Passed or Failed?
This lesson is about how to know, whether the software passed or failed the test. You will understand why this can be quite difficult to say.
Learning Objectives
You will understand the concept of oracles in software testing and the challenges and limitations associated with them. It emphasizes the importance of making judgments when determining if a program passed or failed a test and the fallibility of heuristic oracles. The video also addresses the implications of these challenges for automating tests.
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Core Topics and Takeaways
Passed or Failed?
Specification of the expected result
Specification of the test environment
Specified and unspecified test conditions
Inputs and outputs
Heuristics
Video Highlights
Topics | Key Concepts | Video Location |
---|---|---|
The lecture discusses the concept of Oracles in software testing and the challenges in determining whether a program has passed or failed a test. |
| 00:01 |
Test specifications typically include input conditions and expected results, but rarely specify details such as versions of memory resident programs or system configuration. |
| 01:47 |
The section discusses the challenges of reproducing bugs and the limitations of monitoring all relevant aspects in testing. |
| 03:33 |
Heuristics are fallible but useful decision support tools, and oracles are heuristics that can lead to errors in test evaluation. |
| 05:23 |
Learning Highlights
In this section you have learned whether a program has passed or failed a test. The main reading, "Testing Without a Map" by Michael Bolton, introduces the concept of Oracle heuristics.
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Recommended reading for this chapter is Testing Without a Map. You can find it here.
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Traditionally, oracles are tools to assess whether a program passed or failed, but the paper argues that real oracles are challenging to achieve. The complexity arises from the variability in reference programs, making comparisons difficult. The discussion emphasizes the importance of judgments in testing and the fallibility of test data. Doug Hoffman's insights on monitoring relevant aspects and the limitations of heuristics in automation are highlighted, stressing the need for a nuanced approach.
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