Manual Testing Filter Failure With Multiple Fields

by SLV Team 51 views
Manual Testing Filter Failure with Multiple Fields

Hey guys! Let's dive into a tricky issue we've encountered during manual testing. It looks like our filter functionality, specifically when using multiple fields, isn't quite behaving as expected. This can be a real headache, especially when you're trying to narrow down results based on several criteria. So, let's break down the problem, understand why it's happening, and figure out how to fix it.

The Issue: Multiple Field Filtering Problems

In essence, the problem arises when we attempt to filter data using multiple fields in our application. Imagine you're trying to find a specific entry by filtering for both the status and the urgency level. You might expect to get a precise result, but instead, the filter seems to stumble. Let's look at a concrete example to illustrate this.

Example Scenario

According to our Developer Guide, one of the manual testing steps involves the test case "filter s/APPLIED t/urgent". Now, when we actually run this command, it fails. This is a pretty significant issue because it's documented as a valid test case, implying that it should work. When a documented feature fails, it raises a few questions:

  • Is this a bug in the functionality itself?
  • Is there an error in the documentation?
  • Or is there a misunderstanding of how the feature is intended to be used?

To make things clearer, let's take a look at the screenshots provided. They visually demonstrate the context of the issue, helping us to see exactly what's going wrong and where.

Visualizing the Problem

We have two images that highlight the problem. The first image shows a snippet of the filter input, and the second displays the outcome or the lack thereof. By examining these visuals, we can confirm that the expected filtering behavior isn't occurring. The application isn't correctly processing multiple filter criteria, which leads to inaccurate or incomplete results.

Why is this a Medium Severity Functionality Bug?

This issue has been labeled as severity.Medium and type.FunctionalityBug. Let's unpack that a bit:

  • Severity.Medium: This means the bug impacts a significant feature of the application, but there might be workarounds available. It's not a showstopper, but it definitely needs to be addressed.
  • Type.FunctionalityBug: This clearly indicates that a core function of the application – in this case, filtering – isn't working as it should.

When a core function like filtering malfunctions, it directly affects the user experience. Imagine trying to manage a large dataset without the ability to effectively filter and sort. It would be a nightmare, right? So, while there might be alternative ways to find the information, the broken filter adds unnecessary friction.

Digging Deeper: Possible Causes and Considerations

Okay, so we know we have a problem. Now, let's put on our detective hats and explore some potential causes behind this multiple field filtering failure.

1. Input Parsing Issues

One possibility is that the application isn't correctly parsing the input when multiple filter criteria are provided. The filter command s/APPLIED t/urgent includes two conditions: status (s) and urgency (t). If the parsing logic isn't designed to handle multiple conditions simultaneously, it might only process one condition or misinterpret the entire input. This could happen due to:

  • Incorrect delimiters: The application might be expecting a different separator between the filter conditions.
  • Order of operations: The parsing logic might be applying the filters in the wrong order, leading to unexpected results.
  • Missing handling for multiple parameters: The code might simply not be written to handle more than one filter parameter at a time.

2. Logic Errors in the Filtering Algorithm

Even if the input is parsed correctly, there might be logical errors within the filtering algorithm itself. For instance, the code might be using an incorrect logical operator (like OR instead of AND) when combining the filter conditions. Imagine you're filtering for items that are both "APPLIED" and "urgent". If the logic uses OR, it will return items that are either "APPLIED" or "urgent", which is not the desired result. Other potential issues include:

  • Incorrect field comparisons: The code might be comparing the wrong fields or using the wrong comparison operators.
  • Data type mismatches: If the filter criteria and the data being filtered have different data types, the comparison might fail.
  • Edge case handling: The algorithm might not be handling edge cases, such as empty filter values or unexpected input formats.

3. Data Structure and Database Queries

The way data is structured and queried in the backend can also impact the filtering process. If the data is not indexed properly, or if the database queries are not optimized for multiple filter conditions, the filtering operation can become inefficient or even fail. Some specific things to consider are:

  • Database schema design: The database schema might not be optimized for the types of queries being performed.
  • Indexing: Missing or incorrect indexes can slow down query performance.
  • Query construction: The SQL queries generated by the application might be inefficient or incorrect.

4. Documentation Bug or Intended Behavior?

Let's not forget the possibility that this might not be a bug at all, but rather a documentation issue. The Developer Guide states that the filter s/APPLIED t/urgent command should work. But what if it was added by mistake, or if the functionality was changed without updating the documentation? This is why it's crucial to clarify whether this behavior is intended or not. If it's intended, then the documentation needs to be updated. If it's not, then we're back to fixing a bug.

Steps to Resolve the Issue

So, how do we tackle this problem? Here’s a structured approach we can take:

1. Clarify Intended Behavior

The first step is to determine whether the documented behavior is actually the intended behavior. We need to reach out to the developers or product owners to confirm if multiple field filtering should work as described in the Developer Guide. This will help us avoid wasting time fixing something that was never meant to work in the first place.

2. Reproduce the Bug Consistently

Before we can fix anything, we need to be able to reliably reproduce the bug. This means following the steps outlined in the test case (filter s/APPLIED t/urgent) and ensuring that the failure occurs consistently. If the bug is intermittent, it will be much harder to diagnose and fix.

3. Debug and Isolate the Root Cause

Once we can reproduce the bug, it's time to dive into the code and figure out what's going wrong. This might involve:

  • Reviewing the input parsing logic: Check how the application is parsing the filter command and ensure it can handle multiple conditions.
  • Examining the filtering algorithm: Step through the code that performs the filtering to see if there are any logical errors.
  • Analyzing database queries: Look at the SQL queries being generated to ensure they are correct and efficient.
  • Using debugging tools: Employ debuggers and log statements to trace the execution flow and identify the source of the problem.

4. Implement a Fix

Once we've identified the root cause, we can implement a fix. This might involve modifying the input parsing logic, correcting the filtering algorithm, optimizing database queries, or a combination of these. The fix should be carefully tested to ensure it resolves the bug without introducing any new issues.

5. Test the Solution Thoroughly

After implementing the fix, we need to test it thoroughly. This should include:

  • Running the original test case: Make sure the filter s/APPLIED t/urgent command now works correctly.
  • Testing other multiple field filter combinations: Try different combinations of filter criteria to ensure the fix is robust.
  • Performing regression testing: Run existing tests to ensure the fix hasn't broken any other functionality.

6. Update Documentation (If Necessary)

Finally, if the intended behavior was indeed a documentation bug, we need to update the Developer Guide to reflect the actual functionality. This will prevent future confusion and ensure that users have accurate information.

Conclusion

So, there you have it! The manual testing filter failure with multiple fields is a tricky issue, but by systematically investigating the potential causes and following a structured approach to resolution, we can get to the bottom of it. Remember, clear communication, thorough testing, and attention to detail are key to squashing bugs effectively. Let's get this filter working smoothly, guys!