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ECE 453 – CS 447 – SE 465 Software Testing & Quality Assurance Case Studies Instructor Paulo Alencar. Recommended.

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  1. ECE 453 – CS 447 – SE 465 Software Testing & Quality AssuranceCase StudiesInstructorPaulo Alencar

  2. Recommended 1. Olague, H., Etzkorn, L., Ghoston, S., Quattlebaum, S., Empirical Validation of Three Software Metric Suites to Predict Fault-Proneness of Object-Oriented Classes Developed Using Highly Iterative or Agile Software Development Process, IEEE Transactions on Software Engineering, vol. 33, no.4, pp. 402-419, 2007. 2. Fioravanti, F., Nesi, P., Estimation and Prediction Metrics for Adaptive Maintenance Effort of Object-Oriented Systems, IEEE Transactions on Software Engineering, vol. 27, no. 12, pp. 1062-1082, 2001. 2

  3. Recommended 3. Subramanyam, R., Krishnan, M., Empirical Analysis of CK Metrics for Object-Oriented Design Complexity: Implications for Software Defects, IEEE Transactions on Software Engineering, vol. 29, no.4, pp. 297-310, 2003. 4. Bandi, R., Vaishnavi, V., Turk, D., Predicting Maintenance Performance Using Object-Oriented Design Complexity Metrics, IEEE Transactions on Software Engineering, vol. 29, no. 1, pp.77-87, 2003. 3

  4. Overview To assess the ability of OO metrics to identify fault-prone components in different development environments (e.g., agile process) Validation of three OO metric suites A large software system is evaluated (Mozilla Rhino project) Olague, H., Etzkorn, L, Ghoston, S., Quattlebaum, S., Empirical Validation of Three Software Metric Suites to Predict Fault-Proneness of Object-Oriented Classes Developed Using Highly Iterative or Agile Software Development Process, IEEE Transactions on Software Eng., vol. 33(6), pp. 402-419, 2007. 4

  5. Main Results • Metric definitions – first suite:

  6. Main Results • Metric definitions – second suite:

  7. Main Results • Metric definitions – third suite:

  8. Main Results • Software examined: Mozilla Rhino – an open source implementation of JavaScript written in Java • An example of the use of the agile software development in open source software • Six Rhino versions were analyzed in this case study • Delivery cycle time from 2 to 16 months

  9. Main Results • Hypotheses: • Hypothesis 1: OO metrics can identify fault-prone classes in traditional and highly iterative or agile developed OO software during its initial delivery • Hypothesis 2: OO metrics can identify fault-prone classes in multiple sequential releases of OO software systems developed and using highly iterative or agile software development process

  10. Main Results • Model validation:

  11. Main Results • CK and QMOOD suites contain similar components and produce statistical models that are effective in detecting error-prone classes • MOOD metrics suite are not good class fault-proneness predictors • The produced models can be useful in assessing quality in OO classes developed using modern highly iterative or agile software development processes

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