Studying the relationship between exception handling practices and post-release defects

Pádua, Guilherme B. de; Shang, Weiyi

doi:10.1145/3196398.3196435

Cited by 17 publications

(11 citation statements)

References 45 publications

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“…Three papers and the thesis of Pádua et al [15], [16], [17], [18] cite our article when discussing the importance of exception handling code. Similarly to our article, 19 different papers focus on bugs in the exception handling code [19], [20], [21], [22], [23], [24], [15], [25], [26], [27], [17], [14], [28], [18], [29], [30], [31], [32], [13]. Our categorization of exception handling bugs and their causes has been (partially) used in five different studies [20], [15], [26], [33], [18] The survey we conducted in our article also served as a basis for surveys by de Sousa [13], [34].…”

Section: Impactsmentioning

confidence: 99%

“…Our categorization of exception handling bugs and their causes has been (partially) used in five different studies [20], [15], [26], [33], [18] The survey we conducted in our article also served as a basis for surveys by de Sousa [13], [34]. Finally, we found 15 papers addressing the five themes for future work that our paper discussed [23], [25], [26], [27], [35], [17], [36], [33], [29], [37], [30], [31], [32], [13], [38].…”

Section: Impactsmentioning

confidence: 99%

“…Pádua and Shang [17] studied bugs related to exception propagation and their relationship with exception handling anti-patterns. Our work served as a rationale for three out of the 15 exception flow-related metrics used in the study.…”

Section: A Have Other Papers Followed Up?mentioning

confidence: 99%

“…Following along the steps of the work by Pádua and Shang [17], we think it is worth conducting a more in-depth validation of existing best practices and anti-patterns. Developers have been building intensively-used, mission-critical systems that use exceptions for a long time.…”

Section: New Emerging Ideas and Current Visionmentioning

confidence: 99%

See 3 more Smart Citations

A Reflection on “An Exploratory Study on Exception Handling Bugs in Java Programs”

Ebert

Castor

Serebrenik

2020

2020 IEEE 27th International Conference on Software Analysis, Evolution and Reengineering (SANER)

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Section: Impactsmentioning

confidence: 99%

Section: Impactsmentioning

confidence: 99%

Section: A Have Other Papers Followed Up?mentioning

confidence: 99%

Section: New Emerging Ideas and Current Visionmentioning

confidence: 99%

See 2 more Smart Citations

A Reflection on “An Exploratory Study on Exception Handling Bugs in Java Programs”

Ebert

Castor

Serebrenik

2020

2020 IEEE 27th International Conference on Software Analysis, Evolution and Reengineering (SANER)

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“…Instead of removing all correlated metrics, prior work often manually selects one metric for each group of correlated metrics [49,56,78,79]-assuming that the selected metric is representative to the group of correlated metrics. However, the manual selection approach often varies based on a domain expert and limits the automation of software analytics in practice [14].…”

Section: An Automated Metric Selection Approachmentioning

confidence: 99%

AutoSpearman: Automatically Mitigating Correlated Software Metrics for Interpreting Defect Models

Jiarpakdee

Tantithamthavorn

2018

2018 IEEE International Conference on Software Maintenance and Evolution (ICSME)

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The interpretation of defect models heavily relies on software metrics that are used to construct them. However, such software metrics are often correlated in defect models. Prior work often uses feature selection techniques to remove correlated metrics in order to improve the performance of defect models. Yet, the interpretation of defect models may be misleading if feature selection techniques produce subsets of inconsistent and correlated metrics. In this paper, we investigate the consistency and correlation of the subsets of metrics that are produced by nine commonly-used feature selection techniques. Through a case study of 13 publicly-available defect datasets, we find that feature selection techniques produce inconsistent subsets of metrics and do not mitigate correlated metrics, suggesting that feature selection techniques should not be used and correlation analyses must be applied when the goal is model interpretation. Since correlation analyses often involve manual selection of metrics by a domain expert, we introduce AutoSpearman, an automated metric selection approach based on correlation analyses. Our evaluation indicates that AutoSpearman yields the highest consistency of subsets of metrics among training samples and mitigates correlated metrics, while impacting model performance by 1-2%pts. Thus, to automatically mitigate correlated metrics when interpreting defect models, we recommend future studies use AutoSpearman in lieu of commonly-used feature selection techniques.

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The secret life of test smells - an empirical study on test smell evolution and maintenance

2021

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Studying the relationship between exception handling practices and post-release defects

Cited by 17 publications

References 45 publications

A Reflection on “An Exploratory Study on Exception Handling Bugs in Java Programs”

A Reflection on “An Exploratory Study on Exception Handling Bugs in Java Programs”

AutoSpearman: Automatically Mitigating Correlated Software Metrics for Interpreting Defect Models

The secret life of test smells - an empirical study on test smell evolution and maintenance

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