Exploring C# Optimization Techniques from Entry-Level to Seasoned Veteran

As with any endeavor there are always multiple ways to achieve the primary objective, this is especially the case with software development as the element of individual creativity plays a central part in the solution. Given the varying levels of experience that make up a project roster it is crucial that all players accept respectful critique of their approach and have an open mind as to the different ways to solve the stated problem. It is important to analyze the different solutions and look at the pros and cons of each option objectively to ensure all potential scenarios are covered that results in a robust and stable solution.

Sample Problem

Let us now setup a sample project to analyze how a developer might approach such given their differing levels of experience and creativity.

Project Detail: The state of California is opposing a one-time carbon tax on any individual wishing to move to the state in order to account for damage done to the environment as part of relocation. The carbon tax will be calculated based on how many miles the incoming resident's car will need to travel to reach their final destination at the rate of 15 cents per mile. To make matters worse each state (excluding California) that was entered enroute will charge a flat usage tax on using their highways and any other services as part of the relocation. The usage tax will differ according to state and will need to be obtained in order to provide a total of carbon taxes due for the relocation.

First let's establish some sample data and supporting data structures to allow for the processing of aforementioned solution:

1)  Model 'MigrantTravelInformation' to contain the data we need to analyze to make our final calculation.

2) Methods to simulate the retrieval and population of migrant information coupled with a simulated RPC (remote procedure call) method to obtain the sales and use tax for every state, for demonstration purposes we'll be using the same rate for each state and delay to simulate looking up such information from a state provided API (application programming interface).

From Good to Great with Pros and Cons In Between

One of your best weapons in the war on performance is knowing where your code is going to be slow. If you know what your code does most often, then you can write with that in mind and make sure that it's as fast as possible. In C#, this means understanding what hot spots are and how to avoid them. A hot spot is any place in your code where performance degrades severely because of the work being done there or because resources are being accessed excessively such as file input/output or accessing information over a LAN/WAN.

Solution 1: Entry-Level Simplicity

Solution 1 is probably the most straightforward and most likely is the first plan of attack that would enter a young developer's mind, while its simplicity is to be admired it leaves some optimizations on the table.

Pros:

• Simple and straightforward and thus easy to understand and maintain.

Cons:

• Contains some redundant operations that can be optimized via in-memory caching to reduce remote procedure calls (RPC).

Solution 2: Entry-Level Getting Stronger

Solution 2 is an improvement on the previous reducing the redundant RPC calls while processing the state tax and maintains the simplistic approach. Notice the usage of the Dictionary instead of a HybrdDictionary or Hashtable allowing for faster data retrieval as no boxing/unboxing of the types would be required.

Pros:

• Simple and straightforward and thus easy to understand and maintain.
• Leverage in-memory cache mechanism for optimization.

Cons:

• Single-threaded, could invoke multiple threads and parallelization should volumes be more significant.

Solution 3: Seasoned Veteran

Solution 3 is an improvement on the previous as using the Task Parallel Library provides the partitioning of the collection into units of work and scheduling the processing of such on multiple threads based on the system environment. 

Pros: 

• Parallelization of the iteration over the collection provides access to additional compute resources.
• Task Parallel Library simplifies the management of threads compared to previous capability.
• Using ParallelOptions provides for the governance of how many compute resources to allocate to the process, very flexible.

Cons: 

• Usage of multiple threads will consume more resources which may lead to bottlenecks for other processes running on the server, thus in an environment that sees high levels of concurrency this approach may be too aggressive (see ParallelOptions usage for governance of compute resources).

Solution 4: Seasoned Veteran With Unlimited Resources

Solution 4 is an improvement in terms of sheer performance as each element in the collection is processed in its own thread, however given a large collection the lack of partitioning could lead to thread exhaustion other overhead that may not scale without managing the thread count manually within code. Notice the usage of the ConcurrentDictionary as the previous Dictionary usage is not considered thread safe.

Pros:

• Provides fastest iteration of sample data.

Cons:

• Introduces additional thread overhead if given a large collection.
• Potentially consumes significant resources starving other processes of needed compute and/or memory resources.

Takeaways

The first optimization technique is to time your code. You can use a stopwatch, or you can download a timer app on your phone and set it for one second intervals. Then, when you run the code, count how many times the timer goes off during its execution.

The software developer should be able to recognize the slow and hot spots in their code, knowing how to fix them.

You should be able to identify the slow and hot spots in your code, know how to fix them, and make your code more efficient overall.

• Recognize the common slow and hot spots in your code.

• Know how to make your code more responsive by avoiding these common performance traps.

• Be able to implement techniques that will make it easier for you to understand how the CPU executes a program, including knowing about thread scheduling and thread synchronization issues.

Conclusion

At the end of the day, C# is a great language for writing software that’s fast and efficient. However, it’s important to remember that there are many factors that can impact performance. The first step towards optimizing your code is understanding where bottlenecks are likely to occur and implementing strategies that will combat them. You should also make sure you have a proper testing environment so that you can see results quickly rather than having to wait days or weeks before finding out if something works as expected!