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Showing posts with the label Defects in Software development

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Best Practices for Handling Duplicate Elements in Python Lists

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Here are three awesome ways that you can use to remove duplicates in a list. These are helpful in resolving your data analytics solutions.  01. Using a Set Convert the list into a set , which automatically removes duplicates due to its unique element nature, and then convert the set back to a list. Solution: original_list = [2, 4, 6, 2, 8, 6, 10] unique_list = list(set(original_list)) 02. Using a Loop Iterate through the original list and append elements to a new list only if they haven't been added before. Solution: original_list = [2, 4, 6, 2, 8, 6, 10] unique_list = [] for item in original_list:     if item not in unique_list:         unique_list.append(item) 03. Using List Comprehension Create a new list using a list comprehension that includes only the elements not already present in the new list. Solution: original_list = [2, 4, 6, 2, 8, 6, 10] unique_list = [] [unique_list.append(item) for item in original_list if item not in unique_list] All three methods will result in uni

2 Root Causes for Defects in Software Development

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Miscommunication Miscommunication is a common factor, which can be defined as inaccurate statements or information missing that is required for the action to be done successfully. This miscommunication ends up in the documentation or verbal communication that occurs. Instead of spending time to make sure everything is accurate, statements are made that are untrue or unclear. When this occurs at the beginning of the change process the bad information continues down through the process. Decisions and design are made based on it.  At some point it gets realized that the information is bad and a defect is created. In the common project process that could be classified as linear, most defects are not found until in the later phase of development and unit testing has started. Process Defects This would be similar to a defect a machine makes in manufacturing. Even though the input is accurate, the process itself causes a defect to occur.  The original process was prone to defects no matt