期刊
出版社
IEEE
DOI: 10.1109/ICSE-NIER.2017.7
关键词
program synthesis; pruning; input generation
资金
- National Science Foundation [1645136, 1526253, 1526652]
- Direct For Computer & Info Scie & Enginr
- Division Of Computer and Network Systems [1526253] Funding Source: National Science Foundation
- Division of Computing and Communication Foundations
- Direct For Computer & Info Scie & Enginr [1564162, 1563797] Funding Source: National Science Foundation
- Division of Computing and Communication Foundations
- Direct For Computer & Info Scie & Enginr [1645136, 1526652] Funding Source: National Science Foundation
Program synthesis is succeeding in supporting the generation of programs within increasingly complex domains. The use of weaker specifications, such as those consisting of input/output examples or test cases, has helped to fuel the success of program synthesis by lowering adoption barriers. Yet, employing weaker specifications has the side effect of generating a potentially large number of candidate programs. This was not a problem for simpler and smaller program domains, but it is becoming evident that differentiating among many synthesized programs is a challenge that needs addressing. We sketch an approach to mitigate this challenge, requiring less effort from the user while automatically identifying inputs that can differentiate clusters of synthesized programs. The approach has the potential to more cost-effectively narrow the space of candidate programs in a range of synthesis applications.
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