Computational Intelligence in Software Quality Assurance

Pirmais vāks
World Scientific, 2005 - 180 lappuses
Software systems surround us. Software is a critical component in everything from the family car through electrical power] systems to military equipment. As software ploys an ever-increasing role in our lives and livelihoods, the quality of that software becomes more and more critical. However, our ability to deliver high-quality software has not kept up with those increasing demands. The economic fallout is enormous; the US economy alone is losing over US$50 billion per year due to software failures. This book presents new research into using advanced artificial intelligence techniques to guide software quality improvements. The techniques of chaos theory and data mining arc brought to bear to provide new insights into the software development process. Written for researchers and practitioners in software engineering and computational intelligence, this book is a unique and important bridge between these two fields.

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Autortiesības

Citi izdevumi - Skatīt visu

Computational Intelligence in Software Quality Assurance
Scott Dick,Abraham Kandel
Ierobežota priekšskatīšana - 2005
Computational Intelligence in Software Quality Assurance
S Dick,A Kandel
Ierobežota priekšskatīšana - 2005

Bieži izmantoti vārdi un frāzes

application approach architecture Artificial Intelligence attributes automated average SSE chaos theory chaotic systems Chapter cluster validity Code_Chars Computational Intelligence computationally intelligent correlation cyclomatic complexity data mining database determine deterministic behavior dimension distribution domain error experiments failure rate fault Figure fractal sets function fuzzy clustering fuzzy set Fuzzy Systems genetic algorithm Halstead's IEEE Transactions input iterative Kandel machine learning machine learning algorithms methods metric values MIS dataset modules neural networks noise nonlinear time series number of failures object-oriented ODC1 ODC4 OOSoft operations optimization partition phase portrait pilot system prediction problem Proceedings ProcSoft dataset random regression relationship Reliability Engineering resampling series analysis skewed software development Software Engineering software failures software metrics software quality Software Reliability Engineering software reliability growth software reliability modeling software system software testing source code specific statistical stochastic process Table techniques Transactions on Reliability Transactions on Software unsupervised learning vectors waterfall model

Bibliogrāfiskā informācija

NosaukumsComputational Intelligence in Software Quality Assurance
Grāmatas Series in machine perception and artificial intelligence 63. sējums. sējums
AutoriScott Dick, Abraham Kandel
Izdevums:ilustrēts
IzdevējsWorld Scientific, 2005
ISBN9812561722, 9789812561725
Apjoms180 lappuses
  
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