Data Flow Testing

THE STRATEGIES Page 163 of the Boris Beizer text

Basics of strategies…• Data flow testing strategies are structural strategies.• Data flow strategies require data-flow link weights

(d,k,u,c,p).• They are based on selecting test path segments (sub-

paths) that satisfy some characteristic of data flows for all data objects.

• A strategy X is stronger than strategy Y if all test cases produced under Y are included in those produced under X.

• Conversely for weaker strategies.

Overview of the strategies considered:

• The structural test strategies that we will discuss in the further slides are based on the program’s control flow graph.

• The differences in these strategies are – – the predicate uses and/or computational uses of variables

included in the test set– All computational uses versus at least one computational

use– Both computational and predicate versus either one or

the other

All – du paths (ADUP):• This is the strongest data-flow testing strategy.• A du-path from node i to k is a path segment such

that, if the last link has a computational use of X, then the path is simple & definition clear.

• ADUP is a data-flow testing strategy that requires every definition of every variable from every du path to use every variable of that definition.

• ADUP becomes more complicated when a variable is redefined in many places.

• This strategy considers one test at a time. • ADUP requires the greatest number of paths.

All – du paths (ADUP cont…): Example:

From the figure, we see that variables A and B are defined on link (1,2). It is evident that any path taken for the graph will traverse through (1,2) . Hence the criterion for variables A & B as per ADUP is satisfied. But we have a redefinition at link (3,4). Variable C will not satisfy ADUP if only the path (1,3) is taken, thus violating the ADUP definition.

ADUP becomes complicated when a variable is redefined in many places.

1 2 3 4Begin End

A, B C

All – Uses strategy (AU):• Here, we step down from all paths to branch

coverage.• AU is a strategy that requires every definition from at

least one path segment to use every variable that can be reached by that definition.

If a variable X has a predicate use as shown above, the sub-paths (2,3,4) and (2,4) would be included in some tests. In AU strategy, we don’t have to use both in the same path, meaning (4,5) can be reached by either (2,3,4) or (2,4).

1 2 3 4Begin End C 5

X

All – du paths (ADUP cont…): Example:

From the figure, we see that variables A and B are defined on link (1,2). It is evident that any path taken for the graph will traverse through (1,2) . Hence the criterion for variables A & B as per ADUP is satisfied. But we have a redefinition at link (3,4). Variable C will not satisfy ADUP if only the path (1,3) is taken, thus violating the ADUP definition.

ADUP becomes complicated when a variable is redefined in many places.

1 2 3 4Begin End

A, B C

All–p–Uses/Some–c–Uses strategies (APU+C):• If a variable has a predicate use, then, there is no

need to select a computational use. • The (APU+C) is a strategy requires that – for every

variable and its definition, include at least one definition-free path from the definition to every predicate use. If there are definitions of the variable that are not covered by predicate use, then add computational-use test cases as required, to cover every definition.

All–p–Uses/Some–c–Uses strategies (APU+C cont…): d P cd cd cd P P

• In the (APU + C) strategy, every definition of every variable has a path to every P-use of that definition.

If there is no P-use of the definition, then a c-use is considered.

• Links (1,2), (3,4), (4,5), (5,6) must be included in test cases because they contain definitions for variable Z. The links (2,3),(6,7),(8,9) must also be included in test cases because they contain predicate uses of Z, which c-use does not cover.

1 2 4 5Begin 3 7 86 9 End Z

Flow graph annotated for variable Z

All–c–Uses/Some–p–Uses strategies (ACU-P):• In this testing strategy, we first need to ensure that every

definition has a computational use of that definition and if any definition is not covered, predicate use cases are added to ensure(make sure) that every definition is included in some test case.

• Definition:(ACU + P) is a testing strategy which requires that every definition of every variable includes at least one path from that definition to every computational use.

All–c–Uses/Some–p–Uses strategies (ACU-P cont…):

d c c p c p

c

• As seen above, ACU coverage is achieved for Y by the path (1,2,3,4,7,8,9,10). But several definitions of predicate uses are not covered – path (4,5,6,7).

• In this testing strategy, every definition of every variable has a path to every c-use of that definition. If there is no c-use of that definition, the p-use of the definition is considered. Hence, the (ACU+P) coverage of the path for Y should be (1,2,3,4,7,8,9,10).

1 2 4 5Begin 3

End Z

Flow graph annotated for variable Y

10 9 7 68

Y

All – Definitions strategy (AD):• The AD strategy is weaker than both (ACU+P) and (APU+C)

strategies.• Definition: AD is a testing strategy that requires every definition

of every variable to cover at least one use of that variable. The use can be a computational use(c) or a predicate use(p).

• The path (1,2,3,4,5,6,7,8,9,10) satisfies the AD strategy for variable Y. For the variable Z, any entry or exist path satisfies the AD criterion. Therefore, we expect that the AD strategy is weaker than both the (ACU+P) and (APU+C) strategies.

• Every definition has a path to at least one use of that definition.

**Refer the earlier slide for fig.

All–Predicate–Uses Strategy:• In this testing strategy, every definition of every

variable has a path to every P-use of that definition.• If there is no P-use in the definition, then it is dropped

from the contention(argument).• Definition: APU is a testing strategy derived from the

(APU+C) strategy. But here, we do not include a c-use for the variable if there are no p-uses for the variable following each definition.APU is therefore weaker than (APU+C).

All–Computational Uses Strategies:

• Also referred to as the ACU strategy.• Definition:

ACU is a testing strategy derived from the (ACU+P) strategy. But here, we do not include a p-use for the variable if there are no c-uses for the variable following each definition.

• It is therefore evident(obvious) that ACU is weaker than (ACU+P).

Ordering the strategies:

All Paths

All DU Paths

All-C Uses

All-P/Some-CAll-C/Some-P

All Uses

All-P UsesAll Definitions

Branch

Statement

This shows the relative strength of data flow & control flow testing strategies.

Test cases are based on the Relative strength of testing strategies.

(ACU+P) & (APU+C) are in parallel & hence

comparable

The strength of the testing strategies reduces along the Direction of the arrow. For example, All-Uses is weaker than All DU paths.

Branch & Statement are control flow test strategies

Done!!! Do feel free to get back incase you have any questions

Note: This did appear in earlier papers. So please don’t skip!!