A random forest learning-to-rank model using past co-change history and code features ranks co-changed methods with NDCG@5 of 0.84, but its edge over a historical frequency baseline is only 4.7%.
Comparative Studies of 10 Programming Languages within 10 Diverse Criteria -- a Team 7 COMP6411-S10 Term Report
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
abstract
There are many programming languages in the world today.Each language has their advantage and disavantage. In this paper, we will discuss ten programming languages: C++, C#, Java, Groovy, JavaScript, PHP, Schalar, Scheme, Haskell and AspectJ. We summarize and compare these ten languages on ten different criterion. For example, Default more secure programming practices, Web applications development, OO-based abstraction and etc. At the end, we will give our conclusion that which languages are suitable and which are not for using in some cases. We will also provide evidence and our analysis on why some language are better than other or have advantages over the other on some criterion.
citation-role summary
background 1
citation-polarity summary
fields
cs.SE 1years
2024 1verdicts
CONDITIONAL 1roles
background 1polarities
unclear 1representative citing papers
citing papers explorer
-
Enhancing Software Maintenance: A Learning to Rank Approach for Co-changed Method Identification
A random forest learning-to-rank model using past co-change history and code features ranks co-changed methods with NDCG@5 of 0.84, but its edge over a historical frequency baseline is only 4.7%.