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"Detecting Hidden Failures of DBMS: A Comprehensive Metamorphic Relatio" by Matthew Siu Hin Tang, T. H. Tse et al.

The testing of large databases faces the test oracle problem, namely, that it is difficult to verify execution results against expected outcomes. Rigger and Su applied metamorphic testing through query partitioning and ternary logic partitioning techniques to alleviate the challenge. In Part (A) of our project, we conduct an in-depth investigation and have identified a gap between the two techniques. We propose a disjoint partitioning approach to address it. In Part (B), we conduct a comprehensive investigation into the metamorphic testing of DBMS by comparing disjoint partitioning with metamorphic relation output patterns (MROPs) by Segura et al. We propose an exhaustive collection of MROPs for DBMS. To the best of our knowledge, this is the first project to integrate in-depth and comprehensive approaches to tackle the diverse challenges in DBMS testing. In Part (C), we conduct an empirical case study of their applications to OceanBase, the DBMS associated with the world's fastes ....

Etamorphic Relation Output Pattern , Metamorphic Testing , Test Oracle ,

"A Disjoint-Partitioning Approach to Enhancing Metamorphic Testing of D" by Matthew Siu-Hin Tang, T. H. Tse et al.

Owing to big data, DBMS testing faces the oracle problem, that is, it is difficult to verify execution results against expected outcomes. Rigger and Su applied metamorphic testing to alleviate the challenge. We propose a disjoint-partitioning approach to extend their work. We have conducted an empirical case study on OceanBase, the DBMS associated with the world's fastest online transaction processing system. Even though Ocean- Base has been extensively tested and widely used in the industry, we have unveiled various hidden failures and crashes. ....

Metamorphic Testing , Test Oracle ,

The First Annual Recap From JPA Buddy

In this article, we decided to share a short story behind JPA Buddy, its achievements in 2021, and plans for 2022. ....

Timestamp Datetime , Simon Martinelli , Thorben Janssen , Community Research , Jmix Studio , Spring Data , Eugen Paraschiv , Vlad Mihalcea , Happy New , Intellij Idea ,

SKP's Java/Java EE Gotchas: Clustered Nodes Issue Using Apache Lucene 5.4.y


SKP s Java/Java EE Gotchas: Clustered Nodes Issue Using Apache Lucene 5.4.y
Different Indexes / Results Using Same Data on Different Machines [Clustered Nodes] [Hibernate Search 5.5.x / Apache Lucene 5.4.y]
by
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So, We just spent about 28+ days using Stack Overflow and Hibernate Search Forums as also various other resources to FIX the strangest of issues using Hibernate Search and Apache Lucene. The right help or pointer came from the Hibernate Search Committers/Creators (Official Forums). Thanks a lot to
sanne.grinovero .
Issue Description: In a (non-replicated) clustered environment, if the Indexing by Lucene or Hibernate Search is done from the Same Database (Instance) using the Same Data the Results obtained are Different on Different Nodes. In other words, the Same Data from the Same Database Instance Indexed using the Same Code Yields a Different Result Set for the Same ....

Stack Overflow , Hibernate Search Forums , Hibernate Search , Official Forums , Hibernate 5 , Core Java , Clustered Index , Root Cause Analysis , அடுக்கு ஓவர்‌ஃப்லோ , உறக்கநிலை தேடல் மன்றங்கள் , உறக்கநிலை தேடல் , அதிகாரி மன்றங்கள் , கோர் ஜாவா , வேர் காரணம் பகுப்பாய்வு ,