Continual monitoring of code quality

Kothapalli, Chaitanya; Ganesh, Surya; Singh, Himanshu; Radhika, D. V.; Rajaram, T.; Ravikanth, K.; Gupta, Shrinath; Rao, K. Nitalaksheswara

doi:10.1145/1953355.1953379

Cited by 13 publications

(10 citation statements)

References 24 publications

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“…To address this, customized toolkits [5] have been provided to the teams to help classify results and rate them according to their required priorities, thus providing an -ility based representation of the results. ·…”

Section: Discussionmentioning

confidence: 99%

“…On further investigating, we found that one reason for this is that the violations reported by tools are quite descriptive, and the fixes to these issues are straight forward. And this task is further simplified due to use of toolkits [5] that provide a more understandable form of tool outputs.…”

Section: Experiences In Usage Of Static and Dynamic Analysis Toolsmentioning

confidence: 99%

“…The lengthy nature of the static analysis reports incur cost in terms of time and effort of analyzing the results which is mitigated through usage of customized toolkits [5]. These toolkits facilitate the teams to map to quality models, classify, rate and view the results in an organized manner.…”

Section: Dynamic Analysis Usage Patternmentioning

confidence: 99%

“…Static Analysis Assessments involved usage of static analysis tools and custom toolkits [5] that aided in visualization of the results. The lengthy tool outputs are processed by the toolkit, which enables classification of the violations based on the quality model.…”

Section: Expert Experience In Static Analysis Assessmentsmentioning

confidence: 99%

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Why is dynamic analysis not used as extensively as static analysis: an industrial study

Venkatasubramanyam¹,

Sowmya²

2014

Proceedings of the 1st International Workshop on Software Engineering Research and Industrial Practices

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Code Assessments using static and dynamic analyses are important for the maintenance of code quality of software in the industry. These analyses, though understood to be beneficial, have several practical limitations. The intent of our study was to understand the usage of these analyses across various teams in Siemens during code assessments, reasons for the success of static analysis and the challenges in dynamic analysis. The evaluation was conducted through a survey of the practices of developers in different development teams. Additionally interviews were conducted with expert reviewers and their experiences documented. Our study has revealed that institutionalization of code quality initiatives and customized toolkit support for static a n a l y s i s a r e s o m e o f t h e k e y r e a s o n s f o r t h e s u c c e s s f u l implementation of static analysis. Some of the problems hindering the widespread adoption of dynamic analysis include the direct dependency with test cases, scalability, and understandability of the results. Various implications of the results are discussed, including the possible improvements that could increase the acceptance of dynamic analysis on a regular basis.

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Section: Discussionmentioning

confidence: 99%

Section: Experiences In Usage Of Static and Dynamic Analysis Toolsmentioning

confidence: 99%

Section: Dynamic Analysis Usage Patternmentioning

confidence: 99%

Section: Expert Experience In Static Analysis Assessmentsmentioning

confidence: 99%

See 2 more Smart Citations

Why is dynamic analysis not used as extensively as static analysis: an industrial study

Venkatasubramanyam¹,

Sowmya²

2014

Proceedings of the 1st International Workshop on Software Engineering Research and Industrial Practices

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“…CQMM [3,5] is a continual quality monitoring framework that is based on use of a suitable 'quality model' to arrive at the measures to monitor and also define the corrective actions that can be taken. Fig.…”

Section: B Code Quality Monitoring Methods (Cqmm)mentioning

confidence: 99%

Making Continual Code Quality Monitoring and Control Processes Work in a Global Delivery Organization: COSMOS

Singh¹,

Uppili²,

Pavuluri³

2013

2013 IEEE 8th International Conference on Global Software Engineering

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Continual monitoring and model driven quality improvement methods are becoming critical for product quality within software development organizations. But, setting up such procedures within a global delivery organization poses challenges like -variation in the engagement models across different client projects, variations in build strategies and code ownership model, process related hindrances like overlapping quality processes of the delivery and the product organizations. Moreover, these challenges emerge overtime as the processes become more understood and accepted. We present evolution and design of COSMOS toolkit which exemplifies and addresses such variations in the delivery projects and provides a consistent continual reporting for organizations. The toolkit has become a primary enabler for adoption of a continual quality control process and CQMM, a model based quality improvement process. It addresses among others, key concerns like tools & build variability, legacy code & code ownership, model based rules selection & reporting, variations in applicable thresholds.

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