8 Tips for Testing and Debugging Data

Collecting and inputting the correct data may not always guarantee accuracy in output. Whatever you feed into the system determines the output, hence, the common statement, garbage in, garbage out (GIGO). Ensuring that your data is accurate and consistent requires the process of data testing and debugging.

What is data testing and debugging?

Your business receives large amounts of data from external sources, often beyond your control. The data could have errors that may not be detected during processing but will lead to inaccurate output and impair the decision-making process. To avoid this challenge for your business, it is important to conduct data testing and debugging, the process that helps to identify and correct any errors in input data.

Here are some tips to help you test and debug your data for accurate results.

Use of error-detection tools

You don’t need to be a programmer to detect errors in the data flowing in and out of your business. Make use of the various error-detection tools, such as PURIFY, which can help you capture memory errors or memory leaks. Memory errors compromise the accuracy of the data by creating gaps in the data due to memory losses.

Group the bug into similar classes 

You may capture numerous errors. If this happens, it is advisable to group the errors into classes of similar bugs. This is also known as bug clustering. After grouping the bugs, you can examine only one bug from each group. The bug you test represents the rest of the group. After fixing the selected bug, you will have automatically solved the rest from its group. 

Use the problem simplification method

Code simplification is one of the best ways for testing and debugging your data. This process helps to gradually eliminate portions of the code until you identify the error. Even when the input data is large, you should repeatedly split the data into small parts to expose the bug. 

Use backtracking

Backtracking is the process in which programmers start checking the problem from the point of occurrence backward. This technique will help in detecting what caused the problem and finally correcting the cause. 

Try binary search

You can apply this strategy where backtracking has failed. It is a divide-and-conquer approach that quickly identifies the bug. If you have a large piece of code, you should place a check halfway. If the error is not on the first half, then automatically, it is on the other half. Repeat the process on the unchecked half until you find the bug.

Use debuggers

A debugger replaces manual instrumentation. It sets breakpoints in the program, stepping into and over functions, inspects the memory contents at selected points, and watching program expressions will give all the needed information with small, simple to read log files.

Use the instrument program with Assertions. 

Assertions will help you check if the program has the properties that your code needs. The program will stop immediately if the Assertions fail. The point where the program stops is closer to the cause of the problem. With the use of Assertions, you will quickly get the problem.  

Use of instrument program to log information. 

This method is applicable when print statements are applied. It will be of great help when a large volume of logged data is inserted. You will need automated scripts to sift through the data. The scripts will report the relevant parts in a more compact format. 

If testing and debugging data still sounds overwhelming for your startup, or you just want to free up your time for other important duties in your firm, you can partner with Helios for professional data management services. If you need any help with your data, please contact us today.



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