Current Search:  Computer software--Testing (x)

View All Items

  • CSV Spreadsheet
(1 - 4 of 4)
Choosing software reliability models
Title
Choosing software reliability models.
Creator
Woodcock, Timothy G., Florida Atlantic University, Khoshgoftaar, Taghi M.
Abstract/Description
One of the important problems which software engineers face is how to determine which software reliability model should be used for a particular system. Some recent attempts to compare different models used complementary graphical and analytical techniques. These techniques require an excessive amount of time for plotting the data and running the analyses, and they are still rather subjective as to which model is best. So another technique needs to be found that is simpler and yet yields a...
Show moreOne of the important problems which software engineers face is how to determine which software reliability model should be used for a particular system. Some recent attempts to compare different models used complementary graphical and analytical techniques. These techniques require an excessive amount of time for plotting the data and running the analyses, and they are still rather subjective as to which model is best. So another technique needs to be found that is simpler and yet yields a less subjective measure of goodness of fit. The Akaike Information Criterion (AIC) is proposed as a new approach for selecting the best model. The performance of AIC is measured by Monte-Carlo simulation and by comparison to published data sets. The AIC chooses the correct model 95% of the time.
Show less
Date Issued
1989
PURL
http://purl.flvc.org/fcla/dt/14561
Subject Headings
Computer software--Testing, Computer software--Reliability
Format
Document (PDF)
Multivariate modeling of software engineering measures
Title
Multivariate modeling of software engineering measures.
Creator
Lanning, David Lee., Florida Atlantic University, Khoshgoftaar, Taghi M., College of Engineering and Computer Science, Department of Computer and Electrical Engineering and Computer Science
Abstract/Description
One goal of software engineers is to produce software products. An additional goal, that the software production must lead to profit, releases the power of the software product market. This market demands high quality products and tight cycles in the delivery of new and enhanced products. These market conditions motivate the search for engineering methods that help software producers ship products quicker, at lower cost, and with fewer defects. The control of software defects is key to...
Show moreOne goal of software engineers is to produce software products. An additional goal, that the software production must lead to profit, releases the power of the software product market. This market demands high quality products and tight cycles in the delivery of new and enhanced products. These market conditions motivate the search for engineering methods that help software producers ship products quicker, at lower cost, and with fewer defects. The control of software defects is key to meeting these market conditions. Thus, many software engineering tasks are concerned with software defects. This study considers two sources of variation in the distribution of software defects: software complexity and enhancement activity. Multivariate techniques treat defect activity, software complexity, and enhancement activity as related multivariate concepts. Applied techniques include principal components analysis, canonical correlation analysis, discriminant analysis, and multiple regression analysis. The objective of this study is to improve our understanding of software complexity and software enhancement activity as sources of variation in defect activity, and to apply this understanding to produce predictive and discriminant models useful during testing and maintenance tasks. These models serve to support critical software engineering decisions.
Show less
Date Issued
1994
PURL
http://purl.flvc.org/fcla/dt/12383
Subject Headings
Software engineering, Computer software--Testing, Computer software--Quality control
Format
Document (PDF)
Cost of misclassification in software quality models
Title
Cost of misclassification in software quality models.
Creator
Guan, Xin., Florida Atlantic University, Khoshgoftaar, Taghi M.
Abstract/Description
Reliability has become a very important and competitive factor for software products. Using software quality models based on software measurements provides a systematic and scientific way to detect software faults early and to improve software reliability. This thesis considers several classification techniques including Generalized Classification Rule, MetaCost algorithm, Cost-Boosting algorithm and AdaCost algorithm. We also introduce the weighted logistic regression algorithm, and a new...
Show moreReliability has become a very important and competitive factor for software products. Using software quality models based on software measurements provides a systematic and scientific way to detect software faults early and to improve software reliability. This thesis considers several classification techniques including Generalized Classification Rule, MetaCost algorithm, Cost-Boosting algorithm and AdaCost algorithm. We also introduce the weighted logistic regression algorithm, and a new method to evaluate the performance of classification models---ROC Analysis. We focus our experiments on a very large legacy telecommunications system (LLTS) to build software quality models with principal components analysis. Two other data sets, CCCS and LTS are also used in our experiments.
Show less
Date Issued
2000
PURL
http://purl.flvc.org/fcla/dt/15762
Subject Headings
Computer software--Quality control, Software measurement, Computer software--Testing
Format
Document (PDF)
empirical study of combining techniques in software quality classification
Title
An empirical study of combining techniques in software quality classification.
Creator
Eroglu, Cemal., Florida Atlantic University, Khoshgoftaar, Taghi M.
Abstract/Description
In the literature, there has been limited research that systematically investigates the possibility of exercising a hybrid approach by simply learning from the output of numerous base-level learners. We analyze a hybrid learning approach upon the systems that had previously been worked with twenty-four different classifiers. Instead of relying on only one classifier's judgment, it is expected that taking into account the opinions of several learners is a wise decision. Moreover, by using...
Show moreIn the literature, there has been limited research that systematically investigates the possibility of exercising a hybrid approach by simply learning from the output of numerous base-level learners. We analyze a hybrid learning approach upon the systems that had previously been worked with twenty-four different classifiers. Instead of relying on only one classifier's judgment, it is expected that taking into account the opinions of several learners is a wise decision. Moreover, by using clustering techniques some base-level classifiers were eliminated from the hybrid learner input. We had three different experiments each with a different number of base-level classifiers. We empirically show that the hybrid learning approach generally yields better performance than the best selected base-level learners and majority voting under some conditions.
Show less
Date Issued
2004
PURL
http://purl.flvc.org/fcla/dt/13162
Subject Headings
Computer software--Testing, Computer software--Quality control, Computational learning theory, Machine learning, Digital computer simulation
Format
Document (PDF)