Software Engineering and AI: The Gigantic Picture


Introduction

AI research aims to devise techniques to make the computer perceive, reason and act. On the other hand, Software Engineering (SWE) aims to support humans in developing large software faster and more effectively. This article gives the gigantic picture on the relationship between both SWE and AI and how can they contribute to each other.

Software Engineering

The main concern of SWE is the efficient and effective development of high-qualitative and mostly very large software systems. The goal is to support software engineers and managers in order to develop better software faster with (intelligent) tools and methods.

How do they overlap?

Both deal with modeling real objects from the real world like business processes, expert knowledge or process models.

How can AI contribute to SWE Research?

1)    Translation of informal description of requirements to formal descriptions: Using natural language processing.

2)    Code Auto-Generation: Generating code from detailed design descriptions.

3)    AI Testing: The diversity of test cases while testing a SW may cause a buggy release (as not all test cases could be applied). AI’s role here is applying only the sufficient test cases (instead of all the test cases) – just as humans do – to save time.

4)  Software Size Estimation: Estimating the size of a proposed SW Project using Machine Learning techniques.

How can SWE contribute to AI Research?

1)    Systematic Development of AI Applications

2)    Operating of AI Applications in real-life environments

3)    Maintaining and improving AI applications.

Intersection between AI and SWE ( from: AI and SWE - Current and Future Trends - Jörg Rech & Klaus-Dieter Althoff )

Sciences lying in the intersection

Agent Oriented SWE – Knowledge Based SWE – Computational IntelligenceAmbient Intelligence

References

Artificial Intelligence and SWE – Status and Future Trends

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