Introduction to Software Engineering

A collection of steps organized into phases, each addressing a specific part of the software development process.

The first phase of software development where the problem is precisely defined, understanding the user's needs and expectations.

A document that outlines the detailed specifications of the software, capturing all agreed-upon requirements.

A design approach that structures software into modules with specific functions, focusing on the sequential flow of execution.

A design approach that uses objects with attributes and methods, focusing on data and behavior interactions.

A design approach that uses logical rules and statements to define software behavior, often used in AI systems.

A design approach that focuses on defining functions and their inputs and outputs, emphasizing the transformations of data.

The stage where developers translate the design into code, using a programming language.

Software Engineering encompasses the systematic processes involved in designing, implementing, and testing software to optimize its development and support.

Software Engineering acts as a crucial part of a much larger system design process. It involves considering the software's integration with other systems and users within the overall system architecture.

Understanding the specific needs of users and their desired applications is a cornerstone of successful software development. This stage determines what functionalities the software should provide and how it should interact with the users.

Different software systems cater to distinct domains and prioritize different aspects based on their purpose. Telecommunications often prioritize time-to-market, while aerospace and NASA prioritize safety, and banking systems prioritize maintainability.

Industrial strength software is designed to address specific problems within a real-world context. This software needs to meet rigorous standards of quality, performance, and reliability.

Cost, schedule, and quality are three fundamental factors that influence the development of industrial strength software. It's a balancing act to achieve all three effectively.

Software development often involves significant costs, with each line of code costing several dollars. Large applications can easily reach millions of dollars in development costs.

In today's business environment, software projects often face tight deadlines. Meeting these deadlines is crucial for success, as delays can lead to missed opportunities and business losses.

A software process model is a simplified representation of how software development is done. It provides a structured approach to guide the process.

The Waterfall Model is a linear software development process where each phase is completed before moving to the next. There is no going back or revisiting previous phases.

The cost of fixing defects increases exponentially as they are discovered later in the development process.

The distribution of defects throughout the software development lifecycle is not uniform. Most defects are introduced during the coding phase.

A software project aims to build a software system within specified constraints (cost, schedule, quality) that meets customer expectations.

A process model specifies a general process that suits a particular class of problems, making it efficient for various projects.

Defects can be introduced at any stage of the software development life cycle, making it crucial to identify and rectify them in each phase.

The best practice is to identify and fix defects as early as possible, close to where they were introduced, to minimize the overall cost of fixing them.

A software development approach that delivers software in increments, each increment being a complete and functional unit. It combines advantages of prototyping and waterfall models.

Each increment in the Iterative Model is built upon the feedback received from the previous increment. This feedback helps to improve the subsequent iterations.

It is an advantage of the Iterative Model as it allows for a gradual payment approach, paying for the delivered functionality in each increment instead of paying for the entire system upfront.

A potential drawback of the Iterative Model is that the initial architecture and design might not be ideal if requirements are not fully understood at the beginning. This can lead to redesigning and refactoring in later iterations.

The Iterative Model is particularly suitable for projects with unclear requirements and where quick feedback and response are important.

A software development approach where each iteration has a fixed duration, and the functionality is adjusted to fit within that time frame.

A timeboxed iteration approach where the development stages (requirements, build, deploy) run sequentially, one after the other.

A timeboxed iteration approach where the development stages (requirements, build, deploy) run simultaneously and progress independently.

In timeboxed iterations, the time to complete the iteration is predetermined, while the amount of functionality delivered is flexible.

Time Boxing approach where the functionality to be delivered is fixed, while the duration of the iteration is adjusted to accommodate the desired features.

The time it takes to complete a single iteration of a project using Linear Timeboxing.

The time it takes to deliver a new version of the project using Pipelined Timeboxing. The time decreases with each iteration.

The amount of work completed within a specific time period, regardless of the method used.

Brooks's Law states that adding people to a late software project only makes it later. This applies to timeboxing too; adding people doesn't shorten the time required for a single iteration.

In pipelined timeboxing, because there are separate teams working on each stage simultaneously, the total team size increases compared to linear timeboxing where one team handles everything.

Timeboxing provides a structured method to add manpower efficiently. By adding resources in specific stages, you can potentially expedite delivery without impacting individual iteration time.