Decision tables are a concise visual representation for specifying which actions to perform depending on given conditions. They are algorithms whose output is a set of actions. The information expressed in decision tables could also be represented as decision trees or in a programming language as a series of if-then-else and switch-case statements.
Each decision corresponds to a variable, relation or predicate whose possible values are listed among the condition alternatives. Each action is a procedure or operation to perform, and the entries specify whether (or in what order) the action is to be performed for the set of condition alternatives the entry corresponds to.
To make them more concise, many decision tables include in their condition alternatives a don't care symbol. This can be a hyphen or blank, although using a blank is discouraged as it may merely indicate that the decision table has not been finished. One of the uses of decision tables is to reveal conditions under which certain input factors are irrelevant on the actions to be taken, allowing these input tests to be skipped and thereby streamlining decision-making procedures.
|The above tables convey identical information, but the second table uses a hyphen as a don't-care symbol for brevity.|
Aside from the basic four quadrant structure, decision tables vary widely in the way the condition alternatives and action entries are represented. Some decision tables use simple true/false values to represent the alternatives to a condition (similar to if-then-else), other tables may use numbered alternatives (similar to switch-case), and some tables even use fuzzy logic or probabilistic representations for condition alternatives. In a similar way, action entries can simply represent whether an action is to be performed (check the actions to perform), or in more advanced decision tables, the sequencing of actions to perform (number the actions to perform).
A decision table is considered balanced or complete if it includes every possible combination of input variables. In other words, balanced decision tables prescribe an action in every situation where the input variables are provided.
The limited-entry decision table is the simplest to describe. The condition alternatives are simple Boolean values, and the action entries are check-marks, representing which of the actions in a given column are to be performed.
A technical support company writes a decision table to diagnose printer problems based upon symptoms described to them over the phone from their clients.
The following is a balanced decision table.
|A red light is flashing||Yes||Yes||No||No||Yes||Yes||No||No|
|Printer is recognized by computer||No||Yes||No||Yes||No||Yes||No||Yes|
|Actions||Check the power cable||—|
|Check the printer-computer cable||—|
|Ensure printer software is installed||—|
|Check for paper jam||—|
Of course, this is just a simple example (and it does not necessarily correspond to the reality of printer troubleshooting), but even so, it demonstrates how decision tables can scale to several conditions with many possibilities.
Software engineering benefits
Decision tables, especially when coupled with the use of a domain-specific language, allow developers and policy experts to work from the same information, the decision tables themselves.
Decision tables have proven to be easier to understand and review than code, and have been used extensively and successfully to produce specifications for complex systems.
In the 1960s and 1970s a range of "decision table based" languages such as Filetab were popular for business programming.
Program embedded decision tables
Decision tables can be, and often are, embedded within computer programs and used to "drive" the logic of the program. A simple example might be a lookup table containing a range of possible input values and a function pointer to the section of code to process that input.
|"1"||Function 1 (initialize)|
|"2"||Function 2 (process 2)|
|"9"||Function 9 (terminate)|
Multiple conditions can be coded for in similar manner to encapsulate the entire program logic in the form of an "executable" decision table or control table. There may be several such tables in practice, operating at different levels and often linked to each other (either by pointers or an index value).
- Filetab, originally from the NCC
- DETAB/65, 1965, ACM
- FORTAB from Rand in 1962, designed to be imbedded in FORTRAN
- A Ruby implementation exists using MapReduce to find the correct actions based on specific input values.
- Decision trees
- Case based reasoning
- Cause–effect graph
- Dominance-based rough set approach
- Karnaugh-Veitch diagram
- Many-valued logic
- Semantic decision table
- LI Jing (1 April 2015). "SEEM 3430 Tutorial: Decision Tables" (PDF). p. 23. Retrieved 11 November 2017.
- "Creating a Decision Table in Business Rules". Oracle Help Center. 6 August 2017. Retrieved 11 November 2017.
- Ross, Ronald G. (2005). "Decision Tables, Part 2 ~ The Route to Completeness". Business Rules Journal. 6 (8). Retrieved 11 November 2017.
- Snow, Paul (19 July 2012). "Decision Tables". DTRules: A Java Based Decision Table Rules Engine. Retrieved 11 November 2017.
- LI Jing 2015, p. 24-25.
- Rogers, William T. "Decision Table Examples: Medical Insurance". Saint Xavier University Systems Analysis and Design. Archived from the original on March 29, 2007.
- "Archived copy". Archived from the original on 2012-05-30. Retrieved 2010-07-07.CS1 maint: archived copy as title (link)
- Wets, Geert; Witlox, Frank; Timmermans, Harry; Vanthienen, Jan (1996). "Locational choice modelling using fuzzy decision tables". New frontiers in fuzzy logic and computing: 1996 biennial conference of the North American Fuzzy Information Processing Society – NAFIPS. Biennial Conference of the North American Fuzzy Information Processing Society. Berkeley, CA: IEEE. pp. 80–84. doi:10.1109/NAFIPS.1996.534708. ISBN 0-7803-3225-3.
- "A Real CCIDE Example"
- "Experience With The Cope Decision Table Processor". Archived from the original on 2017-05-04. Retrieved 2010-07-07.
- Udo W. Pooch, "Translation of Decision Tables," ACM Computing Surveys, Volume 6, Issue 2 (June 1974) Pages: 125–151 ISSN 0360-0300
- "FORTAB: A Decision Table Language for Scientific Computing Applications", 1962, Rand
- Alexander Williams (2015). "Ruby decision table parser"
- Dwyer, B. and Hutchings, K. (1977) "Flowchart Optimisation in Cope, a Multi-Choice Decision Table" Aust. Comp. J. Vol. 9 No. 3 p. 92 (Sep. 1977).
- Fisher, D.L. (1966) "Data, Documentation and Decision Tables" Comm ACM Vol. 9 No. 1 (Jan. 1966) p. 26–31.
- General Electric Company (1962) GE-225 TABSOL reference manual and GF-224 TABSOL application manual CPB-l47B (June 1962).
- Grindley, C.B.B. (1968) "The Use of Decision Tables within Systematics" Comp. J. Vol. 11 No. 2 p. 128 (Aug. 1968).
- Jackson, M.A. (1975) Principles of Program Design Academic Press
- Myers, H.J. (1972) "Compiling Optimised Code from Decision Tables" IBM J. Res. & Development (Sept. 1972) p. 489–503.
- Pollack, S.L. (1962) "DETAB-X: An improved business-oriented computer language" Rand Corp. Memo RM-3273-PR (August 1962)
- Schumacher, H. and Sevcik, K.C. (1976) "The Synthetic Approach to Decision Table Conversion" Comm. ACM Vol. 19 No. 6 (June 1976) p. 343–351
- CSA, (1970): Z243.1–1970 for Decision Tables, Canadian Standards Association
- Jorgensen, Paul C. (2009) Modeling Software Behavior: A Craftsman's Approach. Auerbach Publications, CRC Press. Chapter 5.