Software Process Control1 Aditya P. Mathur (CS) Department of Computer Sciences Purdue University, West Lafayette Research collaborators: João Cangussu (CS) Ray. A. DeCarlo (ECE) Friday February 1, 2002 Newton's Law of Motion in Software Development Processes? Presentation at: The Center for Advanced Computer Studies University of Louisiana, Lafayette, LA Room: HLG 147

Software Process Control2 Research Question Can we control the Software Development Process in a manner similar to how physical systems and processes are controlled ? The central problem in control is to find a technically feasible way to act on a given process so that the process adheres, as closely as possible to some desired behavior. The fundamental control problem (Ref: Control System Design by G. C. Goodwin et al., Prentice Hall, 2001) Furthermore, this approximate behavior should be achieved in the face of uncertainty of the process and in the presence of uncontrollable external disturbances acting on the process.

Software Process Control3 Research Methodology 1.Understand how physical systems are controlled? 2. Understand how software systems relate to physical systems. Are there similarities? Differences? 3. Understand the theory and practice of the control of physical systems. Can we borrow from this theory? 4.Adapt control theory to the control of SDP and develop models and methods to control the SDP. 5.Study the behavior of the models and methods in real-life settings and, perhaps, improve the model and methods. 6.Repeat steps 6 and 7 until you are thoroughly bored or get rich.

Software Process Control4 Feedback Control Specifications Program Effort + f(e) Additional effort What is f ? - Required Quality Observed Quality

Software Process Control5 Software Development Process: Definitions A Software Development Process (SDP) is a sequence of well defined activities used in the production of software. An SDP usually consists of several sub-processes that may or may not operate in a sequence. The Design Process, the Software Test Process, and the Configuration Management Process are examples of sub-processes of the SDP.

Software Process Control6 Software Development Process: A Life Cycle Requirements Elicitation Requirements Analysis Integrate/Test Design Code/Unit test System test More testDeploy Not all feedback loops are shown.

Software Process Control7 Current Focus Software Test Process (STP): System test phase Objective: Control the STP so that the quality of the tested software is as desired. Quantification of quality of software: Number of remaining errors Reliability

Software Process Control8 Problem Scenario cp 1 cp 2 cp 3 cp 4 cp 5 cp 6 cp 7 cp 8 cp 9 cp i = check point i rfrf schedule set by the manager approximation r0r0 observed deadline r - number of remaining errors t- time t0t0

Software Process Control9 Our Approach Actual STP Controller r error (t)  ’  w’ f + + wf+wfwf+wf  +  wf+wfwf+wf STP State Model r observed (t) r expected (t) scsc r0r0 scsc r0r0 Initial Settings (w f,  )  wfwf Test Manager wf: workforce  : quality of the test process.

Software Process Control10 Physical and Software Systems: An Analogy Dashpot Rigid surface External force Xcurrent Xequilibrium X: Position Number of remaining errors Spring Force Effective Test Effort Block Software Mass of the block Software complexity Quality of the test process Viscosity Spring To err is Human.

Software Process Control11 Physical Systems: Control Controllability Is it possible to control X (r) by adjusting Y (workforce and process quality)? Observability Does the system have distinct states that cannot be unambiguously identified by the controller ? Robustness Will control be regained satisfactorily after an unexpected disturbance?

Software Process Control12 Physical Systems: Laws of Motion [1] First Law: Every object in a state of uniform motion tends to remain in that state of motion unless an external force is applied to it. Does not apply to testing because the number of errors does not change when no external effort is applied to the application.

Software Process Control13 Physical Systems: Laws of Motion [2] Newton’s Second Law: The relationship between an object's mass m, its acceleration a, and the applied force F is F = ma. CDM’s First Law: The relationship between the complexity Sc of an application, its rate of reduction in the number of remaining errors, and the applied effort E is E=Sc. r..

Software Process Control14 Physical Systems: Laws of Motion [3] Third Law: For every action force, there is an equal and opposite reaction force. When an effort is applied to test software, it leads to fatigue on the tester. This is not a scientific relationship.

Software Process Control15 Assumption I: CDM’s First Law The magnitude of the rate of decrease of the remaining errors is directly proportional to the net applied effort and inversely proportional to the complexity of the program under test. This is analogous to Newton’s Second Law of motion.

Software Process Control16 Assumption II: CDM’s Second Law The magnitude of the effective test effort is proportional to the product of the applied work force and the number of remaining errors. for an appropriate . Analogy with the spring:

Software Process Control17 Assumption III: CDM’s Third Law The error reduction resistance is proportional to the error reduction velocity and inversely proportional to the overall quality of the test phase. for an appropriate . Analogy with the dashpot:

Software Process Control18 State Model : Disturbance

Software Process Control19 Computing the feedback

Software Process Control20 Case Study II: Razorfish Project Description Project Goal: translate 4 million lines of Cobol code to SAP/R3 A tool has been developed to achieve the goal of this project. Goal of the test process: (a) Test the generated code, not the tool. (b) Reduce the number of errors by about 85%.

Software Process Control21 Validation: Razorfish Project Testing Process Transformer = modify S SAP R/3 run output 1 output 2 run S Cobol Select a Test Profile input continue testing yes no

Software Process Control22 Case Study II: Razorfish Project Results 85% reduction achieved. If the process parameters are not altered then the goal is reached in about 35 weeks.

Software Process Control23 Alternatives from Feedback: STP Quality Desired eigenvalue= Improving quality alone will not help in achieving the goal.

Software Process Control24 Alternatives from Feedback: Workforce Desired eigenvalue= Changing the workforce alone can produce the desired results.

Software Process Control25 Alternatives from Feedback: STP quality and workforce Set of valid choices for changing the quality and the workforce

Software Process Control26 Summary Analogy between physical and software systems presented. The notion of feedback control of software processes introduced. One case study described. Parameter estimation techniques used for model calibration. Made use of system identification techniques.

Software Process Control27 Ongoing Research Expansion of the model to include the entire SDP. Additional case studies. Sensitivity analysis: r is more sensitive to changes in the model parameters during the early stages of the test process than during the later stages. An improvement in the quality of the STP is more effective than an increase in the workforce. Brook’s Law was also observed during the analysis.