Functions execute different logic branches not based on arguments, but on system state (Context). This eliminates global if (System.isOverloaded) checks.

Syntax

context_decl ::= "context" identifier "{" layer_decl* "}"
layer_decl   ::= "layer" identifier "{" func_decl* "}"
activate_stmt ::= "activate" [ "(" ] identifier [ ")" ] block

Example (Layered COP):

context MobileMode {
    layer Display {
       func render() {
           print "Rendering for mobile...";
       }
    }
}

activate(MobileMode) {
    render(); // Prints mobile version
}

runtime Behavior (Dispatch Table)

The runtime maintains a Context Vector, a thread-local or global bitmask representing current states (Power, Load, Security).
Function calls to process_image are indirect jumps through a Context Dispatch Table (CDT).

Implementation Task (C++ - Runtime Dispatch)

// Context flags
enum ContextFlag { LOAD_HIGH = 1 << 0, BATTERY_LOW = 1 << 1 };
std::atomic<uint32_t> global_context;

// Dispatcher
typedef void (*ImgProcFn)(Image*);
ImgProcFn process_image_table[4]; // Indexed by flags

void init_dispatch() {
    process_image_table[0] = &high_quality_resize; // Normal
    process_image_table[1] = &fast_bilinear_resize; // LOAD_HIGH
    // ...
}

// Called at callsite: process_image(img) ->
// DOING_THIS_FAST:
inline void call_process_image(Image* img) {
    uint32_t ctx = global_context.load(std::memory_order_relaxed);
    process_image_table[ctx](img);
}

3. Autonomic Self-Healing Runtime (ASR)

Concept

A runtime supervisor hierarchy similar to Erlang/Akka but native to the language control flow. Panics are not crashes; they are signals to the supervisor to intervene.

Syntax

resilient_scope ::= "resilient" "{" statement_list "}" "recovery" "(" strategy ")" ";"
strategy ::= "restart" | "rollback" | "escalate"

Example:

resilient {
    db.connect();
    db.query("SELECT *");
} recovery (restart: 3 times, then escalate);

Runtime Logic (Supervisor Tree)

Scope Entry: Pushes a RecoveryFrame onto the thread's Supervisor Stack.
Panic/Crash: The signal handler (SIGSEGV/SIGABRT) or exception unwinder pauses unwinding at the nearest RecoveryFrame.
Heal: The runtime executes the strategy. If restart, instruction pointer resets to the start of the block.

Implementation Task (Rust - Runtime)

enum Strategy { Restart(usize), Eskalate }

struct SupervisorFrame {
    checkpoint: ContextSaveState, // Registers, Stack Ptr
    strategy: Strategy,
    retry_count: usize,
}

thread_local! {
    static SUPERVISOR_STACK: RefCell<Vec<SupervisorFrame>> = ...;
}

fn handle_panic() {
    let mut stack = SUPERVISOR_STACK.borrow_mut();
    if let Some(frame) = stack.last_mut() {
        match frame.strategy {
            Strategy::Restart(max) if frame.retry_count < max => {
                frame.retry_count += 1;
                longjmp(frame.checkpoint); // Jump back to start
            }
            _ => propagate_panic(),
        }
    }
}

4. Intrinsic Security (Security-as-Grammar)

Concept

Information Flow Control (IFC) baked into the type system. Data originating from untrusted sources is tainted<T>. It cannot be used in sinks (Database, OS Shell) requiring pure<T> without sanitization.

Syntax

type_modifier ::= "tainted" | "pure"
sanitize_op ::= "sanitize" "(" expr ")" "->" identifier

Example:

// Input is inherently tainted
let user_input: tainted<string> = request.body;

// DB requires pure<string>
// db.execute(user_input); // COMPILER ERROR: Type Mismatch

// Must sanitize
let safe_sql: pure<string> = sanitize(user_input) using sql_escaper;
db.execute(safe_sql); // OK

Compiler Logic (Taint Analysis)

Propagation: tainted<T> + pure<T> = tainted<T>. Taint spreads like a virus.
Barrier: Only sanitize blocks can cast tainted<T> to pure<T>.
Check: Sinks are annotated with requires: pure.

Implementation Task (Compiler Semantic Pass)

fn check_assignment(target_type: Type, source_type: Type) -> Result<(), Error> {
    if source_type.is_tainted() && !target_type.is_tainted() {
        return Err("Security Violation: Cannot assign tainted data to pure variable without sanitization.");
    }
    Ok(())
}

5. Chrono-Native Logic

Concept

Data has a lifespan. Variables can expire, triggering garbage collection or logic shifts.

Syntax

temporal_decl ::= "let" identifier ":" "temporal" "<" type ">" "=" expr "decay" duration ";"
check_expr ::= "if" "expired" "(" identifier ")" block

Example:

// Auth token valid for 500ms
let token: temporal<string> = gen_token() decay 500ms;

// ... later ...
print(token); // If > 500ms, throws ExpiredAccessError or returns "decayed_value"

Runtime Behavior (Temporal GC)

The allocator adds a timestamp header to every temporal allocation.
Dereferencing a temporal pointer checks (now - alloc_time) > ttl.

Implementation Task (C++ - Smart Pointer)

template<typename T>
struct Temporal {
    T value;
    uint64_t created_at;
    uint64_t ttl_ms;

    T& operator*() {
        if (now() - created_at > ttl_ms) {
            throw ExpiredException();
        }
        return value;
    }
};

// GC Logic
void collect_expired() {
    for (auto obj : heap) {
        if (obj.is_temporal && obj.is_expired()) {
            free(obj);
        }
    }
}

ProXPL v1.6.0 Release Checklist

Prog. Kanishk Raj — Sun, 09 Aug 2026 14:08:41 +0000

P0: Implementation Criteria

[x] Intents: End-to-end declaration → registration → resolution → execution
[x] Contexts: Declaration → type checking → activation → dynamic layer resolution
[x] ASR (Advanced State Recovery): Nested resilient blocks → exception unwinding

P1: Validation Suite

[x] Create test_asr_recovery.prox (Passes)
[x] Create test_asr_edge_cases.prox (Passes)
[x] Create test_intents_advanced.prox (Passes)
[x] Create test_intents_errors.prox (Passes)
[x] Create test_intents_gc.prox (Passes)
[x] Create test_contexts_layers.prox (Passes)
[x] Create test_contexts_errors.prox (Passes)

P2: Benchmarks

[x] Execution Time: Compare Direct Call vs Intent Resolver Dispatch (Minimal overhead confirmed)
[x] Memory: Track Peak Working Set size of VM during GC test

P3: Release Engineering

[x] Global Version Bump to 1.6.0 (CMakeLists.txt, common.h, setup.iss)
[x] Automate verification script (scripts/verify_release.py)
[x] CHANGELOG.md updated
[x] docs/VERSION_UPGRADE_GUIDE_v1.6.0.md updated
[x] IMPLEMENTATION_STATUS.md marked as IMPLEMENTED

ProXPL v1.6.0 Upgrade Guide

Prog. Kanishk Raj — Sun, 09 Aug 2026 14:07:17 +0000

Welcome to ProXPL v1.6.0! This release marks a significant milestone as we have fully integrated the core advanced paradigms into the ProXPL Virtual Machine and Bytecode generator.

This guide covers the necessary adjustments required when upgrading your codebase from v1.5.0.

1. Intent-Oriented Programming

In v1.5.0, intent declarations and resolvers were parsed but ignored by the compiler backend. In v1.6.0, they are fully functional and emit runtime opcodes.

Syntax Requirement

Intent declarations now strictly require a trailing semicolon (;).

v1.5.0 (Tolerated but ignored):

intent ProcessData(data)

v1.6.0 (Required):

intent ProcessData(data);

Resolver Matching

Ensure you use the matches keyword (not resolves or other variants) when binding a resolver to an intent.

resolver DataHandler matches ProcessData {
    print("Handling data!");
}

2. Context-Aware Polymorphism

Contexts and Layers are now strictly validated and execute proper environment scoping at runtime.

Block Activation

The activate statement now requires a block to encapsulate the active context. It cannot be used as a standalone statement.

v1.5.0 (Tolerated but ignored):

activate AdminTheme;

v1.6.0 (Required):

activate AdminTheme {
    // Operations inside this block run with AdminTheme layers applied
    renderUI();
}

3. Autonomic Self-Healing (ASR)

The resilient keyword now provides genuine zero-cost exception unwinding using setjmp/longjmp under the hood in the VM.

Code placed inside a resilient block will no longer cause fatal crashes when operations like division-by-zero occur. Instead, they will recover silently and continue execution after the block.

No syntax changes are required, but you should review your error-handling logic as runtime errors that previously crashed the process will now be caught and recovered if inside a resilient scope.

ProXPL v1.6.0: The IOP and Resilience Release

Prog. Kanishk Raj — Sun, 09 Aug 2026 14:05:27 +0000

🌟 Overview

ProXPL v1.6.0 delivers the full implementation of three core operational pillars: Intent-Oriented Programming (IOP), Context-Aware Polymorphism (CAP), and Autonomic Self-Healing (ASR). Previously, these paradigms existed only in the frontend (Parser/AST); they are now fully integrated into the Virtual Machine with bytecode opcodes, zero-cost exception handling, and GC support.

✨ New Features

1. Intent-Oriented Programming (IOP)

Intents provide declarative runtime dispatch decoupled from direct function calls.

intent keyword successfully creates Intent Objects.
resolver functions dynamically match against intents using the matches (or for) keyword.
Intent invocations route dynamically based on active scopes and resolvers.

2. Context-Aware Polymorphism (CAP)

Layers override behaviors without requiring heavy class hierarchies.

context blocks establish scope-bound namespaces.
layer blocks define polymorphic overrides.
activate dynamically pushes layers onto the VM's active execution context stack, affecting subsequent virtual calls globally within that scope.

3. Autonomic Self-Healing (ASR)

Zero-cost exception unwinding using native setjmp/longjmp.

resilient blocks protect arbitrary logic chunks.
Exceptions now safely unwind through nested structures, deep call stacks, and closures.
Local variables and closures are safely reclaimed during stack unwinding.

📈 Performance Benchmarks

The v1.6.0 release retains ProXPL's lightning-fast speed metrics for these dynamic paradigms:

Direct Native Call (100k iter): ~0.008s
Intent Dynamic Resolution (100k iter): ~0.006s (Negligible Overhead)
ASR Setup Loop (1 million iter): ~0.035s

🐛 Fixes & Stabilizations

Corrected GC blackenObject switch blocks to safely traverse ObjContext and ObjLayer memory boundaries.
Adjusted the implementation of the interpreter stack-reset behavior to avoid unbounded loop exceptions.

🔧 Upgrading

Refer to the v1.6.0 Upgrade Guide for detailed syntax requirement shifts (e.g., semicolons for intents).

ProXPL v1.6.0 — Intent, Context, and Resilience running at the speed of native C.

ProXPL v1.5.0 Update: Traits Implementation (Phase 2)

Prog. Kanishk Raj — Sun, 09 Aug 2026 14:03:42 +0000

This update represents the completion of Phase 2 of the ProXPL roadmap, successfully establishing the parsing and static analysis foundations for Traits and Generics within the language.

Summary of Changes

1. Abstract Syntax Tree (AST) Enhancements

We expanded the core representations for traits and classes:

TypeInfo: Added a methods field (StmtList*). The Type Checker can now natively track methods associated with a class or trait type directly in the symbol table, rather than having to reconstruct or search the AST for method bodies on the fly.
FuncDeclStmt and ClassDeclStmt: These AST nodes were enriched with genericParams and genericBounds (as StringList*), preparing the compiler for constraints like <T: Comparable>.
ast.c: Factory functions createFuncDeclStmt and createClassDeclStmt were updated to initialize and store these generic arguments properly.

2. Parser Implementations

We implemented parser logic to parse generic arguments cleanly:

Updated funcDecl and classDecl inside parser.c to look for generic tokens bounded by < and >.
The parser can now pull out type variable names and map them against optional trait bounds following a colon (:).
These parsed bounds are then passed to the enhanced AST factory functions mentioned above.

3. Type Checker Enforcement

The bulk of this update is centered on validating trait adherence during the compilation phase:

Trait Adherence: In STMT_CLASS_DECL, if a class declares it implements a set of interfaces, the Type Checker now retrieves each trait's expected methods (using the updated TypeInfo symbols). It then iterates over those requirements, verifying that the class body contains a function definition matching the required method name. A type error is generated if the class fails to satisfy the contract.
Bound Resolution: In both STMT_CLASS_DECL and STMT_FUNC_DECL, the generic bounds parsed out are checked against the symbol table. The Type Checker issues an error if a constraint references a trait that does not exist or if it points to a standard type rather than a trait/interface.
Symbol Persistence: STMT_TRAIT_DECL and STMT_CLASS_DECL bodies have been modified so they register their methods onto their TypeInfo definitions immediately during the first pass.

Impact

This release fundamentally changes how polymorphism will be handled in ProXPL. By shifting to a robust constraint-checking architecture, the compiler can now guarantee structural and nominal type adherence prior to bytecode generation, pushing us significantly closer to our "Type Fortress" goals for v1.5.0.

ProXPL v1.5.0: The "Type Fortress" Release

Prog. Kanishk Raj — Sun, 09 Aug 2026 14:02:22 +0000

🌟 Overview

ProXPL v1.5.0 hardens the type system with Traits/Interfaces v2, Result/Option types, Type Aliases, and Const Generics. This release also delivers a Generational Garbage Collector for dramatically improved latency and the first version of the ProXPL Debugger via DAP (Debug Adapter Protocol).

✨ New Features

1. Traits (Interface v2)

Composable behavioral contracts with default implementations.

trait Printable {
    func toString(): string;

    // Default implementation
    func display() {
        print(this.toString());
    }
}

trait Comparable {
    func compareTo(other): int;
}

class Point : Printable, Comparable {
    let x: int;
    let y: int;

    func init(x, y) {
        this.x = x;
        this.y = y;
    }

    func toString(): string {
        return "(" + to_string(this.x) + ", " + to_string(this.y) + ")";
    }

    func compareTo(other): int {
        let thisDist = this.x * this.x + this.y * this.y;
        let otherDist = other.x * other.x + other.y * other.y;
        return thisDist - otherDist;
    }
}

Implementation Details:

trait keyword for defining behavioral contracts
Default method implementations in traits
Multiple trait implementation per class
Trait bounds for generics: func sort<T: Comparable>(list: List<T>)
Compile-time vtable generation for trait dispatch
New AST nodes: DECL_TRAIT, IMPL_TRAIT

2. Result & Option Types

Explicit error handling without exceptions.

enum Option<T> {
    Some(T),
    None
}

enum Result<T, E> {
    Ok(T),
    Err(E)
}

func divide(a: float, b: float): Result<float, string> {
    if (b == 0) {
        return Result.Err("Division by zero");
    }
    return Result.Ok(a / b);
}

func findUser(id: int): Option<User> {
    let user = db.query("SELECT * FROM users WHERE id = ?", id);
    if (user == null) return Option.None;
    return Option.Some(user);
}

// Usage with pattern matching
match (divide(10, 0)) {
    case Result.Ok(val) => print("Result: " + to_string(val));
    case Result.Err(msg) => print("Error: " + msg);
}

// Chaining with ? operator
func processUser(id: int): Result<string, string> {
    let user = findUser(id)?;   // Early return on None/Err
    let profile = loadProfile(user)?;
    return Result.Ok(profile.name);
}

Implementation Details:

Built on top of v1.3.0 Enums and Generics
? operator for early error propagation
Standard library Option and Result types
Compiler enforces exhaustive handling

3. Type Aliases

Simplify complex type signatures.

type UserID = int;
type Callback = func(int, string): bool;
type Matrix<T> = List<List<T>>;
type StringMap<V> = Dict<string, V>;

func processUsers(ids: List<UserID>, callback: Callback) {
    for (let id in ids) {
        callback(id, "processing");
    }
}

4. Generational Garbage Collector

Dramatically improved GC latency and throughput.

Architecture:
| Generation | Allocation | Collection Strategy |
|------------|------------|---------------------|
| Nursery (Gen 0) | Bump allocator (fast) | Copy collection — frequent, fast (~100μs) |
| Young (Gen 1) | Free-list | Mark-compact — moderate frequency (~1ms) |
| Old (Gen 2) | Free-list | Mark-sweep — infrequent (~10ms) |

Key Improvements:

10–50x reduction in GC pause times
Write barrier for inter-generational references
Concurrent marking for Gen 2 (background thread)
GC tuning API: gc.set_threshold(), gc.stats()

5. Debugger (DAP Support)

Debug ProXPL programs in VS Code.

Features:

Breakpoints (line, conditional, hit count)
Step Into / Step Over / Step Out
Variable inspection and watch expressions
Call stack display with source mapping
Evaluate expressions in debug console
Source maps for LLVM AOT binaries

Integration:

VS Code extension updated with debugger launch configurations
DAP server embedded in ProXPL runtime
Configuration via launch.json:

{
    "type": "proxpl",
    "request": "launch",
    "program": "${workspaceFolder}/src/main.prox",
    "stopOnEntry": false
}

6. Const Generics

Generic parameters that are compile-time constants.

class FixedArray<T, const N: int> {
    let data: T[N];

    func get(index: int): T {
        if (index >= N) throw "Index out of bounds";
        return this.data[index];
    }
}

let arr = new FixedArray<int, 10>();

🐛 Bug Fixes

ID	Description	Component
BUG-301	Fix GC not collecting circular references in closures	GC
BUG-302	Fix trait method resolution order with diamond inheritance	Type Checker
BUG-303	Fix debugger source mapping off-by-one for multi-line expressions	DAP
BUG-304	Fix type alias expansion in generic contexts	Type Checker

📈 Performance Goals

GC pause (Gen 0): < 200μs
GC pause (Gen 1): < 2ms
GC pause (Gen 2): < 15ms
Debugger overhead: < 5% when breakpoints inactive

🔧 Breaking Changes

trait keyword now reserved
type keyword now reserved for type aliases
Old interface keyword deprecated — use trait instead (compatibility shim provided for 1 release)

ProXPL v1.5.0 — Types that protect, a GC that respects your time.

Release Notes for ProXPL v1.4.0

Prog. Kanishk Raj — Sun, 09 Aug 2026 14:00:48 +0000

Deep-Tier Optimizations

Memory Management: Switched the ProXPL core runtime to use mimalloc, drastically reducing heap fragmentation for benchmarks like merge_sort.
Dictionary Optimizations: Implemented SwissTable-style metadata bytes for Dictionary mapping in table.c, enabling ultra-fast linear probing.
ASR Refinement: Established zero-cost stack unwinding for resilient blocks by implementing a side-table ExceptionHandlerTable embedded into the Chunk.
LLVM Backend: Configured an advanced llvm::PassManager with O3 optimizations (Loop/SLP Vectorization, Inlining) and forced CallInst->setTailCall(true) for seamless TCO recursion (crucial for fib).
Updated all language package versions (CLI, VS Code Extension, Language Server, Inno Setup, and CMake) to 1.4.0.

Release Notes for ProXPL v1.3.5

Prog. Kanishk Raj — Sun, 09 Aug 2026 13:57:43 +0000

What's New

1. Performance Optimizations

This release focuses on dramatically improving the execution speed of ProXPL, specifically targeting mathematical loops and heavy computations.

Integer Fast Paths for Virtual Machine (vm.c): Introduced an integer fast path for the OP_MODULO bytecode instruction. The VM now checks if both operands are whole integers, and if so, it utilizes the native hardware modulo operator (%) instead of defaulting to the C standard library's double-precision fmod() function.
Impact: This drastically accelerates performance in algorithms involving heavy integer mathematics (such as loop counters and mathematical conjectures like Collatz), matching or exceeding standard execution times in Node.js and Python for these specific computations.

2. Version Updates

Updated all language package versions (CLI, VS Code Extension, Language Server, Inno Setup, and CMake) to 1.3.5.

Release Notes for ProXPL v1.3.4

Prog. Kanishk Raj — Sun, 09 Aug 2026 13:56:02 +0000

What's New

1. New Data Validation Library (`std/lib/validation.prox`)

A comprehensive schema-based data validation library has been added to the standard library, contributed by Astitva Bhardwaj (@bastitva0-blip).

Validators: Typed builders such as string(), number(), bool(), list(), and any().
Chainable Rules: Supports constraints like required, optional, minLength, maxLength, email, url, alphanumeric, min, max, integer, positive, oneOf, items.
Schema Builder: Schema.define() to validate complete dictionaries and collect all errors simultaneously.
Validation Results: Contains detailed properties like .valid, .errors, and methods to check errors.
Standalone Helpers: Includes Validate.isEmail, isURL, isNotEmpty, isInteger, etc.

2. Language Fixes

Implements Keyword: Addressed parsing and syntax issues related to the implements keyword in classes (Merge pull request #22).

3. Build & CI Improvements

VS Code Extension: Bumped the VS Code Extension (vsce) packaging to match the 1.3.4 language version.
Windows Runner Compatibility: Removed hardcoded Visual Studio generator bindings to improve CI compatibility on Windows runners.

ProXPL v1.3.1 - Stabilization Release

Prog. Kanishk Raj — Sun, 09 Aug 2026 13:51:43 +0000

We are pleased to announce the release of ProXPL v1.3.1, a critical stabilization update focused on resolving architectural discrepancies, memory leaks, and garbage collection vulnerabilities identified during our comprehensive codebase audit.

🚀 Key Improvements

1. Unified VM Dispatch Architecture

The Virtual Machine now uses a unified macro-based dispatch loop. This eliminates the "split-brain" problem where the GNUC Computed Goto path and the standard Switch-Case Fallback path had divergent logic.

Fixed: Missing opcodes in GNUC path (OP_INTERFACE, OP_IMPLEMENT, OP_MODULO, and bitwise operators).
Fixed: OP_CLOSURE upvalue capture failure in high-performance mode.
Benefit: 100% logic parity across all platforms and compilers.

2. Memory Leak Resolution

Identified and resolved a significant memory leak in the Type Checker.

Fixed: String allocations for symbol names and parameter types were not being released during scope exit.
Benefit: Reduced memory footprint during long compilation tasks and improved LSP stability.

3. Enhanced Garbage Collection Safety

Hardened the runtime against race conditions during object allocation.

Fixed: OP_MAKE_TENSOR now roots the newly allocated tensor immediately before popping elements from the stack.
Benefit: Prevents rare but critical segmentation faults that could occur if a GC cycle triggered during tensor initialization.

4. Robust Error Handling

Refactored the VM's internal stack management.

Fixed: Replaced fatal exit(1) calls in the stack push() operation with recoverable INTERPRET_RUNTIME_ERROR reports.
Benefit: Host applications (like the REPL, IDE extension, or embedded hosts) can now gracefully recover from stack overflows instead of crashing.

📦 Version Information

Major: 1
Minor: 3
Patch: 1
Status: Stable / Recommended for all users

🛠️ Update Guide

Users are encouraged to update to v1.3.1 by rebuilding from source or downloading the latest binaries from the releases page.

# To update via PRM
prm update

Release Date: April 22, 2026

Project: ProX Programming Language (ProXPL)

[Boost]

Prog. Kanishk Raj — Sun, 09 Aug 2026 13:49:32 +0000

Prog. Kanishk Raj

Aug 9

ProXPL v1.3.0: The "Pattern Power" Release

#news #programming #opensource #code

3 min read