Milojković, Nevena (June 2017). Improving the Precision of Type Inference Algorithms with Lightweight Heuristics (Unpublished). In: Seminar Series on Advanced Techniques and Tools for Software Evolution SATT. Madrid, Spain. 07.-09. Juni 2017.
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Dynamically-typed languages allow faster software development by not posing the type constraints. Static type information facilitates program comprehension and software maintenance. Type inference algorithms attempt to reconstruct the type information from the code, yet they suffer from the problem of false positives or false negatives. The use of complex type inference algorithms is questionable during the development phase, due to their performance costs. Instead, we propose lightweight heuristics to improve simple type inference algorithms and, at the same time, preserve their swiftness.
Item Type: |
Conference or Workshop Item (Paper) |
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Division/Institute: |
08 Faculty of Science > Institute of Computer Science (INF) > Software Composition Group (SCG) |
Language: |
English |
Submitter: |
Oscar Nierstrasz |
Date Deposited: |
11 Apr 2018 11:15 |
Last Modified: |
23 Nov 2019 20:33 |
BORIS DOI: |
10.7892/boris.113137 |
URI: |
https://boris.unibe.ch/id/eprint/113137 |
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