Lecture

How a Code Snippet is Translated into Assembly Instructions

This module explains how code snippets are translated into assembly instructions. It covers:

  • Basic operations such as store, load, and arithmetic logic unit (ALU) operations.
  • Optimizations for 4-byte addresses in assembly.
  • Translating loops and branch instructions into assembly code.
  • Pointer and array arithmetic representations.
  • Encoding assembly instructions in memory.

Students will learn the fundamentals of low-level programming and how high-level constructs are represented in assembly.


Course Lectures
  • The introductory module provides essential administrative details about the course, including:

    • Exams: time limits and conflicts.
    • Course grade breakdown.
    • Assignment submission and grading policies.
    • Communication through email, newsgroups, and social media.
    • Course prerequisites and the programming languages and paradigms to be taught.

    It also introduces key concepts such as procedural and object-oriented paradigms, assembly, and concurrent programming, along with an overview of functional programming through Scheme.

  • This module delves into data types within C/C++. It covers:

    • Interpretations and sizes of C/C++ data types.
    • Breaking down bytes into bits and understanding character representations.
    • Negative number representations and two's complement addition.
    • Conversion between different data types, such as chars, shorts, ints, and floats.

    By understanding these data types, students will gain deeper insights into memory representation and data manipulation in C/C++.

  • This module focuses on converting between types of different sizes and bit representations using pointers. Key topics include:

    • Little Endian vs. Big Endian data storage.
    • Storage and access methods for structs in memory.
    • Pointer arithmetic and casting arrays to different types.
    • Dynamic memory management for strings and character arrays.
    • Generic functions utilizing memory and pointers.

    Students will learn practical techniques for managing data and memory in C/C++ through hands-on examples and exercises.

  • This module teaches students how to create a generic swap function applicable to data types of arbitrary size. Important topics addressed include:

    • Using void* type for generic pointers.
    • Implementation of swap functionality using memcpy.
    • Pros and cons of generics in C vs. C++.
    • Error handling for improper use of generics.
    • Implementing generic linear search functions.

    Students will gain experience in the concept of generics, advancing their programming capabilities in C.

  • This module focuses on the implementation of a generic linear search algorithm. Key learning points include:

    • Understanding the prototype and comparison functions.
    • Using void pointers and handling byte offsets in generic searches.
    • Implementing more complex data types for searches, including C-strings.
    • Creating C data structures like non-generic stacks.
    • Preallocating memory and managing internal states.

    Students will apply their understanding of generics and data structures to implement a robust linear search function.

  • This module covers the construction of an integer stack, focusing on constructors and destructors. Key areas include:

    • Implementing Stackpush and Stackpop functionalities.
    • Memory reallocation strategies when stack size exceeds limits.
    • Generic stack implementations and handling memory with memcpy.
    • Static functions in stack operations.
    • Best practices for managing dynamic memory in C.

    Students will strengthen their understanding of object-oriented principles in a procedural language context through stack implementation.

  • This module highlights ownership issues in memory management. Topics include:

    • Common pitfalls when freeing dynamically allocated data.
    • Implementing custom free functions for stack implementations.
    • Understanding C library functions like memmove and qsort.
    • Exploring memory layout including stack and heap segments.
    • How heap managers allocate and free memory effectively.

    Students will learn strategies for proper memory management and the implications of ownership on program stability.

  • This module provides insights into heap management, focusing on how allocational information is stored. Key discussions include:

    • Consequences of improper memory freeing.
    • Algorithms for managing free blocks in the heap.
    • Techniques for reducing memory fragmentation.
    • Understanding activation records and stack layout during function calls.
    • How assembly code interacts with the stack and heap.

    Students will gain practical knowledge of memory allocation and management, crucial for optimizing performance in C/C++ applications.

  • This module explains how code snippets are translated into assembly instructions. It covers:

    • Basic operations such as store, load, and arithmetic logic unit (ALU) operations.
    • Optimizations for 4-byte addresses in assembly.
    • Translating loops and branch instructions into assembly code.
    • Pointer and array arithmetic representations.
    • Encoding assembly instructions in memory.

    Students will learn the fundamentals of low-level programming and how high-level constructs are represented in assembly.

  • This module provides detailed insights into activation records, focusing on memory layout during function calls. Topics discussed include:

    • Storage of return addresses on the stack.
    • Construction of activation records during function executions.
    • Setting up function parameters on the stack.
    • Housekeeping at the end of functions using RET instructions.
    • Illustration of recursion in assembly.

    Students will enhance their understanding of function execution and stack management, which is vital for optimizing code performance.

  • This module transitions students from C code generation to C++ code generation, focusing on swap implementation. Key points include:

    • Understanding pointer swap functions in C.
    • Exploring the C++ version of swap using references.
    • Impact of class declarations on stack memory.
    • Exploration of class methods and their "this" pointers.
    • Compilation and linking processes in C++ programming.

    Students will grasp the differences between C and C++ in code generation and memory management techniques.

  • This module introduces preprocessing commands in C/C++. Key learning objectives include:

    • Understanding the #define directive for macro creation.
    • Using preprocessing macros with arguments.
    • Managing circular #include loops.
    • Analyzing the output of the preprocessor.
    • Visual representation of the preprocessing and compilation processes in C/C++.

    Students will become proficient in using preprocessing commands to enhance the flexibility and efficiency of their code.

  • This module reviews the compilation process of a simple program into an object file. Key points include:

    • Understanding the impact of commenting out standard library header files.
    • How GCC infers prototypes and retains output consistency.
    • Identification of issues during linking processes.
    • Debugging examples of seg faults and bus errors.
    • Analyzing array overflow scenarios and their consequences.

    Students will gain insights into the challenges and nuances of the compilation and linking phases in C/C++ programming.

  • This module explores the differences between sequential and concurrent programming. Key concepts covered include:

    • Impact of writing beyond array limits.
    • Data sharing issues and their implications in function interactions.
    • Understanding variable argument functions like printf.
    • Contrast between sequential and concurrent process execution.
    • Real-world examples of concurrency in programming.

    Students will learn how concurrent programming enables more efficient processing through effective resource management.

  • This module transitions from sequential to concurrent programming through a ticket sale example. It covers:

    • Identifying problems with the sequential model.
    • Using threading interfaces to enhance program performance.
    • Realizing issues with shared data access in threads.
    • Implementing semaphores to control access to critical regions.
    • Understanding deadlocks and their implications.

    Students will apply threading concepts to create more efficient and responsive applications.

  • Semaphores
    Jerry Cain

    This module reviews semaphore concepts, focusing on their syntax and usage in multithreading scenarios. Key topics include:

    • Semaphore types: full buffer vs. empty buffer.
    • Modeling race conditions and ensuring data integrity.
    • Implementing reader and writer threads with semaphores.
    • Understanding semaphore patterns and potential deadlocks.
    • Real-world threading applications, including the Dining Philosopher problem.

    Students will learn to manage concurrent processes effectively through semaphore usage.

  • This module provides a detailed review of the Dining Philosopher problem, emphasizing concurrency challenges. Topics include:

    • Modeling philosophers as threads and their interactions.
    • Understanding deadlocks and strategies to avoid them.
    • Implementing solutions using semaphores and shared resources.
    • Analyzing additional threading examples like FTP downloads.
    • Ensuring proper synchronization in thread interactions.

    Students will deepen their understanding of concurrency issues through practical examples and theoretical implications.

  • This module introduces the Ice Cream Store Problem, involving multiple threading scenarios. Key learning points include:

    • Defining roles of customer, cashier, clerk, and manager threads.
    • Implementing thread interactions and constraints.
    • Handling manager-clerk inspections using semaphores.
    • Managing customer queues and ensuring orderly processing.
    • Writing main functions and spawning threads effectively.

    Students will apply concurrency concepts to a real-world scenario, enhancing their understanding of multithreaded design.

  • This module provides an introduction to the functional paradigm using Scheme. It covers:

    • Comparison of imperative and object-oriented paradigms with functional programming.
    • Basic Scheme function definitions and their applications.
    • Scheme primitives, lists, and operations.
    • Understanding the significance of list structures in functional programming.
    • Writing recursive functions and exploring their behavior.

    Students will gain foundational knowledge in functional programming concepts and their practical applications in Scheme.

  • This module delves into car-cdr recursion problems in Scheme, focusing on practical applications. Key topics include:

    • Writing recursive functions to sum elements in a list.
    • Examining type checking during runtime versus compile-time.
    • Implementing a flatten function for nested lists.
    • Using conditional structures to handle recursion.
    • Generalizing functions by passing comparison functions as parameters.

    Students will enhance their skills in recursive function design and its implications in functional programming.

  • This module introduces the Kawa development environment and evaluates expressions in Scheme. Key areas include:

    • Loading and executing function definitions from .scm files.
    • Mapping functions over lists using the map operation.
    • Implementing apply and eval functions for dynamic execution.
    • Writing functions that utilize lambda expressions.
    • Understanding the implications of defining functions within functions.

    Students will learn to navigate the Kawa environment while applying functional programming techniques in practice.

  • This module focuses on writing recursive power set functions in Scheme. Key topics include:

    • Using lambda functions to create recursive mappings.
    • Implementing let bindings to optimize recursive calls.
    • Exploring permutations of lists through recursive functions.
    • Understanding immutability of lists in Scheme.
    • Examining memory allocation and the read-eval-print loop.

    Students will deepen their understanding of recursion and its applications, while also exploring memory management in Scheme.

  • Scheme Memory Model
    Jerry Cain

    This module examines the Scheme memory model, focusing on linked list operations and layout. Key discussions include:

    • Two approaches to laying out lists in memory.
    • Implementing a generic map function to handle multiple arguments.
    • Understanding garbage collection and its high-level mechanics.
    • Exploring other functional languages, such as ML and Haskell.
    • Comparative analysis of functional programming features across languages.

    Students will gain insights into memory management and garbage collection in functional programming, enhancing their understanding of language implementations.

  • This module provides an overview of Python, highlighting its overarching features. Key areas include:

    • Understanding Python as a scripting language with dynamic typing.
    • Exploring Python's object-oriented and functional paradigms.
    • Examining string and list manipulations within Python.
    • Utilizing Python modules and libraries effectively.
    • Understanding dictionary implementations and their applications.

    Students will develop foundational skills in Python programming while understanding its versatile paradigms and data structures.

  • Python Object Model
    Jerry Cain

    This module dives deeper into Python's object model, covering essential topics such as:

    • Understanding how objects are implemented and how they are stored in memory.
    • Exploring Python's dictionary-based class structures.
    • Using classes and objects effectively in Python.
    • Implementing class constructors and understanding initialization.
    • Accessing object data through Python's object interface.

    Students will enhance their understanding of Python's object model and learn to implement classes efficiently.

  • This module examines XML processing in Python, highlighting different processing models. Key points include:

    • Understanding XML parsing through tag handlers.
    • Implementing XML parsers using Python libraries.
    • Defining functions for RSS feed parsing and handling.
    • Exploring tree-based vs. stream-based XML rendering.
    • Examining practical applications of XML processing.

    Students will acquire practical skills in XML parsing and data handling using Python, enhancing their programming versatility.

  • This module serves as an introduction to Haskell, exploring its unique features. Key discussions include:

    • The history of Haskell and its language safeguards.
    • Understanding expressive functions and lazy evaluation.
    • Exploring types, including user-defined data types.
    • Working with lists and recursive type definitions.
    • Comparative analysis of Haskell's functional programming approach.

    Students will gain insights into Haskell's paradigms and its approach to programming, broadening their understanding of functional languages.