Download e-book for kindle: Advances in Machine Learning Applications in Software by Du Zhang, Jeffrey J. P. Tsai

By Du Zhang, Jeffrey J. P. Tsai

ISBN-10: 1591409411

ISBN-13: 9781591409410

ISBN-10: 159140942X

ISBN-13: 9781591409427

ISBN-10: 1591409438

ISBN-13: 9781591409434

Desktop studying is the examine of creating laptop courses that increase their functionality via adventure. to satisfy the problem of constructing and holding higher and complicated software program platforms in a dynamic and altering atmosphere, laptop studying tools were taking part in an more and more very important position in lots of software program improvement and upkeep projects. Advances in computer studying functions in software program Engineering offers research, characterization, and refinement of software program engineering info when it comes to computing device studying tools. This publication depicts purposes of numerous computer studying ways in software program platforms improvement and deployment, and using desktop studying how to determine predictive versions for software program caliber. Advances in computer studying functions in software program Engineering additionally bargains readers course for destiny paintings during this rising examine box

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Is prohibited. TEAM LinG Intelligent Analysis of Software Maintenance Data 31 Table 9. 907 The bbm values assigned to the rules are presented in Table 9. The table contains only the rules that are best after the development stage (with the highest values of bbmT) and the ones that are the best after the validation stage (with the highest value of bbmUPDATE). 0 that are the best after the development process are also the best after the validation process (see bold entries in Table 9). For the rules NC_See5_c1_15 and NC_See5_c_2, their bbm values have increased after the validation phase.

All this and the high bbmUPDATE values indicate that these three rules can be useful in prediction of time needed to eliminate defects. _Incorrect or Other_Error & NUMBER OF COMMENTS in less than 130 or more than 181 & NUMBER OF PREPROCESSOR STATEMENTS is less than 5 or more than 10 & COMPLEXITY is Easy or Moderate & FUNCTIONALITY is Computational or Data_Accessing or Error_Handling then DEFECT ELIMINATION TIME is more than 1 hour but less than 1 day Rule ET_See5_c2_4: if DEFECT TYPE is Language_Use_Error & COMPLEXITY is Easy then DEFECT ELIMINATION TIME is more than 1 hour but less than 1 day Rule ET_GAGP_c2_6: if DEFECT_TYPE is Single_Design_Error or Other_Error & FUNCTIONALITY is Computational or Data_Accessing then DEFECT ELIMINATION TIME is more than 1 hour but less than 1 day Copyright © 2007, Idea Group Inc.

Copying or distributing in print or electronic forms without written permission of Idea Group Inc. is prohibited. TEAM LinG Intelligent Analysis of Software Maintenance Data 29 Table 7. List of attributes of the NRL data—Set II INPUT type of defect phase when defect entered system no. of components examined lines of code no. of comments no. of preprocessor statements subjective complexity functionality OUTPUT time needed to eliminate a defect requirements_incorrect, functional_spec_incorrect, single_design_error, multiple_design_error, language_error, clerical_error, multiple_errors, other requirements_definition, functional_specification, design, code_testing single component, multiple components <0, 635> <0, 360> <0, 42> easy, moderate, hard computational, control, data_processing, error_handling less than 1 hour between 1 hour and 1 day more than 1 day which these defects have been introduced into a system.

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Advances in Machine Learning Applications in Software Engineering by Du Zhang, Jeffrey J. P. Tsai


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