TY - GEN
T1 - Synthesis of LTL formulas from natural language texts
T2 - 26th International Symposium on Temporal Representation and Reasoning, TIME 2019
AU - Brunello, Andrea
AU - Montanari, Angelo
AU - Reynolds, Mark
PY - 2019/10/1
Y1 - 2019/10/1
N2 - Linear temporal logic (LTL) is commonly used in model checking tasks; moreover, it is well-suited for the formalization of technical requirements. However, the correct specification and interpretation of temporal logic formulas require a strong mathematical background and can hardly be done by domain experts, who, instead, tend to rely on a natural language description of the intended system behaviour. In such situations, a system that is able to automatically translate English sentences into LTL formulas, and vice versa, would be of great help. While the task of rendering an LTL formula into a more readable English sentence may be carried out in a relatively easy way by properly parsing the formula, the converse is still an open problem, due to the inherent difficulty of interpreting free, natural language texts. Although several partial solutions have been proposed in the past, the literature still lacks a critical assessment of the work done. We address such a shortcoming, presenting the current state of the art for what concerns the English-to-LTL translation problem, and outlining some possible research directions.
AB - Linear temporal logic (LTL) is commonly used in model checking tasks; moreover, it is well-suited for the formalization of technical requirements. However, the correct specification and interpretation of temporal logic formulas require a strong mathematical background and can hardly be done by domain experts, who, instead, tend to rely on a natural language description of the intended system behaviour. In such situations, a system that is able to automatically translate English sentences into LTL formulas, and vice versa, would be of great help. While the task of rendering an LTL formula into a more readable English sentence may be carried out in a relatively easy way by properly parsing the formula, the converse is still an open problem, due to the inherent difficulty of interpreting free, natural language texts. Although several partial solutions have been proposed in the past, the literature still lacks a critical assessment of the work done. We address such a shortcoming, presenting the current state of the art for what concerns the English-to-LTL translation problem, and outlining some possible research directions.
KW - Evolutionary algorithms
KW - Machine learning
KW - Natural language processing
KW - Semantic parsing
KW - Temporal logic
UR - http://www.scopus.com/inward/record.url?scp=85073529846&partnerID=8YFLogxK
UR - http://ulrichsweb.serialssolutions.com/title/1572568507675/706844
U2 - 10.4230/LIPIcs.TIME.2019.17
DO - 10.4230/LIPIcs.TIME.2019.17
M3 - Conference paper
AN - SCOPUS:85073529846
T3 - Leibniz International Proceedings in Informatics, LIPIcs
SP - 171
EP - 1719
BT - Leibniz International Proceedings in Informatics, LIPIcs
A2 - Gamper, Johann
A2 - Pinchinat, Sophie
A2 - Sciavicco, Guido
PB - Schloss Dagstuhl- Leibniz-Zentrum fur Informatik GmbH, Dagstuhl Publishing
Y2 - 16 October 2019 through 19 October 2019
ER -