Method and apparatus for partial test-cause generation

Claim 2

A partial test-cause generation method comprising the following steps: entering data structure of a boolean function expressed in a decision table, the decision table being indicative of output conditions and states after transition, for combinations of various input conditions; generating a singular matrix based on the entered data structure; checking constraint conditions by comparison of the entered data structure and the generated singular matrix to produce a cause pattern row; expanding the cause pattern row into effect and state pattern rows; checking the validity of said cause, effect and state pattern rows and; editing the resulting pattern rows to produce a partial test-cause.

Claim 3

A partial test-cause generation method comprising: a first step of entering information including a constraint row of a boolean function expressed in a decision table indicative of a correspondence between input and output conditions; a second step of producing a singular matrix for eliminating infeasible combinations in accordance with the constraint row in the decision table entered in said first step; a third step of comparing the pattern of an intermediate row extracted from said decision table with a pattern of the singular matrix produced in said second step, checking constraint conditions for eliminating infeasible combinations between cause nodes, and producing a cause pattern row; a fourth step of expanding the cause pattern row produced in said third step, producing all combinational pattern separately for each cause, and producing effect, state and intermediate pattern rows in accordance with said combinational patterns; and, a fifth step of implementing a validity check for said cause, effect and state pattern rows, and editing said pattern rows to produce a partial test-cause.

Claim 4

A partial test-cause generation method comprising: a first step of entering information including a constraint row of a boolean function expressed in a decision table indicative of a correspondence between input and output conditions; a second step of producing a singular matrix for eliminating infeasible combinations in accordance with the constraint row in the decision table entered in said first step; a third step of comparing the pattern of an intermediate row extracted from said decision table with a pattern of the singular matrix produced in said second step, checking constraint conditions for eliminating infeasible combinations between cause nodes, and producing a cause pattern row; a fourth step of expanding the cause pattern row produced in said third step, producing all combinational pattern separately for each cause, and producing effect, state and intermediate pattern rows in accordance with said combinational patterns; and, a fifth step of implementing a validity check for said cause, effect and state pattern rows, and editing said pattern rows to produce a partial test-cause.

Claim 5

A partial test-cause generation apparatus comprising: first means for entering data structure of a boolean function expressed in a decision table, the decision table being indicative of output conditions and the states after transition, for combinations of various input conditions; second means for generating a singular matrix based on the entered data structure; third means for checking constraint conditions by comparison of the entered data structure and the generated singular matrix to produce a cause pattern row; fourth means for expanding the cause pattern row produced by said third means into effect and state pattern rows; and fifth means for checking the validity of said cause, effect and state pattern rows, and editing the resulting pattern rows to produce a partial test-cause.

Claim 6

A partial test-cause generation apparatus comprising: first means for entering data structure of a boolean function expressed in a decision table, the decision table being indicative of output conditions and the states after transition, for combinations of various input conditions; second means for generating a singular matrix based on the entered data structure; third means for checking constraint conditions by comparison of the entered data structure and the generated singular matrix to produce a cause pattern row; fourth means for expanding the cause pattern row produced by said third means into effect and state pattern rows; and fifth means for checking the validity of said cause, effect and state pattern rows, and editing the resulting pattern rows to produce a partial test-cause.

Claim 7

A partial test-cause generation apparatus comprising: first means for entering data structure of a boolean function in the form of a decision table, the decision table being indicative of output conditions and states after transition, for combinations of various input conditions; second means for producing a singular matrix for eliminating infeasible combinations in accordance with a constraint row in the decision table entered by said first means; third means for comparing a pattern of an intermediate row extracted from said decision table with a pattern of singular matrix produced by said second means, checking constraint conditions by comparison for the entered data structure and the generated singular matrix to produce a cause pattern row; fourth means for expanding the cause pattern produced by said third means, producing all combinational patterns separately for each cause, and producing effect, state and intermediate pattern rows in accordance with said combinational patterns; and fifth means for implementing a validity check for said cause, effect and state pattern rows, and editing said pattern rows to produce a partial test-cause.

Claim 8

A partial test-cause generation apparatus comprising: first means for entering data structure of a boolean function in the form of a decision table, the decision table being indicative of output conditions and states after transition, for combinations of various input conditions; second means for producing a singular matrix for eliminating infeasible combinations in accordance with a constraint row in the decision table entered by said first means; third means for comparing a pattern of an intermediate row extracted from said decision table with a pattern of singular matrix produced by said second means, checking constraint conditions by comparison for the entered data structure and the generated singular matrix to produce a cause pattern row; fourth means for expanding the cause pattern produced by said third means, producing all combinational patterns separately for each cause, and producing effect, state and intermediate pattern rows in accordance with said combinational patterns; and fifth means for implementing a validity check for said cause, effect and state pattern rows, and editing said pattern rows to produce a partial test-cause.