This document provides an overview of statistical process control (SPC) concepts including control charts, process capability, and applying SPC to services. It discusses control charts for attributes like p-charts and c-charts and control charts for variables like x-bar charts and R-charts. It also covers determining control limits, identifying patterns in control charts, and using Excel for SPC.
The presentation depicted herein presents briefly an introduction of acceptance sampling along with some major differences amongst the widely used sampling standards.
Acceptance Sampling standards comparison. MIL-STD-105E, MIL-STD-1916, ISO 2859, ISO 3951. About AQLs and OC Curves.
Smartphone applications are developed with immense creativity and effort. Mobile users demand a sleeker experience with applications compared to desktop users. The mindset of mobile users is very different from web or desktop users. Smartphone apps are used on the move (e.g.: while walking or using a toilet), and mobile devices have a lot to offer through hardware location tracking, gyroscopes and other integrated features. So, how to tune the tester’s mindset to model test approaches specific to smartphone apps? Smartphone apps focus on speed, size and sleek. How to design tests at the UI level to identify issues beyond the usual functional and non-functional testing? Even if a smartphone app has a sleek UI, users will uninstall the app if it drains their battery, crashes frequently or wastes the user’s data plan. So, how to design mobile tests and what tools to use to uncover issues hidden under mobile UI.
Mobile testing is very important from the moment you start thinking about making a mobile app to its release and all the further updates. In this slideshow are some of the main challenges developers have to face while building and updating a mobile app.
Addressing Mobile App Testing ChallengesLee Barnes
If the mobile technology train hasn’t arrived at your organization yet, it soon will. Are you ready to jump onboard and face the unique testing challenges presented by mobile applications? In this session, Lee will lead a journey to help you understand where mobile quality is, where it’s going, why it matters to you, and what you can do to help ensure mobile quality in your organization. Lee’s presentation will highlight testing challenges specific to mobile apps and present mobile testing best practices including techniques for leveraging test automation on mobile platforms. You will understand why testing in a mobile environment is different from traditional software testing and learn how to address the unique testing challenges presented by mobile applications. Attend this talk and walk away with a solid mobile testing baseline and best practices for addressing the challenges that lie ahead.
Techniques, Tips & Tools For Mobile App TestingSOASTA
Today, mobile app testing expertise is in high demand and offers an exciting career path in test/QA. However, the recent Future of Testing study, sponsored by TechWell, noted that the biggest challenge in mobile―just behind having enough time to test―is expertise. Brad Johnson shares how companies from banking to retail use data from real production users, continuous integration frameworks, cloud-based testing platforms, and real mobile devices to help ensure every user experiences top-rated performance—all the time. Brad shares insight about what to test for mobile, when to first automate, and a metric that will drive real change. Explore how organizations are communicating across teams and improving developer-to-tester collaboration with new approaches. Testers need to develop new skills ranging from software coding requirements to data science. Takeaway tips and ideas to impact your company, enhance your skill set, and propel your career with exciting options and new challenges.
The presentation depicted herein presents briefly an introduction of acceptance sampling along with some major differences amongst the widely used sampling standards.
Acceptance Sampling standards comparison. MIL-STD-105E, MIL-STD-1916, ISO 2859, ISO 3951. About AQLs and OC Curves.
Smartphone applications are developed with immense creativity and effort. Mobile users demand a sleeker experience with applications compared to desktop users. The mindset of mobile users is very different from web or desktop users. Smartphone apps are used on the move (e.g.: while walking or using a toilet), and mobile devices have a lot to offer through hardware location tracking, gyroscopes and other integrated features. So, how to tune the tester’s mindset to model test approaches specific to smartphone apps? Smartphone apps focus on speed, size and sleek. How to design tests at the UI level to identify issues beyond the usual functional and non-functional testing? Even if a smartphone app has a sleek UI, users will uninstall the app if it drains their battery, crashes frequently or wastes the user’s data plan. So, how to design mobile tests and what tools to use to uncover issues hidden under mobile UI.
Mobile testing is very important from the moment you start thinking about making a mobile app to its release and all the further updates. In this slideshow are some of the main challenges developers have to face while building and updating a mobile app.
Addressing Mobile App Testing ChallengesLee Barnes
If the mobile technology train hasn’t arrived at your organization yet, it soon will. Are you ready to jump onboard and face the unique testing challenges presented by mobile applications? In this session, Lee will lead a journey to help you understand where mobile quality is, where it’s going, why it matters to you, and what you can do to help ensure mobile quality in your organization. Lee’s presentation will highlight testing challenges specific to mobile apps and present mobile testing best practices including techniques for leveraging test automation on mobile platforms. You will understand why testing in a mobile environment is different from traditional software testing and learn how to address the unique testing challenges presented by mobile applications. Attend this talk and walk away with a solid mobile testing baseline and best practices for addressing the challenges that lie ahead.
Techniques, Tips & Tools For Mobile App TestingSOASTA
Today, mobile app testing expertise is in high demand and offers an exciting career path in test/QA. However, the recent Future of Testing study, sponsored by TechWell, noted that the biggest challenge in mobile―just behind having enough time to test―is expertise. Brad Johnson shares how companies from banking to retail use data from real production users, continuous integration frameworks, cloud-based testing platforms, and real mobile devices to help ensure every user experiences top-rated performance—all the time. Brad shares insight about what to test for mobile, when to first automate, and a metric that will drive real change. Explore how organizations are communicating across teams and improving developer-to-tester collaboration with new approaches. Testers need to develop new skills ranging from software coding requirements to data science. Takeaway tips and ideas to impact your company, enhance your skill set, and propel your career with exciting options and new challenges.
Software Quality Metrics for Testers - StarWest 2013XBOSoft
Presentation by Phil Lew at StarWest 2013.
When implementing software quality metrics, we need to first understand the purpose of the metrics and who will be using them. Will the metric be used to measure people or the process, to illustrate the level of quality in software products, or to drive toward a specific objective? QA managers typically want to deliver productivity metrics to management but management may want to see metrics that describe customer or user satisfaction. Philip Lew believes that software quality metrics without actionable objectives toward increasing customer satisfaction are a waste of time. Learn how to connect each metric with potential actions based on evaluating the metric. Metrics for the sake of information may be helpful but often just end up in spreadsheets of interest to no one. Take home methods to identify metrics that support actionable objectives. Once the metrics and their objectives have been established, learn how to define and use metrics for real improvement.
SwaamTech, is an independent QA and Software Testing company helping clients to bring quality in there products. Contact us for testing of your SmartPhone App testing: support@swaam.com
Testing Techniques for Mobile ApplicationsIndicThreads
With the fantastic growth of mobile computing platforms such as the iPhone, Blackberry,Symbian, J2ME, Windows Mobile and Android environments, there has been a dramatic increase in the value of mobile applications for most companies.
However, one of the biggest challenges that one faces when developing a mobile application is how to test it. Testing Mobile applications is a very intricate and arduous undertaking. There are an enormous number of factors to consider for mobile computing which simply aren’t present for desktop or web development, including hardware/software platforms, installation the application, network type, network strength, memory & battery consumption, external interfacing through WAP and HTTP etc. Additionally, testing the application in simulator, using various debugging tools are some further adventures which the tester undergoes during testing cycles.
With a blend of these challenges as the core of the address, we would be presenting our experience from our product development cycles
This presentation give you a brief knowledge of, how statistical process control applied in our daily lives, how it works and some of its important formulas,
1. Beni Asllani University of Tennessee at Chattanooga Statistical Process Control Operations Management - 5 th Edition Chapter 4 Roberta Russell & Bernard W. Taylor, III
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12. Process Control Chart 1 2 3 4 5 6 7 8 9 10 Sample number Upper control limit Process average Lower control limit Out of control
16. p-Chart UCL = p + z p LCL = p - z p z = number of standard deviations from process average p = sample proportion defective; an estimate of process average p = standard deviation of sample proportion p = p (1 - p ) n
17. p-Chart Example 20 samples of 100 pairs of jeans NUMBER OF PROPORTION SAMPLE DEFECTIVES DEFECTIVE 1 6 .06 2 0 .00 3 4 .04 : : : : : : 20 18 .18 200
18. p-Chart Example (cont.) UCL = p + z = 0.10 + 3 p (1 - p ) n 0.10(1 - 0.10) 100 UCL = 0.190 LCL = 0.010 LCL = p - z = 0.10 - 3 p (1 - p ) n 0.10(1 - 0.10) 100 = 200 / 20(100) = 0.10 total defectives total sample observations p =
33. Control Chart Patterns UCL LCL Sample observations consistently above the center line LCL UCL Sample observations consistently below the center line
35. Zones for Pattern Tests UCL LCL Zone A Zone B Zone C Zone C Zone B Zone A Process average 3 sigma = x + A 2 R = 3 sigma = x - A 2 R = 2 sigma = x + ( A 2 R ) = 2 3 2 sigma = x - ( A 2 R ) = 2 3 1 sigma = x + ( A 2 R ) = 1 3 1 sigma = x - ( A 2 R ) = 1 3 x = Sample number | 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | 10 | 11 | 12 | 13
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37. Performing a Pattern Test 1 4.98 B — B 2 5.00 B U C 3 4.95 B D A 4 4.96 B D A 5 4.99 B U C 6 5.01 — U C 7 5.02 A U C 8 5.05 A U B 9 5.08 A U A 10 5.03 A D B SAMPLE x ABOVE/BELOW UP/DOWN ZONE
42. Process Capability (b) Design specifications and natural variation the same; process is capable of meeting specifications most of the time. Design Specifications Process (a) Natural variation exceeds design specifications; process is not capable of meeting specifications all the time. Design Specifications Process
43. Process Capability (cont.) (c) Design specifications greater than natural variation; process is capable of always conforming to specifications. Design Specifications Process (d) Specifications greater than natural variation, but process off center; capable but some output will not meet upper specification. Design Specifications Process
44. Process Capability Measures Process Capability Ratio C p = = tolerance range process range upper specification limit - lower specification limit 6
45. Computing C p Net weight specification = 9.0 oz 0.5 oz Process mean = 8.80 oz Process standard deviation = 0.12 oz C p = = = 1.39 upper specification limit - lower specification limit 6 9.5 - 8.5 6(0.12)
46. Process Capability Measures Process Capability Index C pk = minimum x - lower specification limit 3 = upper specification limit - x 3 = ,
47. Computing C pk Net weight specification = 9.0 oz 0.5 oz Process mean = 8.80 oz Process standard deviation = 0.12 oz C pk = minimum = minimum , = 0.83 x - lower specification limit 3 = upper specification limit - x 3 = , 8.80 - 8.50 3(0.12) 9.50 - 8.80 3(0.12)
48. Factors Appendix: Determining Control Limits for x -bar and R -Charts Return n A 2 D 3 D 4 SAMPLE SIZE FACTOR FOR x -CHART FACTORS FOR R -CHART 2 1.88 0.00 3.27 3 1.02 0.00 2.57 4 0.73 0.00 2.28 5 0.58 0.00 2.11 6 0.48 0.00 2.00 7 0.42 0.08 1.92 8 0.37 0.14 1.86 9 0.44 0.18 1.82 10 0.11 0.22 1.78 11 0.99 0.26 1.74 12 0.77 0.28 1.72 13 0.55 0.31 1.69 14 0.44 0.33 1.67 15 0.22 0.35 1.65 16 0.11 0.36 1.64 17 0.00 0.38 1.62 18 0.99 0.39 1.61 19 0.99 0.40 1.61 20 0.88 0.41 1.59
49. Copyright 2006 John Wiley & Sons, Inc. All rights reserved. Reproduction or translation of this work beyond that permitted in section 117 of the 1976 United States Copyright Act without express permission of the copyright owner is unlawful. Request for further information should be addressed to the Permission Department, John Wiley & Sons, Inc. The purchaser may make back-up copies for his/her own use only and not for distribution or resale. The Publisher assumes no responsibility for errors, omissions, or damages caused by the use of these programs or from the use of the information herein.