Blogs (1) >>
ICSE 2019
Sat 25 - Fri 31 May 2019 Montreal, QC, Canada
Wed 29 May 2019 16:20 - 16:40 at Duluth - Test Selection and Prioritization Chair(s): Robert Feldt

Today, we depend on numerous large-scale services for basic operations such as email. These services, built on the basis of Continuous Integration/Continuous Deployment (CI/CD) processes, are extremely dynamic: developers continuously commit code and introduce new features, functionality and fixes. Hundreds of commits may enter the code-base in a single day. Therefore one of the most time-critical, yet resource-intensive tasks towards ensuring code-quality is effectively testing such large code-bases. This paper presents FastLane, a system that performs data-driven test minimization. FastLane uses light-weight machine-learning models built upon a rich history of test and commit logs to predict test outcomes. Tests for which we predict outcomes need not be explicitly run, thereby saving us precious test-time and resources. Our evaluation on a large-scale email and collaboration platform service shows that our techniques can save 18.04%, i.e., almost a fifth of test-time while obtaining a test outcome accuracy of 99.99%.

Wed 29 May
Times are displayed in time zone: Eastern Time (US & Canada) change

16:00 - 18:00
Test Selection and PrioritizationPapers / Software Engineering in Practice / Technical Track / Journal-First Papers at Duluth
Chair(s): Robert FeldtChalmers University of Technology
16:00
20m
Talk
Improving Test Effectiveness Using Test Executions History: An Industrial Experience ReportSEIPIndustry Program
Software Engineering in Practice
Armin NajafiConcordia University, Weiyi ShangConcordia University, Canada, Peter RigbyConcordia University, Montreal, Canada
16:20
20m
Talk
FastLane: Test Minimization for Rapidly Deployed Large-scale Online ServicesTechnical TrackIndustry Program
Technical Track
Adithya Abraham Philip, Ranjita BhagwanMicrosoft Research India, Rahul KumarMicrosoft, Chandra MaddilaMicrosoft, Nachiappan NagappanMicrosoft Research
16:40
20m
Talk
Scalable Approaches for Test Suite ReductionArtifacts AvailableArtifacts Evaluated ReusableACM SIGSOFT Distinguished Paper AwardTechnical TrackIndustry Program
Technical Track
Emilio CrucianiGran Sasso Science Institute, L'Aquila, Italy, Breno MirandaFederal University of Pernambuco, Roberto VerdecchiaGran Sasso Science Institute, Vrije Universiteit Amsterdam, Antonia BertolinoCNR-ISTI
Pre-print
17:00
20m
Talk
Using Machine Learning to Recommend Correctness Checks for Geographic Map DataSEIPIndustry Program
Software Engineering in Practice
Abhaya ParthyApple Inc., Leopold SilbersteinApple Inc., Emily KowalczykApple Inc., John Paul HighApple Inc., Adithya NagarajanApple Inc., Atif MemonApple Inc.
17:20
20m
Talk
A Framework for Checking Regression Test Selection ToolsArtifacts Evaluated ReusableTechnical Track
Technical Track
Chenguang ZhuUniversity of Texas, Austin, Owolabi LegunsenUniversity of Illinois at Urbana-Champaign, August ShiUniversity of Illinois at Urbana-Champaign, Milos GligoricUniversity of Texas at Austin
17:40
10m
Talk
ConTesa: Directed Test Suite Augmentation for Concurrent SoftwareJournal-First
Journal-First Papers
Tingting YuUniversity of Kentucky, Zunchen Huang, Chao WangUSC
17:50
10m
Talk
Discussion Period
Papers