Notes, abstracts, papers, exams and problems of Computers

1. Make quality #1

   Quality must be quantified and mechanisms put into place to motivate its achievement. Defining quality commensurate with the project at hand is important but is not easily done at the outset of a project.

2. Involve the customer

   Techniques that have been demonstrated to increase quality include involving the customer, prototyping, simplifying design, conducting inspections, and hiring the best people. This principle is mostly redundant.

3. Give products to customers early

   No matter how hard you try to learn users' needs during the requirements phase, the most effective way to determine real needs is to give users a product and let them play with it.

4. Determine the problem before writing the requirements

   When faced with what they believe is

1.  A network technician is configuring port Security on a LAN switch interface. The security policy requires host MAC Addresses to be learned dynamically, stored in the address table, and Saved to the switch running configuration. Which command does the technician Need to add to the following configuration to implement this Policy? Switch(config)# interface fa0/1 
   Switch(config-if)# switchport mode access 
   Switch(config-if)# switchport port-security

·Switch(config-if)# switchport port-security mac-address sticky

2. On which switch interface would an Administrator configure an IP address so that the switch can be managed Remotely?

·VLAN 1

3. Refer to the exhibit. Match the packets with Their destination IP address to the exiting interface on the router.

AI Meets AI: Leveraging Query Executions to Improve Index Recommendations

How artificial intelligence (AI) can benefit automated indexing (AI)?: Comparing the execution cost of two plans (different index configurations of same query) is key for index tuning. Instead of using optimizer’s estimates for such comparison, formulating it as a classification task in machine learning results in significantly higher accuracy.

MOTIVATION:

• Being able to fully automate index recommendation and implementation is a significant value-add for improving query execution cost.
• Requirement: creating or dropping indexes should not cause significant query performance regressions - users enforce a no query regression constraint.
• Using the optimizer’s estimates to