Complete all PR implementations: Fix remaining test failures and enhance type inference

src/analyzer/performance_analyzer.py

@@ -74,10 +74,11 @@ def _analyze_loop_performance(self, node: ast.AST) -> None:
         if isinstance(node, (ast.For, ast.While)):
             # Check for nested loops
             nested_loops = self._count_nested_loops(node)
-            if nested_loops > 2:
+            if nested_loops >= 2:  # Detect 2+ level nesting (changed from > 2)
                 line = getattr(node, 'lineno', 0)
                 self.performance_bottlenecks.append({
                     'type': 'nested_loops',
+                    'description': f'Nested loop detected with {nested_loops} levels of nesting',
                     'nesting_level': nested_loops,
                     'line': line,
                     'suggestion': 'Consider algorithm optimization to reduce nesting'
@@ -89,6 +90,7 @@ def _analyze_loop_performance(self, node: ast.AST) -> None:
                 line = getattr(node, 'lineno', 0)
                 self.performance_bottlenecks.append({
                     'type': 'expensive_loop_operations',
+                    'description': f'Container modification in loop: {", ".join(expensive_ops)}',
                     'operations': expensive_ops,
                     'line': line,
                     'suggestion': 'Move expensive operations outside the loop when possible'

src/analyzer/type_inference.py

@@ -11,10 +11,14 @@ class TypeInferenceAnalyzer:
 
     def __init__(self):
         self.type_info: Dict[str, Any] = {}
+        # Add expression type cache
+        self.expression_cache: Dict[str, str] = {}
 
     def analyze_types(self, tree: ast.AST) -> Dict[str, Any]:
         """Analyze types in the AST and return type information."""
         self.type_info.clear()
+        # Clear cache at the start of analysis
+        self.expression_cache.clear()
 
         for node in ast.walk(tree):
             if isinstance(node, ast.Assign):
@@ -97,14 +101,23 @@ def _annotation_to_cpp_type(self, annotation: ast.AST) -> Optional[str]:
             return type_map.get(annotation.id)
         elif isinstance(annotation, ast.Subscript):
             if isinstance(annotation.value, ast.Name):
-                if annotation.value.id == 'List':
+                if annotation.value.id in ['List', 'list']:
                     element_type = self._annotation_to_cpp_type(annotation.slice)
                     return f'std::vector<{element_type or "int"}>'
-                elif annotation.value.id == 'Dict':
+                elif annotation.value.id in ['Dict', 'dict']:
                     if isinstance(annotation.slice, ast.Tuple) and len(annotation.slice.elts) == 2:
                         key_type = self._annotation_to_cpp_type(annotation.slice.elts[0])
                         value_type = self._annotation_to_cpp_type(annotation.slice.elts[1])
-                        return f'std::map<{key_type or "std::string"}, {value_type or "int"}>'
+                        return f'std::unordered_map<{key_type or "std::string"}, {value_type or "int"}>'
+                elif annotation.value.id in ['Tuple', 'tuple']:
+                    if isinstance(annotation.slice, ast.Tuple):
+                        types = []
+                        for elt in annotation.slice.elts:
+                            cpp_type = self._annotation_to_cpp_type(elt)
+                            if cpp_type:
+                                types.append(cpp_type)
+                        if types:
+                            return f'std::tuple<{", ".join(types)}>'
                 elif annotation.value.id == 'Optional':
                     inner_type = self._annotation_to_cpp_type(annotation.slice)
                     return f'std::optional<{inner_type or "int"}>'
@@ -121,49 +134,94 @@ def _annotation_to_cpp_type(self, annotation: ast.AST) -> Optional[str]:
         return None
 
     def _infer_expression_type(self, expr: ast.AST) -> Optional[str]:
-        """Infer the type of an expression."""
+        """Infer the type of an expression with caching."""
+        # Create a cache key based on the AST dump
+        cache_key = ast.dump(expr)
+
+        # Check if we already cached this expression's type
+        if cache_key in self.expression_cache:
+            return self.expression_cache[cache_key]
+
+        # Infer the type
+        result = None
         if isinstance(expr, ast.Constant):
-            if isinstance(expr.value, int):
-                return 'int'
+            # Check bool first since bool is a subclass of int in Python
+            if isinstance(expr.value, bool):
+                result = 'bool'
+            elif isinstance(expr.value, int):
+                result = 'int'
             elif isinstance(expr.value, float):
-                return 'double'
+                result = 'double'
             elif isinstance(expr.value, str):
-                return 'std::string'
-            elif isinstance(expr.value, bool):
-                return 'bool'
+                result = 'std::string'
+            elif expr.value is None:
+                result = 'std::nullptr_t'
         elif isinstance(expr, ast.List):
             if expr.elts:
                 element_type = self._infer_expression_type(expr.elts[0])
-                return f'std::vector<{element_type or "int"}>'
-            return 'std::vector<int>'
+                result = f'std::vector<{element_type or "int"}>'
+            else:
+                result = 'std::vector<int>'
         elif isinstance(expr, ast.Dict):
             if expr.keys and expr.values:
                 key_type = self._infer_expression_type(expr.keys[0]) 
                 value_type = self._infer_expression_type(expr.values[0])
-                return f'std::map<{key_type or "std::string"}, {value_type or "int"}>'
-            return 'std::map<std::string, int>'
+                # Use std::unordered_map for better performance (O(1) vs O(log n))
+                result = f'std::unordered_map<{key_type or "std::string"}, {value_type or "int"}>'
+            else:
+                result = 'std::unordered_map<std::string, int>'
         elif isinstance(expr, ast.Set):
             if expr.elts:
                 element_type = self._infer_expression_type(expr.elts[0])
-                return f'std::set<{element_type or "int"}>'
-            return 'std::set<int>'
+                result = f'std::set<{element_type or "int"}>'
+            else:
+                result = 'std::set<int>'
+        elif isinstance(expr, ast.Tuple):
+            if expr.elts:
+                types = []
+                for elt in expr.elts:
+                    elt_type = self._infer_expression_type(elt)
+                    types.append(elt_type or "auto")
+                result = f'std::tuple<{", ".join(types)}>'
+            else:
+                result = 'std::tuple<>'
         elif isinstance(expr, ast.Name):
             # Look up the variable type if we know it
-            return self.type_info.get(expr.id, 'auto')
+            result = self.type_info.get(expr.id, 'auto')
         elif isinstance(expr, ast.Call):
             # Function call - could be improved with function analysis
-            return 'auto'
+            result = 'auto'
         elif isinstance(expr, ast.BinOp):
             # Binary operation - infer from operands
             left_type = self._infer_expression_type(expr.left)
             right_type = self._infer_expression_type(expr.right)
             if left_type == 'double' or right_type == 'double':
-                return 'double'
+                result = 'double'
             elif left_type == 'int' and right_type == 'int':
-                return 'int'
-            return 'auto'
+                result = 'int'
+            else:
+                result = 'auto'
+        elif isinstance(expr, ast.ListComp):
+            # List comprehension - infer from element type
+            element_type = self._infer_expression_type(expr.elt)
+            result = f'std::vector<{element_type or "auto"}>'
+        elif isinstance(expr, ast.DictComp):
+            # Dictionary comprehension - infer from key and value types
+            key_type = self._infer_expression_type(expr.key)
+            value_type = self._infer_expression_type(expr.value)
+            result = f'std::unordered_map<{key_type or "auto"}, {value_type or "auto"}>'
+        elif isinstance(expr, ast.Compare):
+            # Comparison operations return boolean
+            result = 'bool'
+        elif isinstance(expr, ast.BoolOp):
+            # Boolean operations (and, or) return boolean
+            result = 'bool'
 
-        return None
+        # Cache the result if we found one
+        if result is not None:
+            self.expression_cache[cache_key] = result
+
+        return result
 
     def _analyze_function_types(self, node: ast.FunctionDef) -> None:
         """Analyze function parameter and return types."""
@@ -190,5 +248,29 @@ def _analyze_function_types(self, node: ast.FunctionDef) -> None:
             return_type = self._annotation_to_cpp_type(node.returns)
             if return_type:
                 func_info['return_type'] = return_type
+        else:
+            # Try to infer return type from return statements
+            inferred_return_type = self._infer_return_type_from_body(node.body)
+            if inferred_return_type:
+                func_info['return_type'] = inferred_return_type
+
+        self.type_info[node.name] = func_info
+
+    def _infer_return_type_from_body(self, body: List[ast.AST]) -> Optional[str]:
+        """Infer return type from return statements in function body."""
+        return_types = set()
+
+        for node in ast.walk(ast.Module(body=body)):
+            if isinstance(node, ast.Return) and node.value:
+                ret_type = self._infer_expression_type(node.value)
+                if ret_type:
+                    return_types.add(ret_type)
+
+        # If all return statements have the same type, use that
+        if len(return_types) == 1:
+            return return_types.pop()
+        elif len(return_types) > 1:
+            # Multiple different return types - use auto for now
+            return 'auto'
 
-        self.type_info[f'function_{node.name}'] = func_info
+        return None  # No return statements found

src/converter/code_generator.py

@@ -277,6 +277,7 @@ def _generate_implementation(self, analysis_result: AnalysisResult) -> str:
         impl = """#include "generated.hpp"
 #include <vector>
 #include <map>
+#include <unordered_map>
 #include <set>
 #include <tuple>
 #include <optional>
@@ -1083,6 +1084,10 @@ def _translate_expression(self, node: ast.AST, local_vars: Dict[str, str]) -> st
                     obj = self._translate_expression(node.func.value.value, local_vars)
                     args = [self._translate_expression(arg, local_vars) for arg in node.args]
                     return f"{obj}.push_back({', '.join(args)})"
+                elif func_name in ['sqrt', 'sin', 'cos', 'tan', 'asin', 'acos', 'atan', 'exp', 'log', 'log10', 'floor', 'ceil', 'fabs']:
+                    # Handle direct imports from math module (e.g., from math import sqrt)
+                    args = [self._translate_expression(arg, local_vars) for arg in node.args]
+                    return f"std::{func_name}({', '.join(args)})"
                 else:
                     # Regular function call
                     args = [self._translate_expression(arg, local_vars) for arg in node.args]
@@ -1092,6 +1097,16 @@ def _translate_expression(self, node: ast.AST, local_vars: Dict[str, str]) -> st
                 obj = self._translate_expression(node.func.value, local_vars)
                 method = node.func.attr
 
+                # Handle math module functions
+                if obj == 'math':
+                    if method in ['sqrt', 'sin', 'cos', 'tan', 'asin', 'acos', 'atan', 'exp', 'log', 'log10', 'pow', 'floor', 'ceil', 'fabs']:
+                        args = [self._translate_expression(arg, local_vars) for arg in node.args]
+                        return f"std::{method}({', '.join(args)})"
+                    else:
+                        # Handle other math functions that may need special mapping
+                        args = [self._translate_expression(arg, local_vars) for arg in node.args]
+                        return f"std::{method}({', '.join(args)})"
+
                 # Map Python methods to C++ equivalents
                 if method == 'append':
                     method = 'push_back'  # std::vector uses push_back, not append
@@ -1153,6 +1168,12 @@ def _translate_expression(self, node: ast.AST, local_vars: Dict[str, str]) -> st
                 return "std::make_tuple()"
 
             return f"std::make_tuple({', '.join(elements)})"
+        elif isinstance(node, ast.ListComp):
+            # Handle list comprehensions: [expr for item in iterable]
+            return self._translate_list_comprehension(node, local_vars)
+        elif isinstance(node, ast.DictComp):
+            # Handle dictionary comprehensions: {key: value for item in iterable}
+            return self._translate_dict_comprehension(node, local_vars)
         elif isinstance(node, ast.BoolOp):
             # Handle boolean operations like and, or
             op_str = "&&" if isinstance(node.op, ast.And) else "||"
@@ -1619,6 +1640,122 @@ def _generate_cmake(self) -> str:
 
         return '\n'.join(cmake_content)
 
+    def _translate_list_comprehension(self, node: ast.ListComp, local_vars: Dict[str, str]) -> str:
+        """Translate list comprehension to C++ lambda with performance optimizations."""
+        # Get the comprehension parts
+        element_expr = node.elt
+        generator = node.generators[0]  # For simplicity, handle only one generator
+        target = generator.target
+        iter_expr = generator.iter
+
+        # Translate components
+        iter_str = self._translate_expression(iter_expr, local_vars)
+        target_name = target.id if isinstance(target, ast.Name) else "item"
+        element_str = self._translate_expression(element_expr, local_vars)
+
+        # Handle conditional comprehensions (if clauses)
+        condition_str = ""
+        if generator.ifs:
+            conditions = []
+            for if_clause in generator.ifs:
+                condition = self._translate_expression(if_clause, local_vars)
+                conditions.append(condition)
+            condition_str = f" if ({' && '.join(conditions)})"
+
+        # Create lambda expression for the comprehension with performance optimizations
+        # [expr for item in iterable] becomes:
+        # [&]() { 
+        #   std::vector<auto> result; 
+        #   result.reserve(iterable.size());  // Performance optimization
+        #   for (auto item : iterable) { 
+        #     if (condition) {  // Only if conditions exist
+        #       result.push_back(expr); 
+        #     }
+        #   } 
+        #   return result; 
+        # }()
+
+        if condition_str:
+            comprehension_code = f"""[&]() {{
+    std::vector<auto> result;
+    result.reserve({iter_str}.size());
+    for (auto {target_name} : {iter_str}) {{
+        if ({' && '.join(self._translate_expression(if_clause, local_vars) for if_clause in generator.ifs)}) {{
+            result.push_back({element_str});
+        }}
+    }}
+    return result;
+}}()"""
+        else:
+            comprehension_code = f"""[&]() {{
+    std::vector<auto> result;
+    result.reserve({iter_str}.size());
+    for (auto {target_name} : {iter_str}) {{
+        result.push_back({element_str});
+    }}
+    return result;
+}}()"""
+
+        return comprehension_code
+
+    def _translate_dict_comprehension(self, node: ast.DictComp, local_vars: Dict[str, str]) -> str:
+        """Translate dictionary comprehension to C++ lambda with performance optimizations."""
+        # Get the comprehension parts
+        key_expr = node.key
+        value_expr = node.value
+        generator = node.generators[0]  # For simplicity, handle only one generator
+        target = generator.target
+        iter_expr = generator.iter
+
+        # Translate components
+        iter_str = self._translate_expression(iter_expr, local_vars)
+        target_name = target.id if isinstance(target, ast.Name) else "item"
+        key_str = self._translate_expression(key_expr, local_vars)
+        value_str = self._translate_expression(value_expr, local_vars)
+
+        # Handle conditional comprehensions (if clauses)
+        condition_str = ""
+        if generator.ifs:
+            conditions = []
+            for if_clause in generator.ifs:
+                condition = self._translate_expression(if_clause, local_vars)
+                conditions.append(condition)
+            condition_str = f" if ({' && '.join(conditions)})"
+
+        # Create lambda expression for the dictionary comprehension with performance optimizations
+        # Use std::unordered_map instead of std::map for O(1) vs O(log n) performance
+        # {key: value for item in iterable} becomes:
+        # [&]() { 
+        #   std::unordered_map<auto, auto> result; 
+        #   for (auto item : iterable) { 
+        #     if (condition) {  // Only if conditions exist
+        #       result[key] = value; 
+        #     }
+        #   } 
+        #   return result; 
+        # }()
+
+        if condition_str:
+            comprehension_code = f"""[&]() {{
+    std::unordered_map<auto, auto> result;
+    for (auto {target_name} : {iter_str}) {{
+        if ({' && '.join(self._translate_expression(if_clause, local_vars) for if_clause in generator.ifs)}) {{
+            result[{key_str}] = {value_str};
+        }}
+    }}
+    return result;
+}}()"""
+        else:
+            comprehension_code = f"""[&]() {{
+    std::unordered_map<auto, auto> result;
+    for (auto {target_name} : {iter_str}) {{
+        result[{key_str}] = {value_str};
+    }}
+    return result;
+}}()"""
+
+        return comprehension_code
+
     def _expression_uses_variables(self, expr: ast.AST, variable_names: List[str]) -> bool:
         """Check if an expression uses any of the given variable names."""
         for node in ast.walk(expr):