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Achieving High Software Reliability Using a Faster, Easier and Cheaper Method

Achieving High Software Reliability Using a Faster, Easier and Cheaper Method. The Software Measurement Analysis and Reliability Toolkit. Taghi M. Khoshgoftaar. NASA OSMA SAS '01. September 5-7, 2001. NASA OSMA SAS '01. Outline. September 5-7, 2001. Introduction Overview of SMART

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Achieving High Software Reliability Using a Faster, Easier and Cheaper Method

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  1. Achieving High Software Reliability Using a Faster, Easier and Cheaper Method The Software Measurement Analysis and Reliability Toolkit Taghi M. Khoshgoftaar NASA OSMA SAS '01 September 5-7, 2001

  2. NASA OSMA SAS '01 Outline September 5-7, 2001 • Introduction • Overview of SMART • Data Analysis and Modeling Features • Current Utilization of SMART • Case-Based Reasoning • Empirical Study • Conclusions

  3. NASA OSMA SAS '01 Introduction September 5-7, 2001 • Necessity of an integrated tool for efficient empirical software quality research • Commercial packages are available but expensive and don’t always match our exact needs • In house development gives us availability, flexibility and possibility to evolve

  4. NASA OSMA SAS '01 Overview of SMART September 5-7, 2001 • First version back in 1998 • Current version 2.0 • Written in Microsoft Visual C++ • Runs on Microsoft Windows based platforms • User friendly GUI

  5. NASA OSMA SAS '01 SMART GUI September 5-7, 2001

  6. NASA OSMA SAS '01 SMART GUI September 5-7, 2001

  7. NASA OSMA SAS '01 Features included in SMART September 5-7, 2001 • Data management • Multiple Linear Regression (MLR) • Case-based reasoning (CBR), • Case-based reasoning with two group clustering • Case-based reasoning with three group clustering • Module order modeling (MOM)

  8. NASA OSMA SAS '01 Organizational Flowchart September 5-7, 2001

  9. NASA OSMA SAS '01 Current Utilization of SMARTat the ESEL Laboratory September 5-7, 2001 • Empirical research: • Comparative studies of software quality models • Case studies based on real world systems

  10. NASA OSMA SAS '01 Case Based Reasoning September 5-7, 2001 • Based on automated reasoning processes • Easy to use • Results are easy to understand and to interpret • Looks at past cases that are similar to the present case in an attempt to predict or classify an instance

  11. NASA OSMA SAS '01 Case Based Reasoning: Additional Advantages September 5-7, 2001 • The ability to alert users when a new case is outside the bounds of current experience • The ability to interpret the automated classification through the detailed description of the most similar case • The ability to take advantage of new or revised information as it becomes available • The ability for fast retrieval as the size of the library scales up

  12. NASA OSMA SAS '01 Case Based Reasoning September 5-7, 2001 • Working hypothesis for software quality modeling: • Current cases that are in development will more than likely be fault-prone if past cases having similar attributes were fault-prone

  13. NASA OSMA SAS '01 Case Based Reasoning: Comparing the Cases September 5-7, 2001 • Similar cases to a new module or nearest neighbors are determined by similarity functions: • Absolute Distance • Euclidean Distance • Mahalonobis Distance

  14. NASA OSMA SAS '01 Case Based Reasoning: Prediction Methods September 5-7, 2001 • The value of the dependent variable is estimated using the values of the dependent variables of the nearest neighbors and a solution algorithm: • Unweighted Average • Inverse-Distance Weighted Average

  15. NASA OSMA SAS '01 Case Based Reasoning: Classification Methods September 5-7, 2001 • Used to classify a software module into a particular class (fault-prone, not fault-prone). • The types of classification methods include: • Majority Voting • Data Clustering

  16. NASA OSMA SAS '01 Case Study: System Description September 5-7, 2001 • Two data sets were obtained from two large Windows-based applications used primarily for customizing the configuration of wireless products. The data sets were obtained from the initial release of these applications. The applications are written in C++, and they provide similar functionality.

  17. NASA OSMA SAS '01 Case Study: System Description September 5-7, 2001

  18. Case Study:Data Collection Effort • Data collected by engineers over several months using the available information in: • Configuration Management Systems • Problem Reporting Systems

  19. NASA OSMA SAS '01 Case Study:Independent Variables September 5-7, 2001

  20. NASA OSMA SAS '01 Case Study:Accuracy Evaluation September 5-7, 2001 • Average Absolute Error: • Average Relative Error:

  21. NASA OSMA SAS '01 Case Study:Prediction Results September 5-7, 2001

  22. NASA OSMA SAS '01 Case Study:Classification Evaluation September 5-7, 2001

  23. NASA OSMA SAS '01 Case Study:Classification Results September 5-7, 2001 • Entire data set: • Fit and Test data set:

  24. NASA OSMA SAS '01 Case Study:Return On Investment September 5-7, 2001 • Classification using CBR

  25. NASA OSMA SAS '01 Conclusion September 5-7, 2001 • A tool that matches our needs • Used for our extensive empirical work • Proved useful on large scale case study • Faster • Easier • Cheaper • Ready for future enhancement

  26. NASA OSMA SAS '01 Reminder September 5-7, 2001 We will be presenting the tool on Friday, Please feel free to visit us!

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