A Model for Measuring Software Understandability

Lin, Ja‐Chen; Wu, Kuo-Chiang

doi:10.1109/cit.2006.13

Cited by 14 publications

(3 citation statements)

References 10 publications

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“…Besides, manual manipulations might affect code understandability as well. Understandability is defined as to what extent the code allows developers to understand its purpose [11][20] [22]. Readable code is not meant to be understood more easily.…”

Section: Discussionmentioning

confidence: 99%

An Enhanced Data Augmentation Approach to Support Multi-Class Code Readability Classification

Mi¹,

Yang²,

Wu³

et al. 2022

Proceedings of the 34th International Conference on Software Engineering and Knowledge Engineering

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Context: Code readability plays a critical role in software maintenance and evolvement, where a metric for classifying code readability levels is both applicable and desired. However, most prior research has treated code readability classification as a binary classification task due to the lack of labeled data. Objective: To support the training of multi-class code readability classification models, we propose an enhanced data augmentation approach. Method: The approach includes the use of domainspecific data transformation and GAN-based data augmentation. By virtue of this augmentation approach, we could generate sufficient readability data and well train a multi-class code readability model. Result: A series of experiments are conducted to evaluate our augmentation approach. The experimental results show that a state-of-the-art multi-class code readability classification accuracy of 68.0% is reached with a significant improvement of 6.3% compared to only using the original data. Conclusion: As an innovative work of proposing multi-class code readability classification and an enhanced code readability data augmentation approach, our method is proved to be effective.

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Section: Discussionmentioning

confidence: 99%

An Enhanced Data Augmentation Approach to Support Multi-Class Code Readability Classification

Mi¹,

Yang²,

Wu³

et al. 2022

Proceedings of the 34th International Conference on Software Engineering and Knowledge Engineering

View full text Add to dashboard Cite

show abstract

“…To better understand a piece of code, legibility is one of the main factors to take under control, since if code is harder to read, it could be harder to understand [1]. Code understanding requires building high-level abstractions from code statements or visualizations or models [20,21]. However, also readable code could be difficult to be understand [7].…”

Section: Related Workmentioning

confidence: 99%

Does Cyclomatic or Cognitive Complexity Better Represents Code Understandability? An Empirical Investigation on the Developers Perception

Lenarduzzi

Kilamo

Janes

2023

Preprint

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“…If a source code is difficult to read, it is also difficult to understand [2]. Some metrics have also been proposed to calculate source code understandability [11] [12] [4]. For instance, the cognitive complexity metric of SonarSource tool 1 is related with some aspects of understandability [1].…”

Section: Introductionmentioning

confidence: 99%

Readability and Understandability Scores for Snippet Assessment: an Exploratory Study

Dantas¹,

Maia²

2021

Anais Do IX Workshop De Visualização, Evolução E Manutenção De Software (VEM 2021)

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Code search engines usually use readability feature to rank code snippets. There are several metrics to calculate this feature, but developers may have different perceptions about readability. Correlation between readability and understandability features has already been proposed, i.e., developers need to read and comprehend the code snippet syntax, but also understand the semantics. This work investigate scores for understandability and readability features, under the perspective of the possible subjective perception of code snippet comprehension. We find that code snippets with higher readability score has better comprehension than lower ones. The understandability score presents better comprehension in specific situations, e.g. nested loops or if-else chains. The developers also mentioned writability aspects as the principal characteristic to evaluate code snippets comprehension. These results provide insights for future works in code comprehension score optimization.

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A Model for Measuring Software Understandability

Cited by 14 publications

References 10 publications

An Enhanced Data Augmentation Approach to Support Multi-Class Code Readability Classification

An Enhanced Data Augmentation Approach to Support Multi-Class Code Readability Classification

Does Cyclomatic or Cognitive Complexity Better Represents Code Understandability? An Empirical Investigation on the Developers Perception

Readability and Understandability Scores for Snippet Assessment: an Exploratory Study

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