Conference Information

Scala 2018: ACM SIGPLAN Symposium on Scala

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Submission Date:
2018-06-13 Extended
Notification Date:
2018-07-13
Conference Date:
2018-09-28
Location:
St. Louis, Missouri, USA
Years:
9
Viewed: 12035   Tracked: 0   Attend: 0

Conference Partner Index (CP-I)

44.5 / 100
Ranked #3,020 of 5,689 conferences · Top 54%
Academic recognition (35%) No data - scored at the neutral baseline of 50 —
Submission selectivity (20%) No data - scored at the neutral baseline of 50 —
Editions held (20%)
62
Community attention (10%)
8
Public record completeness (15%)
25

Inputs used: Editions on record: 9 · Researchers who opened this page in the past 24 months: 2

Missing from the public record: Historical acceptance rates (+4.5) · Past editions (+3.0) · Best-paper records (+2.3)
Organizers can add these from this page after claiming the conference; scores are recomputed nightly. How to raise this score

Confidence 45% - the share of the score backed by observed data rather than the neutral baseline. How this score is calculated · Browse the ranking · Algorithm version 1.1 · Computed 2026-10-01

Call For Papers

Scala 2018 (ACM SIGPLAN Symposium on Scala) is an academic conference held in St. Louis, Missouri, USA on 2018-09-28. The paper submission deadline is 2018-06-13 (extended). Acceptance notifications are sent on 2018-07-13.

We seek submissions on all topics related to Scala, including (but not limited to): Language design and implementation – language extensions, optimization, and performance evaluation. Library design and implementation patterns for extending Scala – stand-alone Scala libraries, embedded domain-specific languages, combining language features, generic and meta-programming. Formal techniques for Scala-like programs – formalizations of the language, type system, and semantics, formalizing proposed language extensions and variants, dependent object types, type and effect systems. Concurrent and distributed programming – libraries, frameworks, language extensions, programming models, performance evaluation, experimental results. Big data and machine learning libraries and applications using the Scala programming language. Safety and reliability – pluggable type systems, contracts, static analysis and verification, runtime monitoring. Interoperability with other languages and runtimes, such as JavaScript, Java 8 (lambdas), Graal and others. Tools – development environments, debuggers, refactoring tools, testing frameworks. Case studies, experience reports, and pearls
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