#codecoverage

In today's fast-paced development world, balancing rapid releases with high-quality software is no small feat. Enter code coverage—the secret weapon that helps developers ensure their tests cover all bases. But it's not just about percentages. It's about smarter, more efficient testing that gives you the visibility you need to improve your software.

🔍 Why Coverage Matters It's not just about hitting numbers—it's about understanding where your code needs attention. By combining different coverage types like statement, branch, and function coverage, you get a full picture of your testing landscape. This allows for proactive improvements before issues snowball into bigger problems.

💡 Automate Your Coverage In the world of CI/CD, automation is key. Set up automated coverage tools that integrate seamlessly into your workflow to provide real-time feedback. This keeps coverage visible across teams, ensuring every change is covered. The sooner you catch gaps, the better.

📊 Agile & DevOps: A New Era for Coverage In the age of Agile and DevOps, coverage isn't a static number. It's a dynamic tool that evolves with your sprints and releases. Teams need coverage tools that can adapt to rapid changes without losing accuracy.

🌍 Scaling Across Enterprises For larger teams and codebases, scaling coverage is crucial. By establishing clear standards and centralized reporting, large organizations can keep their coverage consistent and effective across multiple teams and tech stacks.

🏆 Culture & Quality Remember—coverage isn't just about compliance. It's a team effort. When coverage becomes a shared goal, it drives collaboration and continuous improvement. A culture that values quality is key to long-term success.

Halo-halo... Ina lagi belajar nyambi ngeblog juga biar ga lupa nih hehe :). Jadi kemungkinan akan ada update ditiap tulisannya karena proses belajar dan nulis yang berbarengan. Semoga tulisannya berfaedah ya. 

13 Maret 2017

Mau bahas code coverage, btw sebetulnya ini tugas minggu lalu tapi baru dikerjain. Ina kurang sprint nih :” hiks semoga dapat segera memperbaiki management waktunya ya :”)

Mulailah saya googling sana sini akhirnya dapat referensi disini. 

code coverage is a measure used to describe the degree to which the source code of a program is tested by a particular test suite.

untuk mengukurnya dapat menggunakan rumus sebagai berikut :

Code Coverage = (Number of lines of code exercised)/(Total Number of lines of code) * 100%

Jadi singkat cerita, semakin tinggi nilai code coveragenya maka kemungkinan bugsnya semakin kecil. Tapi jangan lupa juga code coverage yang rendah bukan berarti terdapat banyak bug melainkan bisa saja design testing kita yang kurang bagus. 

Code coverage is a measure of how much of your code has been  tested. Code coverage tools run a set of metrics in order to determine if your code has been completely tested, reducing the chance of  unwanted bugs.

You have to take into account that even if your code has 100% code coverage, that doesn’t guarantee all your tests are correct, there are some logical bugs you might miss, but as with…

Problem:

Messen der Codeabdeckung eines Python-Skripts

Lösung:

Verwendung des Programms "coverage.py"

Installation: sudo pip install coverage

Coverage ermitteln: coverage run pythonscript.py

Coverage anzeigen: coverage report -m