The techniques used in protein production and structural biology have been developing rapidly, but techniques for recording the laboratory information produced have not kept pace. One approach is the development of la...
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The techniques used in protein production and structural biology have been developing rapidly, but techniques for recording the laboratory information produced have not kept pace. One approach is the development of laboratory information-management systems (LIMS), which typically use a relational database schema to model and store results from a laboratory workflow. The underlying philosophy and implementation of the Protein Information Management System (PiMS), a LIMS development specifically targeted at the flexible and unpredictable workflows of protein-production research laboratories of all scales, is described. PiMS is a web-based java application that uses either Postgres or Oracle as the underlying relational database-management system. PiMS is available under a free licence to all academic laboratories either for local installation or for use as a managed service.
A unique book-and-video package presented by java guru Yakov Fain As one of the most popular software languages for building webapplications, java is often the first programming language developers learn. The latest ...
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ISBN:
(数字)9781118058176
ISBN:
(纸本)9780470889640
A unique book-and-video package presented by java guru Yakov Fain As one of the most popular software languages for building webapplications, java is often the first programming language developers learn. The latest version includes numerous updates that both novice and experienced developers need to know. With this invaluable book-and-video package, java authority Yakov Fain fully covers java?s new features as well as its language extensions, classes and class methods, and the Swing Application Framework. For each lesson that he discusses in the book, there is an accompanying instructional video to reinforce your learning *** include:Introducing java Eclipse IDE Object-Oriented Programming Class MethodsBack to java Basics Packages, Interfaces, and Encapsulation Programming with Abstract Classes and InterfacesIntroducing the Graphic User InterfaceEvent Handling in UIIntroduction to java Applets Developing a Tic-Tac-Toe Applet Developing a Ping-Pong Game Error Handling Introduction to Collections Introduction to Generics Working with Streams java Serialization Network ProgrammingProcessing E-Mails with java Introduction to Multi-Threading Digging Deeper into Concurrent Execution Working with Databases Using JDBC Swing with JTable Annotations and Reflection Remote Method Invocation java EE 6 Overview Programming with Servlets javaServer Pages Developing webapplications with JSF Introducing JMS and MOM Introducing JNDIIntroduction to Enterprise javaBeansIntroduction to the java Persistence APIWorking with RESTful web ServicesIntroduction to Spring MVC Framework Introduction to Hibernate Framework Bringing javaFX to the Mix java Technical Interviews Note: As part of the print version of this title, video lessons are included on DVD. For e-book versions, video lessons can be accessed at *** using a link provided in the interior of the e-book.?
Testing web forms is an essential activity for ensuring the quality of webapplications. It typically involves evaluating the interactions between users and forms. Automated test-case generation remains a challenge fo...
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Testing web forms is an essential activity for ensuring the quality of webapplications. It typically involves evaluating the interactions between users and forms. Automated test-case generation remains a challenge for web-form testing: Due to the complex, multi-level structure of web pages, it can be difficult to automatically capture their inherent contextual information for inclusion in the tests. Large Language Models (LLMs) have shown great potential for contextual text generation. This motivated us to explore how they could generate automated tests for web forms, making use of the contextual information within form elements. To the best of our knowledge, no comparative study examining different LLMs has yet been reported for web-form-test generation. To address this gap in the literature, we conducted a comprehensive empirical study investigating the effectiveness of 11 LLMs on 146 web forms from 30 open-source java web applications. In addition, we propose three HTML-structure-pruning methods to extract key contextual information. The experimental results show that different LLMs can achieve different testing effectiveness, with the GPT-4, GLM-4, and Baichuan2 LLMs generating the best web-form tests. Compared with GPT-4, the other LLMs had difficulty generating appropriate tests for the web forms: Their successfully-submitted rates (SSRs) — the proportions of the LLMs-generated web-form tests that could be successfully inserted into the web forms and submitted — decreased by 9.10% to 74.15%. Our findings also show that, for all LLMs, when the designed prompts include complete and clear contextual information about the web forms, more effective web-form tests were generated. Specifically, when using Parser-Processed HTML for Task Prompt (PH-P), the SSR averaged 70.63%, higher than the 60.21% for Raw HTML for Task Prompt (RH-P) and 50.27% for LLM-Processed HTML for Task Prompt (LH-P). With RH-P, GPT-4’s SSR was 98.86%, outperforming models like LLaMa2 (7B) with
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