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Let's Mainframe! Important Interview questions for a Mainframe developer

Questions asked in Mainframe interviews for a mid level experienced candidate- 1. What is checkpoint restart logic and how will you code it in your program? 2. What is file parallel processing in Cobol programs? 3. What is commit logic in programs? 4. Explain the use of Cursor. 5. Explain these abends- -305, -803,-904,-911. 6. What is real time use of GDG concept? 7. INREC FIELD ,INCLUDE COND Sort examples. 8. What is Array and how is it used, what are subscript and index? 9. What are search and search all and how are they coded? 10.Why is version control tool used? (next is how do you deploy a component from dev to prod?) 11.How do u schedule a job using job scheduling tool? 12.What is your daily task and how do u get requirement? 13.Have u worked on a project from end to end? 14.Challenges you faced while delivering a project. 15.Have you interacted with stakeholders? 16.What is SDLC process? 17.Have u ever done estimation of any requirement? 18.Difference between continue and next sentence. 19.Redefines real time examples. There are more but these are frequently asked questions- Hope it helps!

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Most common question in an interview

Challenges faced while working on java projects 1. **Memory Leaks**: One challenge I faced was identifying and fixing memory leaks in a Java application. I used profilers like VisualVM or YourKit to analyze memory usage and identify objects that were not being garbage collected properly. Then, I reviewed the code to ensure proper resource management, such as closing streams and releasing references when they were no longer needed. 2. **Concurrency Issues**: In a multi-threaded Java application, I encountered race conditions and deadlocks. To solve these issues, I carefully reviewed the code to identify critical sections and synchronized access to shared resources using locks or concurrent data structures like ConcurrentHashMap. Additionally, I used tools like Java's built-in concurrency utilities and frameworks like Akka to manage concurrency more effectively. 3. **Performance Bottlenecks**: Optimizing the performance of a Java application was another challenge. I used profilers to identify bottlenecks and hotspots in the code. Then, I applied various optimization techniques such as algorithmic improvements, caching, and tuning JVM parameters like heap size and garbage collection settings to improve overall performance. 4. **Integration with Legacy Systems**: Integrating a Java application with legacy systems using outdated technologies and protocols was challenging. I leveraged libraries like Apache Camel or Spring Integration to abstract away the complexities of communication protocols and data formats. Additionally, I wrote custom adapters and converters to bridge the gap between the modern Java application and legacy systems. 5. **Handling Big Data**: Processing and analyzing large volumes of data efficiently posed a challenge. I used frameworks like Apache Spark or Hadoop to distribute data processing tasks across multiple nodes and scale horizontally. Additionally, I optimized data processing pipe Source: chatgpt