COMPUTING SCIENCE 220

Software Engineering and Human-Computer Interfaces

Computing Science and Software Engineering: Definitions

The discipline of computing is the systematic study of algorithmic processes that describe and transform information: their theory, analysis, design, efficiency, implementation, and application. The fundamental question underlying all of computing is, "What can be (efficiently) automated?" [1]

Computing and Engineering

The Task Force on the Core of Computer Science (whose definition of the discipline of computing is quoted above) identified three major paradigms or cultural styles by which computing practitioners approach their work:

1. Theory is rooted in mathematics; four steps are followed in developing a theory:
   1. characterize objects of study (definition)
   2. hypothesize possible relationships among them (theorem)
   3. determine whether the relationships are true (proof)
   4. interpret results

   Theory is the bedrock of the mathematical sciences: applied mathematicians share the notion that science advances only on a foundation of sound mathematics.

2. Abstraction (modelling, experimentation) is rooted in the experimental scientific method; four steps are followed in the investigation of a phenomenon:
   1. form a hypothesis
   2. construct a model and make a prediction
   3. design an experiment and collect data
   4. analyze results

   Abstraction (modeling) is the bedrock of the natural sciences: scientists share the notion that scientific progress is achieved primarily by formulating hypotheses and systematically following the modeling process to verify and validate them.

3. Design is rooted in engineering; four steps are followed in the construction of a system or device to solve a given problem:
   1. state requirements
   2. state specifications
   3. design and implement the system
   4. test the system

   Design is the bedrock of engineering: engineers share the notion that progress is achieved by posing problems and systematically following the design process to construct systems that solve them.

The Task Force concluded:

Computing sits at the crossroads among the central processes of applied mathematics, science, and engineering. The three processes are of equal -- and fundamental -- importance in the discipline, which is a unique blend of interaction among theory, abstraction, and design. The binding forces are a common interest in experimentation and design as information transformers, a common interest in computational support of the stages of those processes, and a common interest in efficiency. [2]

Software Engineering: A Definition

Software engineering is: [3]

• a modelling activity -- software engineers deal with complexity through modelling, by focusing at any one time on only the relevant details and ignoring everything else.
  • model -- an abstraction of reality
  • analysis -- constructing a model of the problem domain
  • design -- constructing a model of the solution domain
  • In OO methods, the solution domain model is an extension of the problem domain model, so that the structure of the software reflects that of the problem. [4]
• a problem-solving activity -- models are used to search for an acceptable solution
  • driven by experimentation
  • reuses pattern solutions
  • incremental evolution of the system toward one acceptable to the client
  • revised in response to change
• a knowledge acquisition activity -- in modelling the application and solution domain, software engineers collect data, organize it into information, and formalize it into knowledge.
  • nonlinear -- new information may invalidate previous knowledge
    • risk-based development -- identify high-risk components to avoid late surprises
    • issue-based development -- execute development activities in parallel, organizing according to issues which still need resolution
    • iterative development -- design and implement the high-risk (difficult) parts first
• a rationale-driven activity -- software engineers need to capture the context in which decisions were made and the rationale behind these decisions in order to understand the implications of a proposed change when revisiting a decision.
  • assists in dealing with changing systems
  • useful in the maintenance phase

Wasserman [5] identifies eight fundamental notions that form the basis for an effective discipline of software engineering:

• Abstraction -- a description of the problem at some level of generalization that allows us to concentrate on the key aspects of the problem without getting mired in the details
• Analysis and Design Methods and Notations -- when you work as a team, you must communicate with many other participants in the development process, and therefore need a common notation for communication and documentation
• Prototyping -- building a small version of a system, usually with limited functionality, helps the user to identify the key requirements of a system and demonstrates the feasibility of a design or approach; commonly used to design a good user interface
• Software Architecture -- the description of a system in terms of a set of architectural units, and a map of how the units relate to one another
• Software Process -- the organization and discipline in the activities of the process of developing software (as well as to the products that result) contribute to the quality of the software and the speed with which it is developed
• Reuse -- taking advantage of the commonalities across applications by reusing items from previous development
• Measurement -- quantitative descriptions of improvements to processes, resources, and methods permit us to compare progress across disparate projects and support analysis and decision-making
• Tools and Integrated Environment -- computer-aided software engineering (CASE) tools are designed to enhance software development, but rarely address the entire software development life cycle

Engineering: A New Definition

What is needed for the engineer of the future is a new definition -- one that includes the art and skill of problem-solving in broader socio-technologic issues and, as a need that will be with us forever, the art and skill of change management. In this context, no other career -- with the possible exception of medicine -- offers so much potential for personal reward, self esteem and enduring value to [humankind]. [6]

References