Good Metrics for TDD

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2 likes•7,880 views

Often companies who are new to TDD ask us, what should we measure to know if we are headed in the right direction with regards to TDD. Here are some things you might consider. My take is, less is more. Don't measure 100 things, focus on a few at a time and move on.

Technology Education

Good Metrics for a
TDD Program
“Less is More”

Naresh Jain
naresh@industriallogic.com

Copyright © 2011, Industrial Logic, Inc. All Rights Reserved.
1

C3 - TreeMap

• Coverage
• Complexity
• Churn

Copyright © 2011, Industrial Logic, Inc. All Rights Reserved.
2

Test vs. Production Code
Src LOC Test LOC
60,000

45,000

30,000

15,000

0
15 Feb 2 Mar 17 Mar 1 Apr 18 Apr 1 May 16 May 31 May 15 Jun 30 Jun

Usually Test Driven code has more Test Code than Production Code
Copyright © 2011, Industrial Logic, Inc. All Rights Reserved.
3

Test Run Trend with
every CI Build
# of Failing Test # of Passing

300

225

150

75

0
B1 B2 B3 B4 B5 B6 B7 B8
Each Build
Copyright © 2011, Industrial Logic, Inc. All Rights Reserved.
4

Test Balance
• # of commits that include Tests over time (weekly)
Commits With Tests Commits Without Tests

150.0

112.5

75.0

37.5

0
W1 W2 W3 W4 W5 W6 W7
Copyright © 2011, Industrial Logic, Inc. All Rights Reserved.
5

Test Churn
• # of tests added/removed over time (weekly)
Tests Added Tests Removed

60

45

30

15

0
W1 W2 W3 W4 W5 W6
Copyright © 2011, Industrial Logic, Inc. All Rights Reserved.
6

Satisfaction Rating from
Developers and Testers
Devs Testers

70.0

52.5

%
35.0

17.5

0
June 6th June 13th June 20th June 27th July 4th July 11th July 18th
Weekly
Copyright © 2011, Industrial Logic, Inc. All Rights Reserved.
7

Thank You!
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8

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The presentation explores the development and application of artificial intelligence (AI) from its inception to its current status in the modern world. The term "artificial intelligence" was first coined by John McCarthy in 1956 to describe efforts to develop computer programs capable of performing tasks that typically require human intelligence. This concept was first introduced at a conference held at Dartmouth College, where programs demonstrated capabilities such as playing chess, proving theorems, and interpreting texts. In the early stages, Alan Turing contributed to the field by defining intelligence as the ability of a being to respond to certain questions intelligently, proposing what is now known as the Turing Test to evaluate the presence of intelligent behavior in machines. As the decades progressed, AI evolved significantly. The 1980s focused on machine learning, teaching computers to learn from data, leading to the development of models that could improve their performance based on their experiences. The 1990s and 2000s saw further advances in algorithms and computational power, which allowed for more sophisticated data analysis techniques, including data mining. By the 2010s, the proliferation of big data and the refinement of deep learning techniques enabled AI to become mainstream. Notable milestones included the success of Google's AlphaGo and advancements in autonomous vehicles by companies like Tesla and Waymo. A major theme of the presentation is the application of generative AI, which has been used for tasks such as natural language text generation, translation, and question answering. Generative AI uses large datasets to train models that can then produce new, coherent pieces of text or other media. The presentation also discusses the ethical implications and the need for regulation in AI, highlighting issues such as privacy, bias, and the potential for misuse. These concerns have prompted calls for comprehensive regulations to ensure the safe and equitable use of AI technologies. Artificial intelligence has also played a significant role in healthcare, particularly highlighted during the COVID-19 pandemic, where it was used in drug discovery, vaccine development, and analyzing the spread of the virus. The capabilities of AI in healthcare are vast, ranging from medical diagnostics to personalized medicine, demonstrating the technology's potential to revolutionize fields beyond just technical or consumer applications. In conclusion, AI continues to be a rapidly evolving field with significant implications for various aspects of society. The development from theoretical concepts to real-world applications illustrates both the potential benefits and the challenges that come with integrating advanced technologies into everyday life. The ongoing discussion about AI ethics and regulation underscores the importance of managing these technologies responsibly to maximize their their benefits while minimizing potential harms.

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Building Digital Trust in a Digital Economy Veronica Tan, Director - Cyber Security Agency of Singapore Apidays Singapore 2024: Connecting Customers, Business and Technology (April 17 & 18, 2024) ------ Check out our conferences at https://www.apidays.global/ Do you want to sponsor or talk at one of our conferences? https://apidays.typeform.com/to/ILJeAaV8 Learn more on APIscene, the global media made by the community for the community: https://www.apiscene.io Explore the API ecosystem with the API Landscape: https://apilandscape.apiscene.io/

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The Raspberry Pi 5 was announced on October 2023. This new version of the popular embedded device comes with a new iteration of Broadcom’s VideoCore GPU platform, and was released with a fully open source driver stack, developed by Igalia. The presentation will discuss some of the major changes required to support this new Video Core iteration, the challenges we faced in the process and the solutions we provided in order to deliver conformant OpenGL ES and Vulkan drivers. The talk will also cover the next steps for the open source Raspberry Pi 5 graphics stack. (c) Embedded Open Source Summit 2024 April 16-18, 2024 Seattle, Washington (US) https://events.linuxfoundation.org/embedded-open-source-summit/ https://eoss24.sched.com/event/1aBEx

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As privacy and data protection regulations evolve rapidly, organizations operating in multiple jurisdictions face mounting challenges to ensure compliance and safeguard customer data. With state-specific privacy laws coming up in multiple states this year, it is essential to understand what their unique data protection regulations will require clearly. How will data privacy evolve in the US in 2024? How to stay compliant? Our panellists will guide you through the intricacies of these states' specific data privacy laws, clarifying complex legal frameworks and compliance requirements. This webinar will review: - The essential aspects of each state's privacy landscape and the latest updates - Common compliance challenges faced by organizations operating in multiple states and best practices to achieve regulatory adherence - Valuable insights into potential changes to existing regulations and prepare your organization for the evolving landscape

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Enterprise Knowledge’s Urmi Majumder, Principal Data Architecture Consultant, and Fernando Aguilar Islas, Senior Data Science Consultant, presented "Driving Behavioral Change for Information Management through Data-Driven Green Strategy" on March 27, 2024 at Enterprise Data World (EDW) in Orlando, Florida. In this presentation, Urmi and Fernando discussed a case study describing how the information management division in a large supply chain organization drove user behavior change through awareness of the carbon footprint of their duplicated and near-duplicated content, identified via advanced data analytics. Check out their presentation to gain valuable perspectives on utilizing data-driven strategies to influence positive behavioral shifts and support sustainability initiatives within your organization. In this session, participants gained answers to the following questions: - What is a Green Information Management (IM) Strategy, and why should you have one? - How can Artificial Intelligence (AI) and Machine Learning (ML) support your Green IM Strategy through content deduplication? - How can an organization use insights into their data to influence employee behavior for IM? - How can you reap additional benefits from content reduction that go beyond Green IM?

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Good Metrics for TDD

3. Test vs. Production Code Src LOC Test LOC 60,000 45,000 30,000 15,000 0 15 Feb 2 Mar 17 Mar 1 Apr 18 Apr 1 May 16 May 31 May 15 Jun 30 Jun Usually Test Driven code has more Test Code than Production Code Copyright © 2011, Industrial Logic, Inc. All Rights Reserved. 3

5. Test Balance • # of commits that include Tests over time (weekly) Commits With Tests Commits Without Tests 150.0 112.5 75.0 37.5 0 W1 W2 W3 W4 W5 W6 W7 Copyright © 2011, Industrial Logic, Inc. All Rights Reserved. 5

7. Satisfaction Rating from Developers and Testers Devs Testers 70.0 52.5 % 35.0 17.5 0 June 6th June 13th June 20th June 27th July 4th July 11th July 18th Weekly Copyright © 2011, Industrial Logic, Inc. All Rights Reserved. 7

Good Metrics for TDD

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