An empirical investigation on the challenges of creating custom static analysis rules for defect localization

Custom static analysis rules, i.e., rules specific for one or more applications, have been successfully applied to perform corrective and preventive software maintenance. Pattern-driven maintenance (PDM) is a method designed to support the creation of such rules during software maintenance. However,...

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Published inSoftware quality journal Vol. 30; no. 3; pp. 781 - 808
Main Authors Mendonça, Diogo S., Kalinowski, Marcos
Format Journal Article
LanguageEnglish
Published New York Springer US 01.09.2022
Springer Nature B.V
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Abstract Custom static analysis rules, i.e., rules specific for one or more applications, have been successfully applied to perform corrective and preventive software maintenance. Pattern-driven maintenance (PDM) is a method designed to support the creation of such rules during software maintenance. However, as PDM was recently proposed, few maintainers have reported on its usage. Hence, the challenges and skills needed to apply PDM properly are unknown. In this paper, we investigate the challenges faced by maintainers on applying PDM for creating custom static analysis rules for defect localization. We conducted an observational study on novice maintainers creating custom static analysis rules by applying PDM. The study was divided into three tasks: (i) identifying a defect pattern, (ii) programming a static analysis rule to locate instances of the pattern, and (iii) verifying the located instances. We analyzed the efficiency and acceptance of maintainers on applying PDM and their comments on task challenges. We observed that previous knowledge on debugging, the subject software, and related technologies influenced the performance of maintainers as well as the time to learn the technology involved in rule programming. The results strengthen our confidence that PDM can help maintainers in producing custom static analysis rules for locating defects. However, a proper selection and training of maintainers is needed to apply PDM effectively. Also, using a higher level of abstraction can ease static analysis rule programming for novice maintainers.
AbstractList Custom static analysis rules, i.e., rules specific for one or more applications, have been successfully applied to perform corrective and preventive software maintenance. Pattern-driven maintenance (PDM) is a method designed to support the creation of such rules during software maintenance. However, as PDM was recently proposed, few maintainers have reported on its usage. Hence, the challenges and skills needed to apply PDM properly are unknown. In this paper, we investigate the challenges faced by maintainers on applying PDM for creating custom static analysis rules for defect localization. We conducted an observational study on novice maintainers creating custom static analysis rules by applying PDM. The study was divided into three tasks: (i) identifying a defect pattern, (ii) programming a static analysis rule to locate instances of the pattern, and (iii) verifying the located instances. We analyzed the efficiency and acceptance of maintainers on applying PDM and their comments on task challenges. We observed that previous knowledge on debugging, the subject software, and related technologies influenced the performance of maintainers as well as the time to learn the technology involved in rule programming. The results strengthen our confidence that PDM can help maintainers in producing custom static analysis rules for locating defects. However, a proper selection and training of maintainers is needed to apply PDM effectively. Also, using a higher level of abstraction can ease static analysis rule programming for novice maintainers.
Custom static analysis rules, i.e., rules specific for one or more applications, have been successfully applied to perform corrective and preventive software maintenance. Pattern-driven maintenance (PDM) is a method designed to support the creation of such rules during software maintenance. However, as PDM was recently proposed, few maintainers have reported on its usage. Hence, the challenges and skills needed to apply PDM properly are unknown. In this paper, we investigate the challenges faced by maintainers on applying PDM for creating custom static analysis rules for defect localization. We conducted an observational study on novice maintainers creating custom static analysis rules by applying PDM. The study was divided into three tasks: (i) identifying a defect pattern, (ii) programming a static analysis rule to locate instances of the pattern, and (iii) verifying the located instances. We analyzed the efficiency and acceptance of maintainers on applying PDM and their comments on task challenges. We observed that previous knowledge on debugging, the subject software, and related technologies influenced the performance of maintainers as well as the time to learn the technology involved in rule programming. The results strengthen our confidence that PDM can help maintainers in producing custom static analysis rules for locating defects. However, a proper selection and training of maintainers is needed to apply PDM effectively. Also, using a higher level of abstraction can ease static analysis rule programming for novice maintainers.Custom static analysis rules, i.e., rules specific for one or more applications, have been successfully applied to perform corrective and preventive software maintenance. Pattern-driven maintenance (PDM) is a method designed to support the creation of such rules during software maintenance. However, as PDM was recently proposed, few maintainers have reported on its usage. Hence, the challenges and skills needed to apply PDM properly are unknown. In this paper, we investigate the challenges faced by maintainers on applying PDM for creating custom static analysis rules for defect localization. We conducted an observational study on novice maintainers creating custom static analysis rules by applying PDM. The study was divided into three tasks: (i) identifying a defect pattern, (ii) programming a static analysis rule to locate instances of the pattern, and (iii) verifying the located instances. We analyzed the efficiency and acceptance of maintainers on applying PDM and their comments on task challenges. We observed that previous knowledge on debugging, the subject software, and related technologies influenced the performance of maintainers as well as the time to learn the technology involved in rule programming. The results strengthen our confidence that PDM can help maintainers in producing custom static analysis rules for locating defects. However, a proper selection and training of maintainers is needed to apply PDM effectively. Also, using a higher level of abstraction can ease static analysis rule programming for novice maintainers.
Author Kalinowski, Marcos
Mendonça, Diogo S.
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Issue 3
Keywords Custom static analysis rules
Observational study
Code defect patterns
Pattern-Driven Maintenance
Language English
License The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2021.
This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic.
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SubjectTerms Compilers
Computer Science
Data Structures and Information Theory
Defects
Empirical analysis
Interpreters
Localization
Maintenance
Observational studies
Operating Systems
Programming
Programming Languages
Software
Software Engineering/Programming and Operating Systems
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Title An empirical investigation on the challenges of creating custom static analysis rules for defect localization
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Volume 30
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