| dc.contributor |
Solar-Lezama, Armando |
|
| dc.contributor |
Andreas, Jacob |
|
| dc.contributor |
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science |
|
| dc.creator |
Gu, Alex |
|
| dc.date |
2022-08-29T16:14:32Z |
|
| dc.date |
2022-08-29T16:14:32Z |
|
| dc.date |
2022-05 |
|
| dc.date |
2022-05-27T16:19:16.985Z |
|
| dc.date.accessioned |
2023-02-17T19:52:44Z |
|
| dc.date.available |
2023-02-17T19:52:44Z |
|
| dc.identifier |
https://hdl.handle.net/1721.1/144829 |
|
| dc.identifier.uri |
http://localhost:8080/xmlui/handle/CUHPOERS/242038 |
|
| dc.description |
Program synthesis has traditionally excelled in tasks with precise specifications such as input-output examples and formal constraints by using structured and algorithmic approaches based on enumerative search and type inference. However, traditional synthesis techniques have no mechanism of incorporating real-world knowledge, which is commonplace in software engineering. Motivated by this, we introduce a new synthesis task known as specification reification: synthesizing concrete realizations of vague, high-level application specifications. We focus on a specific instance of this: generating object models from natural language application descriptions. Towards this goal, we present three approaches for object model synthesis that leverage domain knowledge from the GPT-3 language model. In addition, we design a scoring metric to evaluate the success of synthesized object models on seven sample tasks such as classroom management and pet store applications. We demonstrate that our language-model-based synthesizers generate object models that are comparable in quality to human-generated ones. |
|
| dc.description |
M.Eng. |
|
| dc.format |
application/pdf |
|
| dc.publisher |
Massachusetts Institute of Technology |
|
| dc.rights |
In Copyright - Educational Use Permitted |
|
| dc.rights |
Copyright MIT |
|
| dc.rights |
http://rightsstatements.org/page/InC-EDU/1.0/ |
|
| dc.title |
Synthesizing Object Models from Natural Language Specifications |
|
| dc.type |
Thesis |
|