際際滷shows by User: zazworka / http://www.slideshare.net/images/logo.gif 際際滷shows by User: zazworka / Tue, 12 Jun 2012 09:55:26 GMT 際際滷Share feed for 際際滷shows by User: zazworka Identifying and Managing Technical Debt /slideshow/identifying-and-managing-technical-debt/13294240 tdwebinarslideshare-120612095530-phpapp01
The technical debt metaphor is useful in capturing the long-term impacts of tradeoffs taken during software maintenance between productivity (getting something done sooner) and maintainability (degradation of the code's quality over time). This webinar on Technical Debt will present techniques and insights that help software engineers to identify and track technical debt in their projects. We will outline how business and product quality goals should affect the choice of approaches (and combinations of approaches) for managing technical debt. More specifically, we will discuss a set of automated approaches based on static code analysis that are likely to spot problems in source code that have real impact on productivity and defect proneness. Based on previous empirical studies, we will give further advice on which types of debt can be found by these tools, and which types are not yet detectable. ]]>
The technical debt metaphor is useful in capturing the long-term impacts of tradeoffs taken during software maintenance between productivity (getting something done sooner) and maintainability (degradation of the code's quality over time). This webinar on Technical Debt will present techniques and insights that help software engineers to identify and track technical debt in their projects. We will outline how business and product quality goals should affect the choice of approaches (and combinations of approaches) for managing technical debt. More specifically, we will discuss a set of automated approaches based on static code analysis that are likely to spot problems in source code that have real impact on productivity and defect proneness. Based on previous empirical studies, we will give further advice on which types of debt can be found by these tools, and which types are not yet detectable. ]]> Tue, 12 Jun 2012 09:55:26 GMT /slideshow/identifying-and-managing-technical-debt/13294240 zazworka@slideshare.net(zazworka) Identifying and Managing Technical Debt zazworka The technical debt metaphor is useful in capturing the long-term impacts of tradeoffs taken during software maintenance between productivity (getting something done sooner) and maintainability (degradation of the code's quality over time). This webinar on Technical Debt will present techniques and insights that help software engineers to identify and track technical debt in their projects. We will outline how business and product quality goals should affect the choice of approaches (and combinations of approaches) for managing technical debt. More specifically, we will discuss a set of automated approaches based on static code analysis that are likely to spot problems in source code that have real impact on productivity and defect proneness. Based on previous empirical studies, we will give further advice on which types of debt can be found by these tools, and which types are not yet detectable. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/tdwebinarslideshare-120612095530-phpapp01-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> The technical debt metaphor is useful in capturing the long-term impacts of tradeoffs taken during software maintenance between productivity (getting something done sooner) and maintainability (degradation of the code&#39;s quality over time). This webinar on Technical Debt will present techniques and insights that help software engineers to identify and track technical debt in their projects. We will outline how business and product quality goals should affect the choice of approaches (and combinations of approaches) for managing technical debt. More specifically, we will discuss a set of automated approaches based on static code analysis that are likely to spot problems in source code that have real impact on productivity and defect proneness. Based on previous empirical studies, we will give further advice on which types of debt can be found by these tools, and which types are not yet detectable.
Identifying and Managing Technical Debt from zazworka
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