160 ◾ Simple Statistical Methods for Software Engineering
Review Questions
1. What is the commonly used rule for selecting number of bins in a histogram?
2. Mention three purposes for extracting histograms from data.
3. What is meant by a bimodal histogram?
4. What are the elements of a histogram signature?
5. How can you judge process capability from a process data histogram?
Exercises
1. Construct a histogram using the following customer satisfaction data and
extract the signature of customer satisfaction. Interpret the signature.
4, 5, 3; 5, 4, 5, 5, 4, 3, 4, 5, 3, 4, 5, 3, 2, 3, 2, 4, 1, 4,
1, 5, 4, 3, 4, 3, 2, 3, 2, 4, 3, 4, 3, 5, 4, 3, 5, 4, 4, 4, 4
2. Use MS Excel’s data analysis tool Histogram to construct the histogram.
Instead of allowing default bin selection, specify your own bins.
3. If the corporate goal is to get a customer satisfaction score of at least 3, what
is the risk seen in the previously mentioned histogram signature?
4. Test case rework effort data in person-hours are given as follows:
16, 16, 2, 5, 7, 8.5, 8, 9, 10, 11, 5
Draw a histogram with this limited data and try to draw inferences about
the test case development process.
5. Effort variance data in a software enhance project is shown as follows:
−10, 4, 5, −3, 8, −2, 0, 9, 5, −2, 5, 3, 5, 12
Draw an ogive of the given data.
0
2
4
6
8
10
12
0 2 4 6 8 10
Frequency
Coupling
Figure A10.2 Frequency diagram.
Pattern Extraction Using Histogram ◾ 161
References
1. G. P. Kulk and C. Verhoef, Quantifying requirements volatility effects, Science of
Computer Programming, 72, 136–175, 2008.
2. L. Rosenberg, Applying and interpreting object oriented metric, Software Technology
Conference, Utah, April 1998.
3. L. R. Beaumont, Metrics—A Practical Example, AT&T Bell Laboratories. Available at
http://www.humiliationstudies.org/documents/Beaumontmetricsid.pdf.
4. H. Barkman, R. Lincke and W. Lowe, Quantitative Evaluation of Software Quality
Metrics in Open-Source Projects, Software Technology Group, School of Mathematics
and Systems Engineering, Sweden. Available at http://www.arisa.se/Files/BLL-09.
5. L. Liu, W. Lai, X.-S. Hua and S.-Q. Yang, Video Histogram: A Novel Video Signature
for Ecient Web Video Duplicate Detection, Department of Computer Science and
Technology, Tsinghua University, Microsoft Research, Asia, Springer Verlag Berlin,
Heidelberg, 2007.
6. M. K. Kowar and S. Yadav, Brain tumor detection and segmentation using histogram
thresholding, International Journal of Engineering and Advanced Technology, 1(4),
16–20, 2012.
7. W. E. Barkman, In-Process Quality Control for Manufacturing, CRC Press, New York,
1989.
8. T. Weninger and W. H. Hsu, Web Content Extraction rough Histogram Clustring,
Kansas State University, Manhattan, Annie Conference, November 9–12, St. Louis,
Missouri., 2008.
9. D. J. Monroe, e Entitlement Trap, Juran Institute, Inc., 2009.
10. W. Curry, G. Succi, M. Smith, E. Liu and R. Wong, Empirical Analysis of the Correlation
between Amount-of-Reuse Metrics in the C Programming Language, ACM, New York,
135–140, 1999.
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