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RE: [External] - RE: Followup on code metrics

From
Michael Fanning <>
Date
2021-10-14T14:50:14+00:00
ID
Thread
RE: [External] - RE: Followup on code metrics
Got it, thank you.

 

Yes, profiling data is granular and therefore extremely verbose.

 

I think thereâs an argument that code coverage puts us in the same position, since âline level coverageâ is a thing.

 

MCF

 

From: Paul Anderson <> 

Sent: Tuesday, October 12, 2021 1:14 PM

To: Michael Fanning <>; 

Subject: RE: [External] - RE: Followup on code metrics

 

Michael:

 

Thereâs nothing concrete from the Misra committee yet. Thereâs a meeting in a couple of weeks, but most participants are involved with the coding standards efforts too, which tend to suck up all the oxygen.

 

The metrics I mentioned were all static metrics. Dynamic metrics such as coverage would be useful to consider too, especially as we are thinking of SARIF as extending into the dynamic realm. One caveat is that a lot of dynamic metrics are
 most useful at very fine granularities. E.g, if you are profiling then itâs good to see where time is going for each
line of code, whereas we had been thinking of these metrics as being associated with constructs no smaller than functions.

 

-Paul

 

-- 

Paul Anderson, VP of Engineering, GrammaTech, Inc.

531 Esty St., Ithaca, NY 14850

Tel: +1 607 273-7340 x118;

https://www.grammatech.com

 

From: Michael Fanning <>

Sent: Tuesday, October 12, 2021 2:13 PM

To: Paul Anderson <>;


Subject: [External] - RE: Followup on code metrics

 

CAUTION: External Email

 

This is extremely helpful information, Paul, thanks for sending it.

Weâd also discussed whether MISRA has any current thinking/proposals we could review. Is that the case?

 

Thanks again! In addition to the great stuff below, I think probably we should mention condition/decision metrics for code coverage, likely to be a scenario we at least consider (coverage, I mean).

 

For completeness, we also discussed OMGâs âknowledge discovery metamodelâ (KDM) on the call as related art.

 

Any standard that has âmetaâ in its name, of course, is likely to be a bit too abstract for our applied scenario. We are an interchange format with a focus on crisply defined, point-in-time quality data.

 

KDM is a âcommon  vocabulary of knowledgeâ which can be shared between producers/consumers in an Application Lifecycle Management context. Ambitious! @David, I note that KDM has its own Wikipedia page, which might be helpful comparison
 as you develop ours.

 

Knowledge
 Discovery Metamodel (KDM) (omg.org)

Knowledge
 Discovery Metamodel - Wikipedia

 

MCF

 

From:  <>
On Behalf Of Paul Anderson

Sent: Friday, October 1, 2021 11:20 AM

To: 

Subject: [EXTERNAL] [sarif] Followup on code metrics

 

All:

 

Iâm following up on our meeting yesterday with some material on code metrics.

 

There are a couple of metric âfamiliesâ that are commonly used. The first are simple line counts. Itâs common for tools to have several varieties such as raw lines, non-blank lines, lines with comments, etc. There are also a few metrics
 that count syntactic constructs in various ways, such as nesting depth.

 

Then there is the McCabe family which contains the much misunderstood Cyclomatic Complexity and a few relatives that attempt to compensate for its shortcomings; e.g. Essential Complexity, and Module Design Complexity.

 

The Halstead metrics are an antiquated family that are based on counting tokens in various ways. They donât appear to be widely used any more.

 

There are a bunch of Object-oriented metrics that are often about the relationship between classes: coupling, cohesion, etc.

 

I mentioned metrics used in the embedded industry and how thereâs a need for this to be more standardized. A metrics collection that seems to be popular in automotive is the HIS/KGAS set

https://docplayer.net/6136232-His-source-code-metrics.html. Hereâs a blog I wrote a little while ago that picks on one particular metric used in that set:

https://blogs.grammatech.com/why-npath-is-a-terrible-code-metric.

 

As I said in the meeting, metrics have numeric values, but we should also allow for exceptional results. For example:

Computing the metric leads to a numeric error such as divide by zero

The metric canât be computed because itâs inapplicable for some reason

The value canât be reasonably expressed (e.g., a path count metric can easily yield 30-40 digit decimal values)

The value is infinity (which
kind of infinity probably doesnât matter 
😊)

Thereâs some overlap between these of course. Iâve seen them all in real life.

 

-Paul

 

 

-- 

Paul Anderson, VP of Engineering, GrammaTech, Inc.

531 Esty St., Ithaca, NY 14850

Tel: +1 607 273-7340 x118;

https://www.grammatech.com

 

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