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SSBSE 2026: Symposium on Search-Based Software Engineering

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Submission Date:
2026-02-20
Notification Date:
2026-03-28
Conference Date:
2026-07-06
Location:
Montreal, Quebec, Canada
Years:
18
ICORE: B   Viewed: 728   Tracked: 0   Attend: 0

Conference Partner Index (CP-I)

57.4 / 100
Ranked #701 of 5,684 conferences · Top 13%

#79 of 247 in Software Engineering

Academic recognition (35%)
72
Submission selectivity (20%) No data - scored at the neutral baseline of 50 —
Editions held (20%)
79
Community attention (10%)
10
Public record completeness (15%)
35

Inputs used: Listed as ICORE B · Editions on record: 18 · Researchers who opened this page in the past 24 months: 3

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 80% - 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 2026-09-24

Call For Papers

SSBSE 2026 (Symposium on Search-Based Software Engineering) is a ICORE B conference held in Montreal, Quebec, Canada on 2026-07-06. The paper submission deadline is 2026-02-20. Acceptance notifications are sent on 2026-03-28.

The 18th Symposium on Search-Based Software Engineering (SSBSE 2026) invites high-quality submissions that push the boundaries of research in Search-Based Software Engineering (SBSE). This year, we aim to spotlight the transformative role of AI and optimization techniques in software engineering, while continuing to welcome innovative contributions across all areas of SBSE. We encourage submissions that: Apply SBSE techniques to novel and emerging problems, including those where SBSE has not been traditionally applied. Provide theoretical insights into search algorithms tailored for software engineering challenges. Offer rigorous empirical evaluations of SBSE methods, with reproducible experiments and datasets. Share industrial experiences, detailing real-world applications, challenges, and lessons learned from deploying SBSE techniques. SSBSE embraces a wide spectrum of search methods, from exact operational research techniques to nature-inspired algorithms (e.g., evolutionary algorithms, simulated annealing, and swarm intelligence). We particularly welcome papers that integrate SBSE with advancements in artificial intelligence, machine learning, and other cutting-edge technologies. Research papers must be of up to 15 pages, including all text, figures, references, and appendices.
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