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Memory Utilization & Garbage Collection Analysis

Memory Utilization & Garbage Collection Analysis The goal should be to optimize garbage collection (GC) in such way that its impact on application response time or CPU usage is minimized. Monitor the utilization of different memory pools (young, survivor and old). Memory shortage is the number-one reason for the increased GC activity The young generation should be big enough to ensure that all temporary objects die there If overall memory utilization is growing continuously despite garbage collection, it is an indication of memory leak and requires heap analysis Monitor the churn rate (number of object allocation per interval) at the younger generation. The high number of young collection can cause high response time. It can cause unnecessarily copying of objects from young generation to old generation Free tools that can be used for GC analysis are: JConsole, jStat, Java VisualVM, JRockit Mission Control, verbose:gc flag of the JVM A high GC activity generally h

Checklist for Designing Better Performance Test Scripts

Checklist for Designing Better Performance Test Scripts Make sure the script doesn’t contain incorrect or extraneous URLs. The urls specified should be in correct sequence. It might be possible while recording, script writer would have gone to his / her popular website. It can be validated by using test tool’s “playback” feature to confirm what the script actually does. Identify all dynamic data (as the response from server) present in a script and correlate it. Usually it can be found by recording scripts two times and making comparisons between them. Parameterize scripts to support dynamic data set. In presence of dynamic data, every simulated user exercises the exact same path but avoids responses from the cache and exercises database interactions properly. Use proper checkpoint(s) / assertion(s) for all steps involved in the transaction. Absence of checkpoint might result in better response time when a page is not getting downloaded completely / correctl

DW Testing - Test Ideas

DW Testing - Test Ideas Data Completeness Is all expected data being loaded? Is your DW handling updates over time? Is delta pull being tested other than full? What happens when error occurs during the ETL process? Is application able to recover after error? Does the ETL have the ability to resume from the point of failure? Are all data source being considered for testing? Is row count from source to target as per the requirements? Is there any extra data present in the target system? Is unique values of key fields between source data and target data same? Is data truncating before putting into datawarehouse? For example - Source Column width might be having 30 characters, whereas destination might have only 20. Is boundaries of each field been tested? For example, for a decimal(3) field include values of -99 and 999, and for date fields include the entire range of dates expected. Data Transformation Is all data being transformed correctly accordingly to business