A cause-effect graph is a directed graph that maps a set of causes to a set of effects. The causes may be thought of as the input to the program, and the effects may be thought of as the output. Usually the graph shows the nodes representing the causes on the left side and the nodes representing the effects on the right side. There may be intermediate nodes in between that combine inputs using logical operators such as AND and OR.
Constraints may be added to the causes and effects. These are represented as edges labelled with the constraint symbol using a dashed line. For causes, valid constraint symbols are E (exclusive?), O (one and only one?), and I (at least one?). For effects, valid constraint symbols are R (Require?) and M (Mask?). (This information needs to be verified.)
The graph's direction is as follows:
(XXX: a figure would represent this better)Causes --> intermediate nodes --> Effects It is a proven technique for effective requirements validation and test case design, cause-effect graphing is the process of transforming specifications into a graphic representation. This graphic representation depicts the functional relationships and conditions present in the requirements, illustrating how each input relates to every other input, as well as every output.
Constraints and observability of nodes also are established during this process, allowing the project team to identify potential problem areas. In developing the cause-effect graph, the test team evaluates the requirements for completeness, consistency, sufficient level of detail and lack of ambiguity, often finding defects that otherwise would not be found until integration testing.
Constraints may be added to the causes and effects. These are represented as edges labelled with the constraint symbol using a dashed line. For causes, valid constraint symbols are E (exclusive?), O (one and only one?), and I (at least one?). For effects, valid constraint symbols are R (Require?) and M (Mask?). (This information needs to be verified.)
The graph's direction is as follows:
(XXX: a figure would represent this better)Causes --> intermediate nodes --> Effects It is a proven technique for effective requirements validation and test case design, cause-effect graphing is the process of transforming specifications into a graphic representation. This graphic representation depicts the functional relationships and conditions present in the requirements, illustrating how each input relates to every other input, as well as every output.
Constraints and observability of nodes also are established during this process, allowing the project team to identify potential problem areas. In developing the cause-effect graph, the test team evaluates the requirements for completeness, consistency, sufficient level of detail and lack of ambiguity, often finding defects that otherwise would not be found until integration testing.
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