Is there a way to get LOC (lines of code) per EPIC in JIRA

[Ariel Man]

I want to examine new methodologies to estimate our efforts on Epics/Features.

COCOMO model talking about estimation by software-complexity, and LOC is part of it:

https://en.wikipedia.org/wiki/COCOMO

https://www.youtube.com/watch?v=r2qkxbCSsvE

In our daily job, each commit must have JIRA ID, so after the push there's sync between the bitbucket PR to Jira EPIC/Story.

As very-first step, I need to see if there is correlation for actual time took to close Epic and the LOC done.

So I was wonder if there's a way that for a given Jira Epic, find all child issues - commits - LOC.

At the end, I need number of lines of code written that are associated with a specific Jira epic/story.

I'm aware there are several BitBucket Plug-Ins which are specific for BitBucket (not in Jira context), means that I'm able to count LOC for a developer/branch/repository/time period, but NOT for a context such as Epic/Story.

[Kit Friend · Accepted solution]

What's the "So what?" you're wanting to derive from this? Lines of code isn't really associate with either value or size (you can write 1000 lines that are useless and quick to churn out, and 10 lines that are really valuable but take ages to whittle down). 

It's worth exploring https://www.scopemaster.com/ and Cosmic Function Points if this sort of topic is interesting.

Normally folks are more interested in "And what did we get?" for each piece of work though - for that you need a discussion around value and outcomes using something like www.gtmhub.com 

[Ariel Man]

Tnx

I've looked on scopemaster, and seems the plugin is Jira oriented (It can do the work at Jira aspects).

The thing we need is BitBucket + Jira solution (get all items Based on BitBucket branches).

 In addition, I did not find a server version, only cloud.

[Kit Friend]

Sure - for combined metrics you probably want something like www.plandek.com or jellyfish.io 

BUT

The more important query here is what you're hoping to get from this data. Measuring lines of code doesn't really tell you much other than how many lines of code have been written - most teams are more interested in questions like:

- Was that code of good quality?

- Did the code give us the benefits we expected?

- Do certain things always take way longer than expected to make?

- What is delaying our time to market/lead time?