History/Emergence of SE
- The emergence of Software Engineering dates back to the late 1960s, when the rapid growth of computer usage exposed serious problems in software development.
- In the early days of computing (1950s–1960s), software was small in size, developed by individuals, written without formal methods, etc.
- As computer systems became more complex, software projects grew in size, cost, complexity, etc.
- Also, by the mid-1960s, the industry faced a software crisis, characterized by projects running over budget, late delivery of software, poor quality & reliability, difficult maintenance, failure to meet user requirements, etc. This crisis highlighted that writing software was not just coding—it required disciplined processes.
- The term “Software Engineering” was first introduced at the NATO(North Atlantic Treaty Organization) Software Engineering Conference in 1968.
- The emergence of Software Engineering transformed software development from an ad-hoc activity into a systematic engineering discipline, enabling the development of reliable and complex software systems used worldwide.
Introduction
- Software engineering is a crucial component of modern software development, essential for creating software products that are reliable, efficient, and effective.
Definition
- Software engineering is a systematic, scientific, and disciplined approach to developing software that focuses on the entire software development life cycle, from requirements gathering to maintenance and support.
- Software engineering is the process of designing, creating, testing, and maintaining software products using principles and methods from the field of science & engineering.
Objectives
- The goal of software engineering is to produce high-quality software products that meet the needs of end-users and stakeholders in a scientific and managed way, while also being reliable, efficient, and maintainable over time.
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Need for Software Engineering emergence –
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Manage large and complex software systems
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Improve software quality and productivity
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Reduce development cost and time
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Ensure maintainability and scalability
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Provide systematic, scientific, and managed development approaches
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It ensures software is reliable, efficient, maintainable, and user-friendly.
Characteristics
- Software engineering involves applying systematic, disciplined, and quantifiable approaches to the development and maintenance of software.
- One of the key principles of software engineering is the use of a systematic and iterative approach to software development. This involves breaking the software development process down into smaller, more manageable tasks and continuously testing and evaluating the software throughout the development process.
- The field of software engineering encompasses a wide range of activities and methodologies, including:
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Requirements engineering: This involves identifying the needs and requirements of end-users and stakeholders, and translating them into software specifications.
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Design: This involves creating a high-level design of the software, including the architecture and the user interface.
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Implementation: This involves writing code and integrating components to create the software.
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Testing: This involves verifying that the software meets its requirements and specifications, and identifying and fixing any defects or bugs.
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Maintenance: This involves updating and improving the software to meet changing needs and requirements.
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- Software engineering also places a strong emphasis on collaboration and communication among members of the development team, as well as with stakeholders and end-users. This helps to ensure that the software being developed meets the needs of its intended users and is delivered on time and within budget.
- Software engineering also involves the use of various tools and techniques to manage the software development process, such as project management tools, version control systems, and software testing frameworks.
Use/Applications
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Software Engineering is essential for –
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Web and mobile applications
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Enterprise systems
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Embedded and IoT systems
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AI and data-driven applications
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