Metody statystyczne Copyright, 2001 © Jerzy R. Nawrocki Doskonalenie Procesów Programowych Wykład 8

J. Nawrocki, DPP, Wykład 8 Introduction.. Project planning.. Size estimating

J. Nawrocki, DPP, Wykład 8 Introduction Time & defect recording Time & defect recording Coding strd+Size measuremnt+PIP Coding strd+Size measuremnt+PIP Size estimating + Test report Task & schedule planning Code & design reviews Code & design reviews Design templates Design templates Cyclic dev. Cyclic dev. Baseline Planning Quality Cyclic

J. Nawrocki, DPP, Wykład 8 Plan of the lecture IntroductionIntroduction The Probe methodThe Probe method ExampleExample Effort estimationEffort estimation

J. Nawrocki, DPP, Wykład 8 Probe method Humphrey, CMU, 1995 PROxy-Based Estimating Objects as proxies HistoricaldataStatisticalmethods Probemethod

J. Nawrocki, DPP, Wykład 8 Planning a software project Conceptual design Size estimates Resource estimates The schedule The product RequirementsRequirements Size database Productivity database Resources available Size, res., sched. data

J. Nawrocki, DPP, Wykład 8 Probe method Conceptual design Calculate projected and modified LOC Estimate program size Calculate prediction interval Identify objects Number of Object Relative Reuse methods type size categories Identify objects Number of Object Relative Reuse methods type size categories

J. Nawrocki, DPP, Wykład 8 Probe method 1. Prepare a conceptual design (objects and methods + their function)

J. Nawrocki, DPP, Wykład 8 Probe method 2. For each object assign its type. Skyscraper Church Garage Logic Logic I/O I/O Text Text Calculation Calculation Data Data Set-up Set-up

J. Nawrocki, DPP, Wykład 8 Probe method 3. For each object assign one of size ranges. Very big Big Medium Small Very small

J. Nawrocki, DPP, Wykład 8 Probe method 4. Knowing: programming language object type size ranges the number of methods estimate, using historical data, size of each object.

J. Nawrocki, DPP, Wykład 8 Probe method 5. Determine initial program estimated size, X, adding the values received in the previous step = = 5

J. Nawrocki, DPP, Wykład 8 Probe method 6. Apply linear regression to get estimated program size Y: Y =  1 X +  0 5 means 10 5 means 10

J. Nawrocki, DPP, Wykład 8 Probe method  x i y i - n x avg y avg  x i y i - n x avg y avg  x i 2 - n x avg 2  x i 2 - n x avg 2 1 = 1 = 1 = 1 =  0 = y avg -  1 x avg  0 = y avg -  1 x avg

J. Nawrocki, DPP, Wykład 8 Probe method 7. Using the t distribution and standard deviation compute the prediction interval for a given percentage. For 100% the For 100% the interval is [0; +  ]

J. Nawrocki, DPP, Wykład 8 Probe method 7a. Calculate the standard deviation, , of your historical data around the regression line. 1  2 = (y i -  0 -  1 x i ) 2 n-2 n-2  i=1n

J. Nawrocki, DPP, Wykład 8 Probe method 7b. To find the two-sided value of t for the probability q, look in a table of the t distribution under p(  )= (1+q)/2 and n-2 degree of freedom.

J. Nawrocki, DPP, Wykład 8 The t distribution

J. Nawrocki, DPP, Wykład 8 Probe method (X - x avg ) 2  (x i - x avg ) n +1  Range = t    7c. Compute the range as follows: Initial estimate obtained in Step 5

J. Nawrocki, DPP, Wykład 8 Plan of the lecture IntroductionIntroduction Probe methodProbe method ExampleExample Effort estimationEffort estimation

J. Nawrocki, DPP, Wykład 8 Example Program to be modified MatrixMatrixLinearsystemLinearsystemLinkedlistLinkedlist Data entry Base program

J. Nawrocki, DPP, Wykład 8 Example Program to be modified MatrixMatrixLinearsystemLinearsystemLinkedlist1Linkedlist1 Data entry Base program Linkedlist2Linkedlist2

J. Nawrocki, DPP, Wykład 8 Example Assignment of numbers to fuzzy values

J. Nawrocki, DPP, Wykład 8 Example Base program LOC modified (M) LOC modified (M) New objects Type Methods Size Total LOC Matrix Data 13 Medium 115 Matrix Data 13 Medium 115 Linear sys. Calc. 8 Large 197 Linear sys. Calc. 8 Large 197 Linked list 1 Data 3 Large 49 Linked list 1 Data 3 Large 49 Total new & modified (X)     Estimated new & modified (Y)

J. Nawrocki, DPP, Wykład 8 Example Estimated new & modified (Y) Prediction percent % p = (1 + percent)/ Number of programs in historical DB (n) Std deviation  from regression line Degrees of freedom (n-2) t (8, 0.9)  (1 + 1/ ) Prediction range Upper interval (Y + range) Lower interval (Y - range)

J. Nawrocki, DPP, Wykład 8 Plan of the lecture IntroductionIntroduction The Probe methodThe Probe method ExampleExample Effort estimationEffort estimation

J. Nawrocki, DPP, Wykład 8 Effort estimation begin.. end Programs written so far Historical data It should take... a man month to finish the project

J. Nawrocki, DPP, Wykład 8 Effort estimation begin.. end Estimatedsize Actualtime Historical data

J. Nawrocki, DPP, Wykład 8 Effort estimation begin.. end Estimatedsize Actualtime Historical data r 2  0.5

J. Nawrocki, DPP, Wykład 8 Effort estimation Estimated size Actual time 1.  0,  1 2. Effort =  1 * Estimated_size +  n +1  3. Range = t    r 2  Effort min = Effort - Range

J. Nawrocki, DPP, Wykład 8 Summary Size estimation is a basis for effort estimation and planning The Probe method: Historical data are needed. Statistical methods are used. Programmer obtains not only the estimate but also a prediction interval.

J. Nawrocki, DPP, Wykład 8 Further readings W. Humphrey, A Discipline for Software Engineering, Addison- Wesley, Reading, 1995, Chapter 5.

J. Nawrocki, DPP, Wykład 8 Quality assessment 1. What is your general impression ? (1 - 6) 2. Was it too slow or too fast ? 3. Did you learn something important to you ? 4. What to improve and how ?