Abstract
A production system (PS) is a forward chaining rule-based system used to build large expert systems. Testing a PS must involve the construction of a covering set of test data but it is not clear what the meaning of covering a PS is and how a test data set can be measured according to coverage. We propose a test data coverage measure for a subset for PS with well defined semantics. We use a correspondence between PS and function free first order Horn logic programs to define the declarative coverage notion and measure. We found that the coverage measure can be used to determine the coverage of the program logic of a PS as well as to automate test data generation. Unification theory is utilised to measure test data coverage and constrained inductive generation is used for test data construction.
| Language | English |
|---|---|
| Title of host publication | Proceedings Ninth International Symposium on Software Reliability Engineering |
| Publisher | IEEE |
| Pages | 214-221 |
| Number of pages | 8 |
| ISBN (Print) | 0818689919 |
| DOIs | |
| Publication status | Published - 1 Dec 1998 |
| Externally published | Yes |
| Event | Ninth International Symposium on Software Reliability Engineering - Paderborn, Germany Duration: 4 Nov 1998 → 7 Nov 1998 |
Publication series
| Name | Proceedings of the International Symposium on Software Reliability Engineering, ISSRE |
|---|---|
| ISSN (Print) | 1071-9458 |
Conference
| Conference | Ninth International Symposium on Software Reliability Engineering |
|---|---|
| Abbreviated title | ISSRE 98 |
| Country | Germany |
| City | Paderborn |
| Period | 4/11/98 → 7/11/98 |
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Testing production system programs. / Antoniou, Grigoris; Jack, Oliver.
Proceedings Ninth International Symposium on Software Reliability Engineering. IEEE, 1998. p. 214-221 (Proceedings of the International Symposium on Software Reliability Engineering, ISSRE).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
TY - GEN
T1 - Testing production system programs
AU - Antoniou, Grigoris
AU - Jack, Oliver
PY - 1998/12/1
Y1 - 1998/12/1
N2 - A production system (PS) is a forward chaining rule-based system used to build large expert systems. Testing a PS must involve the construction of a covering set of test data but it is not clear what the meaning of covering a PS is and how a test data set can be measured according to coverage. We propose a test data coverage measure for a subset for PS with well defined semantics. We use a correspondence between PS and function free first order Horn logic programs to define the declarative coverage notion and measure. We found that the coverage measure can be used to determine the coverage of the program logic of a PS as well as to automate test data generation. Unification theory is utilised to measure test data coverage and constrained inductive generation is used for test data construction.
AB - A production system (PS) is a forward chaining rule-based system used to build large expert systems. Testing a PS must involve the construction of a covering set of test data but it is not clear what the meaning of covering a PS is and how a test data set can be measured according to coverage. We propose a test data coverage measure for a subset for PS with well defined semantics. We use a correspondence between PS and function free first order Horn logic programs to define the declarative coverage notion and measure. We found that the coverage measure can be used to determine the coverage of the program logic of a PS as well as to automate test data generation. Unification theory is utilised to measure test data coverage and constrained inductive generation is used for test data construction.
UR - http://www.scopus.com/inward/record.url?scp=0032303210&partnerID=8YFLogxK
U2 - 10.1109/ISSRE.1998.730884
DO - 10.1109/ISSRE.1998.730884
M3 - Conference contribution
SN - 0818689919
T3 - Proceedings of the International Symposium on Software Reliability Engineering, ISSRE
SP - 214
EP - 221
BT - Proceedings Ninth International Symposium on Software Reliability Engineering
PB - IEEE
ER -