Modeling readability to improve unit tests

@article{Daka2015ModelingRT,
  title={Modeling readability to improve unit tests},
  author={Ermira Daka and Jos{\'e} Campos and Gordon Fraser and Jonathan Dorn and Westley Weimer},
  journal={Proceedings of the 2015 10th Joint Meeting on Foundations of Software Engineering},
  year={2015}
}
Writing good unit tests can be tedious and error prone, but even once they are written, the job is not done: Developers need to reason about unit tests throughout software development and evolution, in order to diagnose test failures, maintain the tests, and to understand code written by other developers. Unreadable tests are more difficult to maintain and lose some of their value to developers. To overcome this problem, we propose a domain-specific model of unit test readability based on human… 
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Improving Readability of Automatically Generated Unit Tests
TLDR
This work proposes a domain-specific model of unit test readability based on human judgments, and uses this model to guide automated unit test generation, which can automatically generate test cases with improved readability with the overall objective of reducing the effort for developers to understand these test cases.
Improving readability in automatic unit test generation
TLDR
A domain-specific model of unit test readability, based on human judgements is used to augment automated unit test generation to produce test suites with both high coverage and improved readability.
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TLDR
It is suggested that developers tend to neglect the readability of test cases and that automatically generated test cases are generally even less readable than manually written ones.
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TLDR
An empirical study in which participants were presented with an automatically generated or manually written failing test, and were asked to identify and fix the cause of the failure, found developers to be equally effective with manually written and automatically generated tests.
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TLDR
An empirical study with 20 real developers indicates that automatically generated tests can be a great help for identifying faults during maintenance and developers may integrate generated test suites into the project at any stage.
The impact of test case summaries on bug fixing performance: an empirical investigation
TLDR
An approach which automatically generates test case summaries of the portion of code exercised by each individual test, thereby improving understandability, is proposed, which can complement the current techniques around automated unit test generation or search-based techniques designed to generate a possibly minimal set of test cases.
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TLDR
A novel approach - UnitTestScribe - that combines static analysis, natural language processing, backward slicing, and code summarization techniques to automatically generate natural language documentation of unit test cases is proposed.
Generating Readable Unit Tests for Guava
TLDR
This work integrates a further optimization target based on a model of test readability learned from human annotation data that produces more readable unit tests without loss of coverage.
The impact of test case summaries on bug fixing performance: An empirical investigation
TLDR
An approach which automatically generates test case summaries of the portion of code exercised by each individual test, thereby improving understandability, is proposed, which can complement the current techniques around automated unit test generation or searchbased techniques designed to generate a possibly minimal set of test cases.
The impact of test case summaries on bug fixing performance: An empirical investigation
TLDR
An approach which automatically generates test case summaries of the portion of code exercised by each individual test, thereby improving understandability, is proposed, which can complement the current techniques around automated unit test generation or searchbased techniques designed to generate a possibly minimal set of test cases.
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