Software Construction & Testing PDF

Faculty of Informatics and Computer Science Software Construction & Testing Topic 4 Functional Programming II (Exploring Advanced Concepts in Functional Programming) Dr. Ahmed Maghawry  Faculty of Informatics and C...

Faculty of Informatics and Computer Science Software Construction & Testing Topic 4 Functional Programming II (Exploring Advanced Concepts in Functional Programming) Dr. Ahmed Maghawry  Faculty of Informatics and Computer Science Contents 1. Currying and Partial Application 2. Type Systems and Type Inference 3. Laziness and Infinite Data Structures 4. Pattern Matching 5. Concurrency and Parallelism 6. Conclusion  Faculty of Informatics and Computer Science 1. Currying & Partial Application Currying and partial application are techniques used to transform functions with multiple arguments into functions with fewer arguments or a sequence of functions with a single argument. Both techniques are based on the concept of higher-order functions, which treat functions as first-class citizens.  Faculty of Informatics and Computer Science 1. Currying & Partial Application Currying is the process of converting a function that takes multiple arguments into a sequence of functions, each taking a single argument. The curried function takes the first argument and returns a new function that takes the second argument, and so on, until all arguments are consumed and the final result is returned.  Faculty of Informatics and Computer Science 1. Currying & Partial Application Partial application is closely related to currying and refers to the process of fixing a function's arguments to create a new function with fewer arguments. It allows you to create specialized versions of a function by providing some, but not all, of its arguments. The resulting function can then be called with the remaining arguments at a later time.  Faculty of Informatics and Computer Science 2. Type Systems & Type Inference Type Systems Type Inference A type system is a set of rules and constraints It is a feature that allows the compiler to that assign types to variables, expressions, automatically deduce the types of variables and functions in a program. based on their usage and the context in which they are declared. It ensures type safety by enforcing strict adherence to type rules and preventing It eliminates the need for explicit type incompatible operations. annotations in certain cases, making the code more concise and readable.  Faculty of Informatics and Computer Science 3. Laziness & Infinite Data Structures Laziness Infinite Data Structures It refers to a programming technique where These are data structures that can represent an expressions or computations are deferred unbounded or potentially infinite amount of data. until their values are actually needed. These structures enable working with sequences This allows for on-demand evaluation and can of data without explicitly defining their size or provide performance benefits by avoiding generating all the elements upfront. unnecessary computations.  Faculty of Informatics and Computer Science 4. Pattern Matching Pattern matching Is a technique used to match the structure of data against predefined patterns and perform different computations or actions based on the match.  Faculty of Informatics and Computer Science 5. Concurrency & Parallelism Concurrency Parallelism allows for the execution of multiple tasks or Involves the simultaneous execution of multiple computations independently, potentially overlapping in tasks or computations. It aims to improve time. It enables effective management of different performance by dividing a larger task into smaller tasks, maximizing resource utilization and subtasks that can be executed concurrently. responsiveness. Parallelism is beneficial for computationally Concurrency is useful when tasks can progress intensive tasks that can be divided into concurrently, even if not executed simultaneously. independent units of work.  Faculty of Informatics and Computer Science 6. Conclusion Currying and Partial Application: Promotes code modularity and reusability by transforming functions into sequences of specialized functions or fixing arguments. They enable composability and flexibility in functional programming. Type Systems and Type Inference: Ensures program correctness and safety by providing static type checking. They reduce the need for explicit type annotations and facilitate robust software development. Laziness and Infinite Data Structures: Laziness allows for delayed computations and manipulation of potentially infinite data structures. It improves efficiency and enables concise representation of large or infinite datasets. Pattern Matching: Simplifies complex data structure handling through concise and structured actions based on matching patterns. It enhances code readability and logic in functional programming. Concurrency and Parallelism: Allows for independent execution of multiple tasks, while parallelism achieves simultaneous execution to improve performance. These techniques enhance responsiveness, scalability, and efficiency in functional programs.  Faculty of Informatics and Computer Science References Martin, R. C. Clean code: A handbook of agile software craftsmanship. Prentice Hall. Hunt, A., & Thomas, D. The pragmatic programmer: Your journey to mastery. Addison-Wesley. Desikan, S., & Ramesh, G. Software testing: Concepts and practices. Pearson Education. Faculty of Informatics and Computer Science Questions?