Overview

The first 31 chapters of this text have explored a process for software engineering. This chapter discusses some issues to consider when trying understand how software and software engineering will change in the future. Predicting future trends in any field requires collecting data, organizing it, looking for subtle associations to extract knowledge, and using this knowledge to suggest probable future occurrences. A short-term prediction may or may not prove to be true and yet, may still be true in the long term.

Importance of Software

• Software as a differentiator (products, systems, services, competitive advantages in the marketplace)
• Software generates valuable information (programs, documents, data)
• Mechanism for automating business, industry, and government
• Medium for transferring new technologies
• Means of capturing people's expertise for use by others
• Software is a hidden technology, embedded in daily activities and used without customers thinking about it

Scope of Change

• Changes in computing over the past 50 years have been driven by advances in the hard sciences (physics, chemistry, materials science, engineering)
• During the next several decades changes in computing are likely to be driven by the soft sciences (human psychology, biology, neurophysiology, sociology, philosophy)
• Changes in software engineering will be influenced by

• people who do the work
• processes they apply
• nature of information
• underlying computer technology

People and Systems Construction

• Systems are becoming more complex, requiring larger programs and more people involved in their construction
• Communications between individual software engineers and between specialized teams working on the same project will need to be improved to avoid losing information
• The evolution of intelligent agents may change the work patterns of software engineers by extending the capabilities of software tools
• The World Wide Web has made many changes in the ways that people acquire and access knowledge

New Software Engineering Process

• The first two decades of software engineering were characterized by linear thinking, yet linear systems development runs contrary to the ways in which most software systems are actually built
• Evolutionary process models recognize that uncertainty dominates most development activities
• Modern development time lines are impossibly short, iterative delivery of partial products provides crucial functionality when complete product delivery is not possible
• The Capability Maturity Model provides a good indicator about what attributes should exist when solid software engineering is practiced
• Object technologies coupled with component-based software engineering are a natural outgrowth of the evolutionary process model trend
• Customer involvement early in the design process is likely to be observed more frequently
• Rapid growth in Web-based applications development is changing both the software engineering process (focus in immediacy, security, and aesthetics) and it participants (melding content non-technical specialists with software designers)

New Modes for Representing Information

• Data processing has been replaced by the term information technology
• Emphasis is shifting from managing large quantities of data to extracting meaningful information from this data
• Knowledge engineering techniques may begin migrating form the artificial intelligence laboratories to the application domain as people seeks ways to associate information from more than one context
• Software systems may be viewed in the future as systems the extract knowledge from data and information (many knowledge bases have already been created)