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Ben Franklin and Rosicrucian Dragons - Trepanning
Ben Franklin will always appear to be a great man and he was that indeed. But he was not just the founder of America or The Enlightenment Experiment. He was one of the founders of the New World Order along with Pierre Dupont de Nemours who he...
Cosmic Absurdities
The BBC today reported that archaeologists in China have found the worlds oldest observatory. The semicircular platform (130 feet in diameter) surrounded by 13 pillars was unearthed near the city of Linfen in the Shanxi province. The remains are...
Experiments in the Science of Mind
In any science experiment, you take a situation, change
something about it, and measure the effect of your action on the
situation. When you're a kid, you might start with a still cup
of vinegar, add baking soda, and be delighted when the...
How the Meter Came To Be
One can know where one is in the world by the systems of
measurement that specific place uses. There is the English
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What does statistics have to do with drug contaminated bank notes?
Does the topic pique your curiosity? Are you wondering what
indeed does statistics have to do with drug contaminated notes?
Let's suffice it to say: Everything. Yes, though the connection
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Declarative Programming - Strategies for Solving Software Problems
Many software and hardware producers take pride in the
exponential pace of technology change, but for users and
consumers of their products and services the rapid technological
obsolescence often means increased costs, frustrations, and
unfulfilled promises. Corporate America expects to make capital
investments in goods and facilities that should last five, ten,
even twenty years, but only an eighteen-month lifetime for
computer software and hardware investment is not uncommon.
Lowering the costs to develop new software solutions or
extending the lifetime of software applications are two
complementary approaches to addressing technological change.
These goals can often be met by taking a declarative strategy
when designing software systems independent of the programming
methodology employed.
Issues with Imperative Programming
Most programming projects today use the imperative style of
programming. Developers write sequences of operations in a
language, such as C++, Java, Visual Basic, etc., that implement
an algorithm, or recipe, for performing tasks. The algorithm for
the task mixes logical, or relational, statements about the task
to be solved and control statements about how to calculate the
solution. The logical statements describe "what-to" calculate
while the control statements describe "how-to" calculate.
Debugging the algorithm consists of verifying the accuracy of
the logical statements and fixing the control statements, if
necessary.
There are many problems with the imperative approach. The
sequence of operations critically determines the correctness of
the algorithm. Unexpected execution sequences through an
algorithm caused by user input actions or real-time events in a
multitasking environment may result in subtle or catastrophic
algorithm failure. Writing the control logic is the programmer's
responsibility and, therefore, subject to implementation errors.
Understanding a program's algorithm is often difficult for other
developers without extensive metadata, or comments, on the code
and empirical tracing of the program's execution with sample
data. Verifying program correctness consumes a significant
portion of the development effort, but also usually fails to
discover a significant number of defects.
To address the problems associated with imperative programming,
the computer industry has developed and advocated many
approaches. Structured programming and campaigns against "go-to"
statements address some of the problems discovered with ad hoc
control structures and statements. Modularization initiatives
stress decomposition techniques on the premise that humans can
better comprehend, reason about, and maintain smaller pieces of
code. Object-oriented programming advocates program
constructions using reusable components, libraries, and
frameworks. The pattern programming school stresses analogies to
other fields, such as architecture, by constructing programs
using well-designed and crafted solutions, or patterns, that
recur in many programming contexts.
What is Declarative Programming?
Declarative programming separates the logic, or what, of an
algorithm from the control, or how, of an algorithm. The
programmer still specifies the logic or equations specifying the
problem's relations, but the programming system is responsible
for control, or how the logic is evaluated. The most familiar
examples are spreadsheets and query languages for relational
databases. The user, or programmer, specifies a mathematical
relation as a query, say in SQL, for what to retrieve, while the
database engine determines how to execute the query against the
database.
There are many advantages to declarative programming over the
imperative style. In declarative languages, programmers do not
specify sequences of operations, but only definitions or
equations specifying relations. Unlike imperative programming,
the logic relations in declarative programming are execution
order independent, free of side effects of evaluation, and
semantically clear to visual inspection.
The declarative family of programming languages has a long
history in the academic computer science community and
specialized areas of commercial application, such as compiler
construction, expert systems, and databases. Declarative
languages have two main family trees. The logic declarative
languages, such as Prolog, are based on first-order predicate
calculus, which generalizes the notions of Aristotelian true or
false values to statements, or predicates, involving relations
among any entities. The other family branch consists of
functional declarative languages, such as Miranda, Haskell, and
SML. The functional declarative languages are based on the
l-calculus developed by the mathematician, Alonzo Church in the
1930's. l-calculus formalizes the notions of recursive
application of pure functions to computable problems. Although
not widely known as such, the latest programming fashion, XSLT,
an extensible stylesheet language for transforming XML, is also
a functional declarative language.
Despite the theoretical advantages of declarative programming
languages, they do not have widespread use in commercial
programming practice despite an attempt in the 1980's by Borland
to mass-market a PC version of Prolog along with the highly
popular Turbo Pascal. There are many factors contributing to the
infrequent use of declarative languages. A large contributor is
the paucity of collegiate training in declarative languages, but
awkward syntaxes of some languages, inefficient compilers and
run-times, and restricted domains of applicability of
generalized "how-to" mechanisms are all contributors.
Using Declarative Strategies in Commercial Software
While declarative programming languages have not
received
wide-spread commercial usage, the strategy of separating logic,
or what, from control, or how, in an algorithm is a powerful,
generalized technique for increasing ease of use and extending
the longevity of software. Declarative techniques are
particularly powerful in user interfaces and application
programming interfaces (APIs) that have a rich, complex set of
inputs over a relatively small field of execution behaviors.
Two examples of commercial software that illustrate the
applicability of declarative techniques are DriverLINX and
ExceLINX in the fields of data acquisition and test instrument
control.
Using Declarations for Data Acquisition
DriverLINX is an API for controlling data-acquisition hardware
used to measure and generate analog and digital signals
interfaced to all types of external transducers.
Data-acquisition applications include laboratory research,
medical instrumentation, and industrial process control.
Traditionally, APIs for data-acquisition devices modeled the
characteristics of the hardware design and had a large number of
functions of one or more parameters to setup the hardware and
control data flow through the system. The ordering of sequences
of operations was often critical to correctly programming and
controlling the hardware. Upgrading to new data-acquisition
hardware was often costly as hardware-necessitated changes in
the order of operation sequences to program the hardware
required costly software changes.
To surmount these problems, DriverLINX takes an abstract and
declarative approach to data-acquisition programming. Instead of
modeling specific board designs, DriverLINX abstracts the
functional subsystems of data-acquisition hardware into
generalized attributes and capabilities. Programs request the
measurement task they want to perform by parameterizing a
"service request" declaration. The DriverLINX runtime determines
how to satisfy the service request using the available hardware
and returns the measurements as a packetized stream to the
program. The data-acquisition programmer is relieved of any
responsibility for data-acquisition algorithm control.
Besides relieving the programmer of control responsibility, the
DriverLINX abstract, declarative approach gives the program
syntactic and semantic interchangeability when migrating to
equivalent hardware products. The abstract, declarative approach
also helps isolate the software vendor from early technological
obsolescence of change in the computer industry by focusing on
the immutable logic of data-acquisition relations while the
control mechanisms vary with software developments. DriverLINX
has been a viable approach to data-acquisition programming for
more than 12 years despite the market evolution from 16-bit
Windows to .NET today.
Using Declarations for Test Instruments
Test instruments, such as digital voltmeters and electrometers,
have evolved from simple devices with a front panel knob and
display screen to sophisticated measurement processors
performing dozens of measurement and control functions. Like
data-acquisition devices, typically developers send a carefully
ordered sequence of commands to an instrument to setup the
measurement and then send additional command sequences to
control the data flow of measurements from the instrument. The
aforementioned problems for developers using imperative
approaches to instrument control significantly limit ease of use
and prohibit quick instrumentation solutions to short-term
measurement needs.
ExceLINX is an add-in to Microsoft Excel that allows rapid
specification of instrument test setups by using worksheet
forms. Users specify, or declare, the channels, configurations,
sampling rates, triggering, and data locations for the
measurements they wish to perform by filling out an Excel
worksheet. When the user selects the "start" button on the
toolbar, ExceLINX translates the specification into the correct
command sequence for the target instrument, initiates the
measurement, and flows the data back to the requested worksheet.
Users can setup and collect measurements by themselves in
minutes using logic specifications compared to days or weeks
using programmer's time for imperative specifications.
Internally, ExceLINX also uses a declarative approach to
handling the complex problem of field validation for the
worksheet forms. Instruments have hundreds of parameters with
complex overlaps among parameters. To validate whether the
instrument supports the parameter set the user selected,
ExceLINX maintains a dependency tree of allowed, disallowed, and
unused parameters for every input cell on the worksheet. Each
node in the tree also maintains logical relations among the
selected set of parameters that ExceLINX evaluates at runtime to
cross validate user input selections. Each supported instrument
model has different parameter semantics, but ExceLINX can easily
handle this complexity by switching model trees because the
model-specific logic in the validation tree is separate from the
shared control implementation in the ExceLINX code.
Declarative programming strategies that separate logic from
control in algorithms are powerful techniques that can be used
with today's popular imperative languages. These techniques can
make software more interchangeable, maintainable, usable, and
endurable
Copyright Roy E. Furman, M.D., Ph.D 2005
About the author:
Roy Furman, M.D., Ph.D. is Director of Research and Development
at Scientific Software Tools, Inc. He leads a team of software
developers who have produced over 70 commercial software
products for customers in the test and measurement, life science
and healthcare industries. Visit their website,
http//www.sstnet.com for articles and information on software
development.
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