Book Chapter10.4018/978-1-60960-818-7.CH504
Artificial Intelligence in Software Engineering: Current Developments and Future Prospects
Farid Meziane,Sunil Vadera +1 more
- 01 Jan 2012
- pp 1215-1236
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TL;DR: This chapter provides a survey on the use of AI for software engineering that covers the main software development phases and AI methods such as natural language processing techniques, neural networks, genetic algorithms, fuzzy logic, ant colony optimization, and planning methods.
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Abstract: Artificial intelligences techniques such as knowledge based systems, neural networks, fuzzy logic and data mining have been advocated by many researchers and developers as the way to improve many of the software development activities. As with many other disciplines, software development quality improves with the experience, knowledge of the developers, past projects and expertise. Software also evolves as it operates in changing and volatile environments. Hence, there is significant potential for using AI for improving all phases of the software development life cycle. This chapter provides a survey on the use of AI for software engineering that covers the main software development phases and AI methods such as natural language processing techniques, neural networks, genetic algorithms, fuzzy logic, ant colony optimization, and planning methods.
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Citations
Software Engineering Using Artificial Intelligence Techniques: Current State and Open Problems
Hany H. Ammar,W. Abdelmoez,Mohamed Hamdi +2 more
- 01 Jan 2012
TL;DR: This survey paper relates AI techniques to software engineering processes specified by the IEEE 12207 standard of software engineering, and brings the state of the art of AI techniques closer to the software engineer, and highlights the open research problems for the research community.
50
Search-based test case generation for object-oriented Java software using strongly-typed genetic programming
José Carlos Bregieiro Ribeiro
- 01 Jul 2008
TL;DR: The focus of the on-going work is on employing evolutionary algorithms for the structural unit-testing of object-oriented Java programs, and the introduction of novel methodologies for automation, search guidance and input domain reduction.
34
Artificial Intelligence Techniques in Software Engineering for Automated Software Reuse and Design
Divanshi Priyadarshni Wangoo
- 01 Dec 2018
TL;DR: An analysis of several AI techniques in software reuse domain of software engineering is discussed for automated software reuse and identification of potential research prospects in the field.
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•Journal Article
The Definition of Intelligent Computer Aided Software Engineering (I-CASE) Tools
TL;DR: The definition of Intelligent Computer Aided Software Engineering (I-CASE) is presented, which encompasses a clear decomposition of each basic software development activity to sub activities, and classify each one of them whether it is an intellectual or procedural job.
A hybrid model for agile practices using case based reasoning
Mehwish Mukhtar,Yasir Hafeez Motla,M. Riaz,M. Afzaal Khan,Mehmood Ahmed,M. Azeem Abbas,Hummera Naz,Asma Batool +7 more
- 23 May 2013
TL;DR: The model provides a guideline to the Agile Software Development regarding enhancement of Agile Practices incorporated with CBR and expert's response method is applied to accomplish the appraisal of this model.
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References
•Book
Automated Planning, Theory And Practice
Malik Ghallab,Dana S. Nau,Paolo Traverso +2 more
- 01 Jan 2006
TL;DR: This chapter discusses Classical Planning and its Applications, as well as Neoclassical and Neo-Classical Techniques, and discusses search procedures and Computational Complexity.
Object-oriented development
TL;DR: The author examines the process of object-oriented development as well as the influences upon this approach from advances in abstraction mechanisms, programming languages, and hardware.
Software Testing Research: Achievements, Challenges, Dreams
Antonia Bertolino
- 23 May 2007
TL;DR: A consistent roadmap of the most relevant challenges to be addressed in software testing research is proposed, constituted by some important past achievements, while the destination consists of four identified goals to which research ultimately tends, but which remain as unreachable as dreams.
Strongly typed genetic programming
TL;DR: Strongly typed genetic programming (STGP) is an enhanced version of genetic programming that enforces data-type constraints and whose use of generic functions and generic data types makes it more powerful than other approaches to type-constraint enforcement.
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