Misplaced Pages

#904095

53-483: DSR focuses on the development and performance of (designed) artifacts with the explicit intention of improving the functional performance of the artifact. DSRM is typically applied to categories of artifacts including algorithms , human/computer interfaces , design methodologies (including process models ) and languages. Its application is most notable in the Engineering and Computer Science disciplines, though

106-595: A binary search algorithm (with cost ⁠ O ( log ⁡ n ) {\displaystyle O(\log n)} ⁠ ) outperforms a sequential search (cost ⁠ O ( n ) {\displaystyle O(n)} ⁠ ) when used for table lookups on sorted lists or arrays. The analysis, and study of algorithms is a discipline of computer science . Algorithms are often studied abstractly, without referencing any specific programming language or implementation. Algorithm analysis resembles other mathematical disciplines as it focuses on

159-468: A flowchart offers a way to describe and document an algorithm (and a computer program corresponding to it). It has four primary symbols: arrows showing program flow, rectangles (SEQUENCE, GOTO), diamonds (IF-THEN-ELSE), and dots (OR-tie). Sub-structures can "nest" in rectangles, but only if a single exit occurs from the superstructure. It is often important to know how much time, storage, or other cost an algorithm may require. Methods have been developed for

212-745: A function . Starting from an initial state and initial input (perhaps empty ), the instructions describe a computation that, when executed , proceeds through a finite number of well-defined successive states, eventually producing "output" and terminating at a final ending state. The transition from one state to the next is not necessarily deterministic ; some algorithms, known as randomized algorithms , incorporate random input. Around 825 AD, Persian scientist and polymath Muḥammad ibn Mūsā al-Khwārizmī wrote kitāb al-ḥisāb al-hindī ("Book of Indian computation") and kitab al-jam' wa'l-tafriq al-ḥisāb al-hindī ("Addition and subtraction in Indian arithmetic"). In

265-435: A heuristic is an approach to solving problems that do not have well-defined correct or optimal results. For example, although social media recommender systems are commonly called "algorithms", they actually rely on heuristics as there is no truly "correct" recommendation. As an effective method , an algorithm can be expressed within a finite amount of space and time and in a well-defined formal language for calculating

318-680: A computer-executable form, but are also used to define or document algorithms. There are many possible representations and Turing machine programs can be expressed as a sequence of machine tables (see finite-state machine , state-transition table , and control table for more), as flowcharts and drakon-charts (see state diagram for more), as a form of rudimentary machine code or assembly code called "sets of quadruples", and more. Algorithm representations can also be classified into three accepted levels of Turing machine description: high-level description, implementation description, and formal description. A high-level description describes qualities of

371-719: A computing machine or a human who could only carry out specific elementary operations on symbols . Most algorithms are intended to be implemented as computer programs . However, algorithms are also implemented by other means, such as in a biological neural network (for example, the human brain performing arithmetic or an insect looking for food), in an electrical circuit , or a mechanical device. Step-by-step procedures for solving mathematical problems have been recorded since antiquity. This includes in Babylonian mathematics (around 2500 BC), Egyptian mathematics (around 1550 BC), Indian mathematics (around 800 BC and later),

424-758: A designed artifact. Since the first days of computer science , computer scientists have been doing DSR without naming it. They have developed new architectures for computers, new programming languages, new compilers, new algorithms, new data and file structures, new data models, new database management systems, and so on. Much of the early research was focused on systems development approaches and methods. The dominant research philosophy in many disciplines has focused on developing cumulative, theory-based research results in order to make prescriptions. It seems that this ‘theory-with-practical-implications’ research strategy has not delivered on this aim, which led to search for practical research methods such as DSR. The design process

477-403: A possible product of Mode 2 research with the potential to improve the relevance of academic research in management. Mode 1 knowledge production is purely academic and mono-disciplinary, while Mode 2 is multidisciplinary and aims at solving complex and relevant field problems. Hevner et al. have presented a set of guidelines for DSR within the discipline of Information Systems (IS). DSR requires

530-525: A programmer can write structured programs using only these instructions; on the other hand "it is also possible, and not too hard, to write badly structured programs in a structured language". Tausworthe augments the three Böhm-Jacopini canonical structures : SEQUENCE, IF-THEN-ELSE, and WHILE-DO, with two more: DO-WHILE and CASE. An additional benefit of a structured program is that it lends itself to proofs of correctness using mathematical induction . By themselves, algorithms are not usually patentable. In

583-477: A sequence of operations", which would include all computer programs (including programs that do not perform numeric calculations), and any prescribed bureaucratic procedure or cook-book recipe . In general, a program is an algorithm only if it stops eventually —even though infinite loops may sometimes prove desirable. Boolos, Jeffrey & 1974, 1999 define an algorithm to be an explicit set of instructions for determining an output, that can be followed by

SECTION 10

#1732787296905

636-548: A similar framework, the Technology Readiness Level (TRL) model. The TRL model was proposed by NASA and is currently also widely applied in the European Union 's research programs such as Horizon. Thus, validation leads to TRL level 4 - “Technology validated in a laboratory environment”; while evaluation leads to a TRL level 6 - “Technology demonstrated in a relevant environment”. Books,

689-472: Is a finite sequence of mathematically rigorous instructions, typically used to solve a class of specific problems or to perform a computation . Algorithms are used as specifications for performing calculations and data processing . More advanced algorithms can use conditionals to divert the code execution through various routes (referred to as automated decision-making ) and deduce valid inferences (referred to as automated reasoning ). In contrast,

742-416: Is a method or mathematical process for problem-solving and engineering algorithms. The design of algorithms is part of many solution theories, such as divide-and-conquer or dynamic programming within operation research . Techniques for designing and implementing algorithm designs are also called algorithm design patterns, with examples including the template method pattern and the decorator pattern. One of

795-581: Is a more specific classification of algorithms; an algorithm for such problems may fall into one or more of the general categories described above as well as into one of the following: One of the simplest algorithms finds the largest number in a list of numbers of random order. Finding the solution requires looking at every number in the list. From this follows a simple algorithm, which can be described in plain English as: High-level description: (Quasi-)formal description: Written in prose but much closer to

848-629: Is a potential gulf between theoretical propositions and concrete issues faced in practice—a challenge known as design theory indeterminacy . Guidelines for addressing this challenges are provided in Lukyanenko et al. 2020. The engineering cycle is a framework used in Design Science for Information Systems and Software Engineering, proposed by Roel Wieringa . Artifacts within DSR are perceived to be knowledge containing. This knowledge ranges from

901-434: Is a sequence of expert activities that produces an innovative product. The artifact enables the researcher to get a better grasp of the problem; the re-evaluation of the problem improves the quality of the design process and so on. This build-and-evaluate loop is typically iterated a number of times before the final design artifact is generated. In DSR, the focus is on the so-called field-tested and grounded technological rule as

954-657: Is not restricted to these and can be found in many disciplines and fields. DSR, or constructive research, in contrast to explanatory science research, has academic research objectives generally of a more pragmatic nature. Research in these disciplines can be seen as a quest for understanding and improving human performance . Such renowned research institutions as the MIT Media Lab , Stanford University 's Center for Design Research, Carnegie Mellon University 's Software Engineering Institute, Xerox ’s PARC, and Brunel University London ’s Organisation and System Design Centre, use

1007-411: Is possible and useful for the creation of possible futures, rather than on what is currently existing. This mission can be compared to that of the ‘explanatory sciences’, like the natural sciences and sociology, which is to develop knowledge to describe, explain and predict. Hevner states that the main purpose of DSR is achieving knowledge and understanding of a problem domain by building and application of

1060-453: Is useful for uncovering unexpected interactions that affect performance. Benchmarks may be used to compare before/after potential improvements to an algorithm after program optimization. Empirical tests cannot replace formal analysis, though, and are non-trivial to perform fairly. To illustrate the potential improvements possible even in well-established algorithms, a recent significant innovation, relating to FFT algorithms (used heavily in

1113-1107: The Entscheidungsproblem (decision problem) posed by David Hilbert . Later formalizations were framed as attempts to define " effective calculability " or "effective method". Those formalizations included the Gödel – Herbrand – Kleene recursive functions of 1930, 1934 and 1935, Alonzo Church 's lambda calculus of 1936, Emil Post 's Formulation 1 of 1936, and Alan Turing 's Turing machines of 1936–37 and 1939. Algorithms can be expressed in many kinds of notation, including natural languages , pseudocode , flowcharts , drakon-charts , programming languages or control tables (processed by interpreters ). Natural language expressions of algorithms tend to be verbose and ambiguous and are rarely used for complex or technical algorithms. Pseudocode, flowcharts, drakon-charts, and control tables are structured expressions of algorithms that avoid common ambiguities of natural language. Programming languages are primarily for expressing algorithms in

SECTION 20

#1732787296905

1166-686: The Journal of Software and Systems Modeling , and the Requirements Engineering Journal . In 2019, Wieringa retired from academia, and now works and blogs at The Value Engineers, which was founded in 2017 with Jaap Gordijn and Dan Ionita. The engineering cycle is a framework used in Design Science for Information Systems and Software Engineering, proposed by Roel Wieringa in his book "Design Science Methodology for Information Systems and Software Engineering". The engineering cycle consists of: The design cycle consists of

1219-629: The Jacquard loom , a precursor to Hollerith cards (punch cards), and "telephone switching technologies" led to the development of the first computers. By the mid-19th century, the telegraph , the precursor of the telephone, was in use throughout the world. By the late 19th century, the ticker tape ( c.  1870s ) was in use, as were Hollerith cards (c. 1890). Then came the teleprinter ( c.  1910 ) with its punched-paper use of Baudot code on tape. Telephone-switching networks of electromechanical relays were invented in 1835. These led to

1272-619: The University of Groningen , Faculty of Mathematics, for the thesis "Generatieve Grammatika's en Bijbehorende Analyseprocedures voor Natuurlijke talen" (Generative Grammars and Their Analysis procedures for NaturalLanguages". He received his MA in 1987 at the University of Amsterdam , Faculty of Philosophy for the thesis Machine intelligence and Explication , and his PhD in 1990 at the Vrije Universiteit Amsterdam , under supervision of Reinder Pieter van de Riet for

1325-401: The DSR approach. Design science is a valid research methodology to develop solutions for practical engineering problems. Design science is particularly suitable for wicked problem s. The main goal of DSR is to develop knowledge that professionals of the discipline in question can use to design solutions for their field problems. Design sciences focus on the process of making choices on what

1378-792: The Ifa Oracle (around 500 BC), Greek mathematics (around 240 BC), and Arabic mathematics (around 800 AD). The earliest evidence of algorithms is found in ancient Mesopotamian mathematics. A Sumerian clay tablet found in Shuruppak near Baghdad and dated to c.  2500 BC describes the earliest division algorithm . During the Hammurabi dynasty c.  1800  – c.  1600 BC , Babylonian clay tablets described algorithms for computing formulas. Algorithms were also used in Babylonian astronomy . Babylonian clay tablets describe and employ algorithmic procedures to compute

1431-596: The United States, a claim consisting solely of simple manipulations of abstract concepts, numbers, or signals does not constitute "processes" (USPTO 2006), so algorithms are not patentable (as in Gottschalk v. Benson ). However practical applications of algorithms are sometimes patentable. For example, in Diamond v. Diehr , the application of a simple feedback algorithm to aid in the curing of synthetic rubber

1484-454: The algorithm itself, ignoring how it is implemented on the Turing machine. An implementation description describes the general manner in which the machine moves its head and stores data in order to carry out the algorithm, but does not give exact states. In the most detail, a formal description gives the exact state table and list of transitions of the Turing machine. The graphical aid called

1537-588: The algorithm's properties, not implementation. Pseudocode is typical for analysis as it is a simple and general representation. Most algorithms are implemented on particular hardware/software platforms and their algorithmic efficiency is tested using real code. The efficiency of a particular algorithm may be insignificant for many "one-off" problems but it may be critical for algorithms designed for fast interactive, commercial or long life scientific usage. Scaling from small n to large n frequently exposes inefficient algorithms that are otherwise benign. Empirical testing

1590-403: The analysis of algorithms to obtain such quantitative answers (estimates); for example, an algorithm that adds up the elements of a list of n numbers would have a time requirement of ⁠ O ( n ) {\displaystyle O(n)} ⁠ , using big O notation . The algorithm only needs to remember two values: the sum of all the elements so far, and its current position in

1643-457: The application of well-known processes. The central design cycle iterates between the core activities of building and evaluating the design artifacts and processes of the research. DSR in itself implies an ethical change from describing and explaining of the existing world to shaping it. One can question the values of information system research, i.e., whose values and what values dominate it, emphasizing that research may openly or latently serve

Design science (methodology) - Misplaced Pages Continue

1696-696: The computer science department at the University of Twente . Circa 1996, Wieringa and Frank Dehne wrote the Toolkit for Conceptual Modeling , for Wieringa's conceptual modeling courses and book, Requirements Engineering: Frameworks for Understanding . Wieringa has been Associate Editor in Chief of the IEEE Software journal from 2004 to 2007, and was member of the editorial board of the International Journal of Business Information Systems ,

1749-412: The creation of an innovative, purposeful artifact for a special problem domain . The artifact must be evaluated in order to ensure its utility for the specified problem. In order to form a novel research contribution, the artifact must either solve a problem that has not yet been solved, or provide a more effective solution. Both the construction and evaluation of the artifact must be done rigorously, and

1802-969: The design logic, construction methods and tool to assumptions about the context in which the artifact is intended to function (Gregor, 2002). The creation and evaluation of artifacts thus forms an important part in the DSR process which was described by Hevner et al., (2004) and supported by March and Storey (2008) as revolving around “build and evaluate”. DSR artifacts can broadly include: models, methods, constructs, instantiations and design theories (March & Smith, 1995; Gregor 2002; March & Storey, 2008, Gregor and Hevner 2013), social innovations, new or previously unknown properties of technical/social/informational resources (March, Storey, 2008), new explanatory theories, new design and developments models and implementation processes or methods (Ellis & Levy 2010). DSR can be seen as an embodiment of three closely related cycles of activities. The relevance cycle initiates DSR with an application context that not only provides

1855-521: The earliest codebreaking algorithm. Bolter credits the invention of the weight-driven clock as "the key invention [of Europe in the Middle Ages ]," specifically the verge escapement mechanism producing the tick and tock of a mechanical clock. "The accurate automatic machine" led immediately to "mechanical automata " in the 13th century and "computational machines"—the difference and analytical engines of Charles Babbage and Ada Lovelace in

1908-523: The early 12th century, Latin translations of said al-Khwarizmi texts involving the Hindu–Arabic numeral system and arithmetic appeared, for example Liber Alghoarismi de practica arismetrice , attributed to John of Seville , and Liber Algorismi de numero Indorum , attributed to Adelard of Bath . Hereby, alghoarismi or algorismi is the Latinization of Al-Khwarizmi's name; the text starts with

1961-427: The field of image processing), can decrease processing time up to 1,000 times for applications like medical imaging. In general, speed improvements depend on special properties of the problem, which are very common in practical applications. Speedups of this magnitude enable computing devices that make extensive use of image processing (like digital cameras and medical equipment) to consume less power. Algorithm design

2014-416: The first 3 tasks of the engineering cycle: investigation, design, and validation. The engineering and design cycles do not prescribe a mandatory, rigid sequence of activities. Moreover, they are often applied recursively for sub-problems of the main research objective. The engineering cycle and the design cycle are often applied in several iterations (hence “cycle”). In such a case, the evaluation may become

2067-447: The high-level language of a computer program, the following is the more formal coding of the algorithm in pseudocode or pidgin code : Roel Wieringa Roelf Johannes (Roel) Wieringa (born 1952) is a Dutch computer scientist who was a professor of Information Systems at the University of Twente , specialized in the "integration of formal and informal specification and design techniques". Wieringa received his MSc in 1978 at

2120-408: The implementation in practice. On the other hand, evaluation is executed after the implementation in practice of the designs. It involves analyzing the behavior, effects, and impact of the designed artifacts in practice, in the field. In our case, this meant implementation and analysis of the designs in actual, industry IT projects. Stefan Morcov proposes a parallel between these 2 activities and

2173-450: The input list. If the space required to store the input numbers is not counted, it has a space requirement of ⁠ O ( 1 ) {\displaystyle O(1)} ⁠ , otherwise ⁠ O ( n ) {\displaystyle O(n)} ⁠ is required. Different algorithms may complete the same task with a different set of instructions in less or more time, space, or ' effort ' than others. For example,

Design science (methodology) - Misplaced Pages Continue

2226-827: The interests of particular dominant groups. The interests served may be those of the host organization as perceived by its top management, those of information system users, those of information system professionals or potentially those of other stakeholder groups in society. There are limited references to examples of DSR, but Adams has completed two PhD research topics using Peffers et al.'s DSRP (both associated with digital forensics but from different perspectives): 2013: The Advanced Data Acquisition Model (ADAM): A process model for digital forensic practice 2024: The Advanced Framework for Evaluating Remote Agents (AFERA): A Framework for Digital Forensic Practitioners Algorithm In mathematics and computer science , an algorithm ( / ˈ æ l ɡ ə r ɪ ð əm / )

2279-490: The invention of the digital adding device by George Stibitz in 1937. While working in Bell Laboratories, he observed the "burdensome" use of mechanical calculators with gears. "He went home one evening in 1937 intending to test his idea... When the tinkering was over, Stibitz had constructed a binary adding device". In 1928, a partial formalization of the modern concept of algorithms began with attempts to solve

2332-460: The investigation part of the next engineering cycle. According to the Design science methodology of (Wieringa, 2014), validation is part of the design cycle. It involves checking if the designed artifacts support the initial assumptions. It is executed in a theoretical, “laboratory” environment; such as through discussions and interviews with practitioners and experts. Validation is executed before

2385-429: The mid-19th century. Lovelace designed the first algorithm intended for processing on a computer, Babbage's analytical engine, which is the first device considered a real Turing-complete computer instead of just a calculator . Although a full implementation of Babbage's second device was not realized for decades after her lifetime, Lovelace has been called "history's first programmer". Bell and Newell (1971) write that

2438-627: The most important aspects of algorithm design is resource (run-time, memory usage) efficiency; the big O notation is used to describe e.g., an algorithm's run-time growth as the size of its input increases. Per the Church–Turing thesis , any algorithm can be computed by any Turing complete model. Turing completeness only requires four instruction types—conditional GOTO, unconditional GOTO, assignment, HALT. However, Kemeny and Kurtz observe that, while "undisciplined" use of unconditional GOTOs and conditional IF-THEN GOTOs can result in " spaghetti code ",

2491-564: The phrase Dixit Algorismi , or "Thus spoke Al-Khwarizmi". Around 1230, the English word algorism is attested and then by Chaucer in 1391, English adopted the French term. In the 15th century, under the influence of the Greek word ἀριθμός ( arithmos , "number"; cf. "arithmetic"), the Latin word was altered to algorithmus . One informal definition is "a set of rules that precisely defines

2544-427: The requirements for the research as inputs but also defines acceptance criteria for the ultimate evaluation of the research results. The rigor cycle provides past knowledge to the research project to ensure its innovation. It is incumbent upon the researchers to thoroughly research and reference the knowledge base in order to guarantee that the designs produced are research contributions and not routine designs based upon

2597-429: The results of the research presented effectively both to technology-oriented and management -oriented audiences. Hevner counts 7 guidelines for a DSR: Transparency in DSR is becoming an emerging concern. DSR strives to be practical and relevant. Yet few researchers have examined the extent to which practitioners can meaningfully utilize theoretical knowledge produced by DSR in solving concrete real-world problems. There

2650-685: The thesis Algebraic Foundations for Dynamic Conceptual Models . After finishing his PhD, he continued to work at the Faculty of Mathematics and Computer Science of the Vrije Universiteit. In 1998 he joined the Department of Computer Science of the University of Twente as Professor of Information Systems. From 2006 to 2011 he was Scientific Director of the School of Information and Knowledge Systems (SIKS), and from 2009 to 2012 he headed

2703-675: The time and place of significant astronomical events. Algorithms for arithmetic are also found in ancient Egyptian mathematics , dating back to the Rhind Mathematical Papyrus c.  1550 BC . Algorithms were later used in ancient Hellenistic mathematics . Two examples are the Sieve of Eratosthenes , which was described in the Introduction to Arithmetic by Nicomachus , and the Euclidean algorithm , which

SECTION 50

#1732787296905

2756-449: Was deemed patentable. The patenting of software is controversial, and there are criticized patents involving algorithms, especially data compression algorithms, such as Unisys 's LZW patent . Additionally, some cryptographic algorithms have export restrictions (see export of cryptography ). Another way of classifying algorithms is by their design methodology or paradigm . Some common paradigms are: For optimization problems there

2809-692: Was first described in Euclid's Elements ( c.  300 BC ). Examples of ancient Indian mathematics included the Shulba Sutras , the Kerala School , and the Brāhmasphuṭasiddhānta . The first cryptographic algorithm for deciphering encrypted code was developed by Al-Kindi , a 9th-century Arab mathematician, in A Manuscript On Deciphering Cryptographic Messages . He gave the first description of cryptanalysis by frequency analysis ,

#904095