Statistical Process Control Methods
OPS/574 v1
Process Improvement Flowchart
OPS/574 v1
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Process Improvement Flowchart
Evaluate the efficacy of your process using process improvement techniques.
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The feedback gathered by software measurement and therefore the evaluation of the consequences of the development provide a minimum of two benefits. By making the result visible, it motivates and justifies the trouble put into the initiative. Furthermore, it allows for a better evaluation of the SPI strategies and tactics. However, at an equivalent time, it's difficult to determine and implement a measurement program which provides relevant and valid information on which decisions are often based (Oktaba, 2007). There’s little agreement on what should be measured, and therefore the absence of a scientific and reliable measurement approach is considered an element that contributes to the high failure rate of improvement initiatives. no matter these problems in evaluating SPI initiatives, a plethora of evidence exists to point out that improvement efforts provide the expected benefits |
Process Improvement Flow Chart
Determine how the process can be improved based on the results of your evaluation.
· Plan the testing and QA processes
· Employ test-oriented software development management
· Conduct formal technical reviews
· Ensure suitable work
· Implement user acceptance testing onboarding
· Optimize the utilization of automated tests
Define metrics and measure the current process.
Development method metric
Software Quality Metrics
Weighted method per class (WMC)-WMC is that the sum of total methods during a class or the tactic complexity, which is measured via cyclometric complexity coupling between object classes (CBO)-CBO,is that the summation of classes that are including a specific class. Lack of Cohesion of Methods (LCOM)-LCOM may be a quality measurement metric for the category cohesiveness, which may be achieved by measuring common attributes in multiple methods. It calculates the extent of similarity between methods through data input variables or attributes.
Summary
List of references
Conradi, H., & Fuggetta, A. (2002). Improving software process improvement. IEEE software, 19(4), 92-99.
Oktaba, H., García, F., Piattini, M., Ruiz, F., Pino, F. J., & Alquicira, C. (2007). Software process improvement: The COMPETISOFT project. Computer, 40(10), 21-28.
Iversen, J. H., Mathiassen, L., & Nielsen, P. A. (2004). Managing risk in software process improvement: an action research approach. Mis Quarterly, 395-433.
Copyright 2020 by University of Phoenix. All rights reserved.
Copyright 2020 by University of Phoenix. All rights reserved.