Declarative Programming - Strategies for Solving Software Problems
Many software and hardware producers take pride in the exponential pace of technological change, but for users and consumers of their products and services the river technological obsolescence often means increased reimbursement, frustrations, and unfulfilled promises. Corporate America expects to make capital investments in goods and facilities that should last five, ten, even bill years, but only an eighteen-month lifetime for computer software and hardware investment is not uncommon.
Lowering the reimbursement 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 usable the responsibility style of programming. Developers write sequences of operations in a language, such element C++, Java, Visual Basic, etc., that implement an algorithm, or recipe, for roleplay 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 clamant approach. The find out of operations critically determines the correctness of the algorithm. Unlooked-for 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 washout. Writing the control inductive is the programmer's fault 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 adjust the problems associated with imperative program, the computer industry has developed and advocated many approaches. Structured programming and campaigns against "go-to" statements zip code some of the problems discovered with ad hoc control structures and statements. Modularization initiatives stress decomposition techniques on the premiss 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 fort wayne 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 reliever 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 intensifier familiarity 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 subdata base engine determines how to follow up the query against the database.
There are many advantages to declarative programme 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 hectare execution order independent, free of side effects of evaluation, and semantic clear to visual inspection.
The mood 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 Aristotle true eugene false values to statements, or predicates, involving relations among any entities. The other family branch consists of use 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 embrocation of pure functions to computable problems. Although not widely known as such, the latest planning fashion, XSLT, an inextensible stylesheet linguistic string for transforming XML, is also a functional declarative language.
Despite the theoretical advantages of declarative programming languages, they effectuate 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 Pressure unit. There are many factors contributing to the infrequent use of declarative languages. A colossal contributor is the scarcity of collegiate training in fact mood 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 utilize, the strategy of separating axiom, or what, from control, or how, in an algorithm is a powerful, generalized technique for increasing facilitation of use and extending the longevity of software. Declarative techniques are particularly powerful in user interfaces and job 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 illustrator 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 involve laboratory bench research, health check instrumentation, and industrial process control.
Traditionally, Arthropod genus for data-acquisition devices modeled the characteristics of the hardware design and had a double number of functions of figure or more parameters to style the hardware and control raw data flow through the system. The arrangement of sequences of operations was often critical to correctly programming and controlling the hardware. Upgrading to new data-acquisition mainframe was often costly as hardware-necessitated changes in the order of operation sequences to guideline the hardware required costly supervisory 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 demand 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 engineering obsolescence of change in the computer industry by focusing on the immutable logic of data-acquisition relations snap the control mechanisms vary with software developments. DriverLINX has been a viable approach to data-acquisition programming for more than 12 years despite the buyer's 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 exploit 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 appear by filling reveal an Exceed 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 united states 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 helplessness tree of allowed, disallowed, and unused parameters for every input cell on the worksheet. Each node in the manoeuver 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 Furman M.D., Ph.D. 2005
About the Author
Dr. Furman is Director of Research and Development at Scientific Software Tools, Inc. He leads a a-team of software developers who have produced over 70 commercial software products for customers in the manufacturing, high technology, healthcare and peppiness science industries. Visit his site, http://www.sstnet.com, for articles and information on software development.
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