[SystemSafety] Qualifying SW as "proven in use" [Measuring Software]

[Steve Tockey]

Derek,

"So you agree that there is no empirical evidence."

No. I am agreeing that there isn't very much evidence, but I disagree that
there is no evidence at all. I've already cited some, and there's a little
more out there.

I think we both strongly agree that there really needs to be a lot more
evidence.


"cyclomatic complexity is just one of many 'complexity'
metrics that have a high correlation with quantity of code,
so why not just measure lines of code?"

Maybe we are using different applications of cyclomatic complexity to
code? Yes, sure, increasing the total number of lines of code in some code
base will almost certainly increase the total number of decisions in that
code base, and probably by roughly an equal proportion. 10,000 lines of
code with 2000 decisions almost certainly implies close to 4000 decisions
in 20,000 lines of code.

But I'm not looking for a correlation of overall, total code base
cyclomatic complexity to overall defects. I'm looking for the correlation
of cyclomatic complexity within a single function/method to the defect
density within that same single function/method. Figure 4 in the Schroeder
paper shows a strong correlation of function/method-level cyclomatic
complexity and function/method-level defect density. Again, reverse
engineering from the numbers in Figure 4, shows that the defect density
goes up by more than an order of magnitude between cyclomatic complexity
less than/equal to 5 vs greater than/equal to 15 ***within a single
function***.

"once developers know they are being judged by some metric
or other they can easily game the system by actions such as
splitting/merging functions.  If the metric has a causal connection
to the quantity of interest, e.g., faults, then everybody is happy
for developers to what what they will to reduce the metric,
but if the connection is simply a correlation (based on code
written by developers not trying to game the system) then
developers doing whatever it takes to improve the metric value
is at best wasted time."

Yes, I have seen this happen more than once. But as I've been stating all
along, what we need in the end is a balancing of a collection of syntactic
complexity metrics. When functions/methods are split, it always increases
fan out. When functions/methods are merged, it always decreases fan out.
The complexity didn't go away, it just moved to a different place in the
code. So having a limit in only one place easily allows people to squeeze
it into any other place. Having a set of appropriate limits means there's
a lot less chance of it going unnoticed somewhere else.

In any case, police giving speeding tickets to people who drive to fast
obviously doesn't stop people from breaking the speed limit, but that
doesn't mean we should give up issuing speeding tickets. People who break
rules should be punished appropriately and/or have to suffer the
consequences of their actions. Chronic speeders should lose their driving
license. And if an accident is caused by a speeder then that speeder
should have a higher liability than if it were a non-speed related
accident. Just the same, I'm basically arguing for more professionalism in
the software industry. I mean seriously, the programmer who was
responsible for that single C++ class with a single method of 3400 lines
of code with a cyclomatic complexity over 2400 is a total freaking moron
who has no business whatsoever in the software industry.

In fact, I would even advocate a removal of the liability waiver on
software licenses. Let programmers who write code that fails be liable for
the damage that their defects caused. Then, and probably only then, will
we see proper professionalism applied to software development. It's
clearly (to me, at least) not an issue of software not being able to be
built in a solid, reliable way, it's simply that the practitioners are too
used to complete immunity from their sloppiness.

And, we will also always need semantic evaluation of code (which, as I
said earlier, has to be done by humans) because syntax-based metrics alone
will probably always be game-able.


Regards,

-- steve




-----Original Message-----
From: Derek M Jones <derek at knosof.co.uk>
Organization: Knowledge Software, Ltd
Date: Tuesday, June 25, 2013 4:21 PM
To: "systemsafety at techfak.uni-bielefeld.de"
<systemsafety at techfak.uni-bielefeld.de>
Subject: Re: [SystemSafety] Qualifying SW as "proven in use"
[Measuring	Software]

Steve,

...
> "local vs. global" categories, it's just that nobody has yet published
>any
> data identifying which ones should be paid attention to and which ones
> should be ignored.

So you agree that there is no empirical evidence.

Your statement is also true of almost every metrics paper published
todate.

With so many different metrics having been proposed at least one of
them is likely to agree with the empirical data that is yet to be
published.

You cited the paper: “A Practical Guide to Object-Oriented Metrics”
as the source of the cyclomatic complexity vs fault correlation
claim.  Fig 4 looks like it contains the data.  No standard
deviation is given for the values, but this would have to be
very large to ruin what looks like a reasonable correlation.

Such a correlation can often be found, however:

    o cyclomatic complexity is just one of many 'complexity'
metrics that have a high correlation with quantity of code,
so why not just measure lines of code?

    o once developers know they are being judged by some metric
or other they can easily game the system by actions such as
splitting/merging functions.  If the metric has a causal connection
to the quantity of interest, e.g., faults, then everybody is happy
for developers to what what they will to reduce the metric,
but if the connection is simply a correlation (based on code
written by developers not trying to game the system) then
developers doing whatever it takes to improve the metric value
is at best wasted time.

>
> -----Original Message-----
> From: Todd Carpenter <todd.carpenter at adventiumlabs.com>
> Date: Monday, June 24, 2013 7:20 PM
> To: "systemsafety at techfak.uni-bielefeld.de"
> <systemsafety at techfak.uni-bielefeld.de>
> Subject: Re: [SystemSafety] Qualifying SW as "proven in use"
> [Measuring	Software]
>
> ST> For example, the code quality measure "Cyclomatic Complexity"
> (reference:
> ST> Tom McCabe, ³A Complexity Measure², IEEE Transactions on Software
> ST> Engineering, December, 1976) was validated many years ago by simply
>
> DMJ> I am not aware of any study that validates this metric to a
>reasonable
> DMJ> standard.  There are a few studies that have used found a medium
> DMJ> correlation in a small number of data points.
>
> Les Hatton had an interesting presentation in '08, "The role of
>empiricism
> in improving the
> reliability of future software" that shows there is a strong correlation
> between
> source-lines-of-code and cyclomatic complexity, and that defects follow a
> power law distribution:
>
> 
>http://www.leshatton.org/wp-content/uploads/2012/01/TAIC2008-29-08-2008.pd
>f
>
> Just another voice, which probably just adds evidence to the argument
>that
> we haven't yet found a
> trivial metric to predict bugs...
>
> -TC
>
> On 6/24/2013 6:38 PM, Derek M Jones wrote:
>> All,
>>
>>> Actually, getting the evidence isn't that tricky, it's just a lot of
>>> work.
>>
>> This is true of most things (+ getting the money to do the work).
>>
>>> Essentially all one needs to do is to run a correlation analysis
>>> (correlation coefficient) between the proposed quality measure on the
>>> one
>>> hand, and defect tracking data on the other hand.
>>
>> There is plenty of dirty data out there that needs to be cleaned up
>> before it can be used:
>>
>> 
>>http://shape-of-code.coding-guidelines.com/2013/06/02/data-cleaning-the-n
>>e
>> xt-step-in-empirical-software-engineering/
>>
>>
>>> For example, the code quality measure "Cyclomatic Complexity"
>>> (reference:
>>> Tom McCabe, ³A Complexity Measure², IEEE Transactions on Software
>>> Engineering, December, 1976) was validated many years ago by simply
>>
>> I am not aware of any study that validates this metric to a reasonable
>> standard.  There are a few studies that have used found a medium
>> correlation in a small number of data points.
>>
>> I have some data whose writeup is not yet available in a good enough
>> draft form to post to my blog.  I only plan to write about this
>> metric because it is widely cited and is long overdue for relegation
>> to the history of good ideas that did not stand the scrutiny of
>> empirical evidence.
>>
>>> finding a strong positive correlation between the cyclomatic complexity
>>> of
>>> functions and the number of defects that were logged against those same
>>
>> Correlation is not causation.
>>
>> Cyclomatic complexity correlates well with lines of code, which
>> in turn correlates well with number of faults.
>>
>>> functions (I.e., code in that function needed to be changed in order to
>>> repair that defect).
>>
>> Changing the function may increase the number of faults.  Creating two
>> functions where there was previously one will reduce an existing peak
>> in the distribution of values, but will it result in less faults
>> overall?
>>
>> All this stuff with looking for outlier metric values is pure hand
>> waving.  Where is the evidence that the reworked code is better not
>> worse?
>>
>>> According to one study of 18 production applications, code in functions
>>> with cyclomatic complexity <=5 was about 45% of the total code base but
>>> this code was responsible for only 12% of the defects logged against
>>>the
>>> total code base. On the other hand, code in functions with cyclomatic
>>> complexity of >=15 was only 11% of the code base but this same code was
>>> responsible for 43% of the total defects. On a per-line-of-code basis,
>>> functions with cyclomatic complexity >=15 have more than an order of
>>> magnitude increase in defect density over functions measuring <=5.
>>>
>>> What I find interesting, personally, is that complexity metrics for
>>> object-oriented software have been around for about 20 years and yet
>>> nobody (to my knowledge) has done any correlation analysis at all (or,
>>> at
>>> a minimum they have not published their results).
>>>
>>> The other thing to remember is that such measures consider only the
>>> "syntax" (structure) of the code. I consider this to be *necessary* for
>>> code quality, but far from *sufficient*. One also needs to consider the
>>> "semantics" (meaning) of that same code. For example, to what extent is
>>> the code based on reasonable abstractions? To what extent does the code
>>> exhibit good encapsulation? What are the cohesion and coupling of the
>>> code? Has the code used "design-to-invariants / design-forchange"? One
>>> can
>>> have code that's perfectly structured in a syntactic sense and yet it's
>>> garbage from the semantic perspective. Unfortunately, there isn't a way
>>> (that I'm aware of, anyway) to do the necessary semantic analysis in an
>>> automated fashion. Some other competent software professionals need to
>>> look at the code and assess it from the semantic perspective.
>>>
>>> So while I applaud efforts like SQALE and others like it, one needs to
>>> be
>>> careful that it's only a part of the whole story. More work--a lot
>>> more--needs to be done before someone can reasonably say that some
>>> particular code is "high quality".
>>>
>>>
>>> Regards,
>>>
>>> -- steve
>>>
>>>
>>>
>>>
>>>
>>> -----Original Message-----
>>> From: Peter Bishop <pgb at adelard.com>
>>> Date: Friday, June 21, 2013 6:04 AM
>>> To: "systemsafety at techfak.uni-bielefeld.de"
>>> <systemsafety at techfak.uni-bielefeld.de>
>>> Subject: Re: [SystemSafety] Qualifying SW as "proven
>>> in    use"    [Measuring    Software]
>>>
>>> I agree with Derek
>>>
>>> Code quality is only a means to an end
>>> We need evidence to to show  the means actually helps to achieve the
>>> ends.
>>>
>>> Getting this evidence is pretty tricky, as parallel developments for
>>>the
>>> same project won't happen.
>>> But you might be able to infer something on average over multiple
>>> projects.
>>>
>>> Derek M Jones wrote:
>>>> Thierry,
>>>>
>>>>> To answer your questions:
>>>>> 1°) Yes, there is some objective evidence that there is a correlation
>>>>> between a low SQALE index and quality code.
>>>>
>>>> How is the quality of code measured?
>>>>
>>>> Below you say that SQALE DEFINES what is "good quality" code.
>>>> In this case it is to be expected that a strong correlation will exist
>>>> between a low SQALE index and its own definition of quality.
>>>>
>>>>> For example ITRIS has conducted a study where the "good quality" code
>>>>> is statistically linked to a lower SQALE index, for industrial
>>>>> software actually used in operations.
>>>>
>>>> Again how is quality measured?
>>>>
>>>>> No, there is not enough evidence, we wish there would be more people
>>>>> working on getting the evidence.
>>>>
>>>> Is there any evidence apart from SQALE correlating with its own
>>>> measures?
>>>>
>>>> This is a general problem, lots of researchers create their own
>>>> definition of quality and don't show a causal connection to external
>>>> attributes such as faults or subsequent costs.
>>>>
>>>> Without running parallel development efforts that
>>>> follow/don't follow the guidelines it is difficult to see how
>>>> reliable data can be obtained.
>>>>
>>>
>>
>
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-- 
Derek M. Jones                  tel: +44 (0) 1252 520 667
Knowledge Software Ltd          blog:shape-of-code.coding-guidelines.com
Software analysis               http://www.knosof.co.uk
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