The Risks Digest

The RISKS Digest

Forum on Risks to the Public in Computers and Related Systems

ACM Committee on Computers and Public Policy, Peter G. Neumann, moderator

Volume 3 Issue 75

Saturday, 4 October 1986

Contents

o re: Estell on Viking (RISKS-3.73)
David Parnas
Dave Benson
o Software becomes obsolete, but does not wear out
Dave Benson
o The fallacy of independence
Dave Benson
o Re: Paths in Testing (RISKS-3:72)
Chuck Youman
Mark Day
o Mathematical checking of programs (quoting Tony Hoare)
Henry Spencer
o Info on RISKS (comp.risks)

re: Estell on Viking (RISKS-3.73)

<parnas%qucis.BITNET@WISCVM.WISC.EDU>
Fri, 3 Oct 86 15:33:03 EDT
Robert Estell's contribution perpetuates two serious myths about the
discussion on Viking and other software.

(1) That any of the discussants is expecting perfection.

Perfectionists do not use the net.  In fact, the only computer
scientist I know who could be called a perfectionist does not use
computers.  Most of us know that computer systems, like other human
artifacts, will never be perfect.  Our concern is with establishing
confidence that the system is free of unacceptable or catastrophic
errors.  This we can do with many other engineering products.  Only
software products regularly carry disclaimers instead of limited
warranties.  That is not because they are the only products that are
imperfect.  It is because we have so little confidence that they are
free of catastrophic flaws.

(2) That size is a good measure of the difficulty of a problem.

There are big programs solving dull but easy problems.  Small
programs occasionally solve very hard problems.  The size
and irregularity of the problem state space, and how well
we know that state space determine, in large part the
complexity of the problem.  The size of the program is often
determined by the simplicity of the programmer.

In spite of Nancy's help, we don't know much from this forum
about what the Viking software actually did.  It seems clear that
most of the software could have been, and was, used before the
flight.  Whether the descent software could have been used
depends on what it did.  At 100 lines one would expect that
it did not do much.

        We all know that programs can work acceptably well.  We
use them and accept what they do.  We also know that failures
are not catastrophic and that these programs failed many times
before they became reliable enough to be useful.  If we had
been in a situation in which those failures were unacceptable
we would have found another way to solve the real problem.


Viking Lander, once again.

Dave Benson <benson%wsu.csnet@CSNET-RELAY.ARPA>
Fri, 3 Oct 86 17:57:52 pdt
I repeat some quotations from Bonnie A. Claussen's paper:
    The unprecented success of the Viking mission was due in part to
        the ability of the flight software to operate in an AUTONOMOUS
        and ERROR FREE manner. ...  Upon separation from the Orbiter the
        Viking Lander, under AUTONOMOUS software control, deorbits, enters
        the Martian atmosphere, and performs a soft landing on the surface.
        [CAPS added for emphasis.]
Since the up-link was only capable of 4 bits/sec and the light-speed signal
requires about 14 minutes for a round-trip to Mars, manifestly the software
carried out these control functions without human assistance.

 >I worry when anecdotal evidence about one software project is used as
 >"proof" about what will happen with general software projects.
 >     Nancy Leveson

I concur.  But the Viking Lander experience does give a compelling example
that autonomous software can be made to work under certain circumstances.
Thus a claim that <

Software becomes obsolete, but does not wear out

Dave Benson <benson%wsu.csnet@CSNET-RELAY.ARPA>
Fri, 3 Oct 86 18:33:12 pdt
ob'so.lete.  Abbr. obs.  Of a type or fashion no longer current; out of
date; as, an obsolete machine.

ob'so.les''cent.  Going out of use; becoming obsolete.

wear v.t. ... 6. To use up by wearing (sense 1); as, to wear out a dress;
hence, to consume or cause to deteriorate by use, esp. personal use;
as, the lugage is worn. 7. To impair, waste, or diminish, by continual
attrition, scraping, or the like; as, the rocks are worn by water;
hence, to exhaust or lessen the strength of; fatigue; weary; use up;
as, to be worn with desease. 8. To cause or make by friction or wasting;
as, to wear a channel or hole.
wear v.i. ... 4. To be wasted, consumed, or diminished, by use; to
suffer injury, loss, or extinction, by use or time;-- often with
<out>, <off>, <on>, etc.; as the day has worn on.

Software, like any artifact, becomes obsolete over time.  The changing
informational environment about the software drives it to obsolesence.
It becomes unmaintainable, not from wear, but because the expertise
required has become dissipated.  Recall that nobody knows how to
make a Stradivarius violin anymore, either.

I agree with the causes of software obsolescence, but strongly recommend that
we use the customary meanings of words in the dictionary so that
we understand one-another and so that non-software-types can somewhat
understand us as well.  Thus: software may become obsolete from many
causes, some of which are understood.  But software ordinarily does not
wear out and never, never rots.  [...]

There is a reason for precise technical terms.  In other disciplines words
are coined, just to avoid the overloading and potential resultant
misunderstanding.  I recommend that we attempt this, but suggest looking
in the dictionary first.


The fallacy of independence

Dave Benson <benson%wsu.csnet@CSNET-RELAY.ARPA>
Sat, 4 Oct 86 22:21:39 pdt
A RISKS contribution suggests that since we can engineer good 100,000
statement software, the means to make good 1,000,000 statement software
is to produce 10 smaller packages and hook these 10 together.
    Such a claim makes the assumption that the informational
environment of the total software is such that the total software system
can be decomposed into 10 nearly independent parts, which communicate with
one another along well-understood interfaces.
    The key is the claim that the interfaces are well-understood.
Software is an example of an extremely complex artifact, a class of artifacts
which we understand poorly--for otherwise we wouldn't call them complex.
In smaller programs we repeatedly see that the interfaces are not
well-understood until the program is available for experimentation.  Even
then, our everyday experiences with software demonstrate again and again
that what we had assumed about the program behavior does not match the
reality of actual experience.  Thus we discover that the interfaces are
not well-understood.
    Example:  Virtual storage managers in operating systems provide
a superficially simple interface to the hardware  and the rest of the
operating system.  The interface to the user program is the essense of
simplicity--complete transparency.  Now the earliest virtual storage managers
were the essense of simplicity.  So nothing could go wrong, right?  Wrong.
The interaction of user virtual storage requests, the operating system
scheduler, and the virtual storage manager led to thrashing--slowing
performance to a crawl, at best.  Upon OBSERVING this phenomenon, theories
were developed and better, more complex, algorithms were installed.  But
this phenomenon was not predicted a priori.
    The essential point is that even the cleanest design may fail in
actual engineering practice until it is tried in the fully operational
environment for which it was intended.  In software engineering we only
have confidence in a design if it is similar to a previous, successful
design.  But that is just like any other engineering practice.  The
intuition and insight of a Roebling (Brooklyn Bridge, 1883) is rare
in any engineering field.  Most of us are good copiers, making local
improvements to a  design already shown to be successful.
    The corollary is that it is wrong to assume the near-independence
of components until this near-independence has been abundantly shown in
practice and theory.
    Example:  The division of the frontend of a compiler into lexical
and syntactic parsing components which interact in well-understood ways
has an excellent underlying theory and works well in practice.  Thus it is
common to teach this practice and theory, since post-facto it is a
workable engineering design of nearly-independent components.
    By all means color me realist.  Also color me existentialist.
What works is that which works, not what we might hope or dream or
imagine works.  The near-independence of software components is an
aspect which is proved in practice to be a near-independence of
components.  As there is no "software decomposition theorem" which provides
a general framework for that elusive quality, near-independence, we
cannot assume that 10 good parts will actually form a cohesive, practical
reliable whole.  In each separate design, then, the value of the whole
system can only be demonstrated by the use of the whole system.
    Thus I claim it is a fallacy to assert independence, or even
near-independence, for any division of the work within a system until
this has been conclusively demonstrated.  I further claim, with ample
historical precedent, that the reliability of a system is only poorly
correlated with the reliability of its parts.  Without a specific design
one can say nothing in general.


Re: Paths in Testing (RISKS-3:72)

Chuck Youman <m14817@mitre.ARPA>
Fri, 03 Oct 86 16:46:13 -0500
A comment on basis paths.

There was a paper on "Evaluating Software Testing Strategies" presented
by Richard Selby at the 9th Annual NASA Goddard Software Engineering Workshop
that compared the strategies of code reading, functional testing, and 
structural testing in three aspects of software testing.  One of the
conclusions I recall is that structural testing was not as effective
as the other two methods at detecting omission faults and control faults.

The conference proceedings are report SEL-84-004 and can be obtained from Frank
E. McGarry, Code 552, NASA/GSFC, Greenbelt, MD 20771.

Charles Youman (youman@mitre.arpa)


Re: Paths in Testing (RISKS-3:72)

Mark S. Day <MDAY@XX.LCS.MIT.EDU>
Sat 4 Oct 86 14:03:24-EDT
It's reasonably well known that structural (path-based) testing is
poor at detecting faults of omission.  Correspondingly, functional
testing is poor at detecting faults on "extra" paths that are present
in the implementation (for optimization of common cases, for example)
but are not "visible" in a functional spec of the module.  The conclusion
to draw is that proper testing requires a combination of "external" testing
(treating the module as a black box and examining its input/output structure)
and "internal" testing (examining the contents of the module).  

--Mark


Mathematical checking of programs (quoting Tony Hoare)

<decvax!utzoo!henry@ucbvax.Berkeley.EDU>
Sat, 4 Oct 86 21:12:13 edt
I agree with much of the quoted discussion from Hoare, including the
obvious desirability of rather heavier use of mathematical analysis
of safety-critical programs.  I do have one quibble with some of his
comments, though:

>   ... never even heard of the possibility that you can establish
>   the total correctness of computer programs by the normal mathematical
>   techniques of modelling, calculation and proof. ...
>   A mathematical proof is, technically, a completely reliable method of
>   ensuring the correctness of programs, but this method could never be
>   effective in practice unless it is accompanied by the appropriate attitudes
>   and managerial techniques. ...

I think talk of "total correctness" and "complete reliability" shows excess
enthusiasm rather than realistic appreciation of the situation.  Considering
the number of errors that have been found in the small programs used as
published examples of "proven correctness", wariness is indicated.  Another
cautionary tale is the current debate about the validity of the Rourke/Rego
proof of the Poincare conjecture.  As I understand it -- it's not an area
I know much about -- the proof is long, complex, and sketchy, and nobody
is sure whether or not to believe it.  And this is a case where the specs
for the problem are very simple and obviously "right".  Mathematical proof
has its own feet of clay.  If one defines "effective in practice" to imply
complete confidence in the results, then I would not fly on an airliner
whose flight-control software was written by a team making such claims.
Complete confidence in provably fallible techniques worsens risks rather
than reducing them.

(The apocryphal comment of the aeronautical structure engineer looking
at his competitor's aircraft:  "Fly in it?  I wouldn't even walk under it!")

On the other hand, if one defines "effective in practice" to mean "useful
in finding errors, and valuable in increasing one's confidence of their
absence", I wholeheartedly agree.  One should not throw out the baby with
the bathwater.  If one sets aside the arrogant propaganda of the proof-
of-correctness faction, there is much of value there.  To borrow from the
theme of a PhD thesis here some years ago, proving programs INcorrect is
much easier than proving them correct, and is very useful even if it isn't
the Nirvana of "total correctness".  The mental discipline imposed on program
creation (defining loop invariants, etc.) is also important.

                Henry Spencer @ U of Toronto Zoology
                {allegra,ihnp4,decvax,pyramid}!utzoo!henry

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