Can A Software Engineer Become A Software Developer

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Solid Code

Get best-in-class engineering practices to help you write more-robust, bug-free code. Two Microsoft .NET development experts share real-world examples and proven methods for optimizing the software development life cycle—from avoiding costly programming pitfalls to making your development team more efficient. Managed code developers at all levels will find design, prototyping, implementation, debugging, and testing tips to boost the quality of their code—today. Optimize each stage of the development process—from design to testing—and produce higher-quality applications. Use metaprogramming to reduce code complexity, while increasing flexibility and maintainability Treat performance as a feature—and manage it throughout the development life cycle Apply best practices for application scalability Employ preventative security measures to ward off malicious attacks Practice defensive programming to catch bugs before run time Incorporate automated builds, code analysis, and testing into the daily engineering process Implement better source-control management and check-in procedures Establish a quality-driven, milestone-based project rhythm—and improve your results!
Principles of Software Engineering

Author: EduGorilla Prep Experts
language: en
Publisher: EduGorilla Community Pvt. Ltd.
Release Date: 2024-06-05
EduGorilla Publication is a trusted name in the education sector, committed to empowering learners with high-quality study materials and resources. Specializing in competitive exams and academic support, EduGorilla provides comprehensive and well-structured content tailored to meet the needs of students across various streams and levels.
Expert Systems for Software Engineers and Managers

Author: S. David Hu
language: en
Publisher: Springer Science & Business Media
Release Date: 2013-03-08
This book is written for software engineers, software project leaders, and software managers who would like to introduce a new advanced software technology, expert systems, into their product. Expert system technology brings into programming a new dimension in which "rule of thumb" or heuristic expert knowledge is encoded in the program. In contrast to conventional procedural languages {e. g. , Fortran or C}, expert systems employ high-level programming languages {Le. , expert system shells} that enable us to capture the judgmental knowledge of experts such as geologists, doctors, lawyers, bankers, or insurance underwriters. Past expert systems have been more successfully applied in the problem areas of analysis and synthesis where the boundary of lo;nowledge is well defined and where experts are available and can be identified. Early successful applications include diagnosis systems such as MYCIN, geological systems such as PROSPECTOR, or design/configu ration systems such as XC ON. These early expert systems were mainly applicable to scientific and engineering problems, which are not theoreti cally well understood in terms of decisionmaking processes by their experts and which therefore require judgmental assessment. The more recent expert systems are being applied to sophisticated synthesis problems that involve a large number of choices, such as how the elements are to be compared. These problems normally entailed a large search space and slower speed for the expert systems designed. Examples of these systems include factory scheduling applications such as ISIS, or legal reasoning applications such as TAXMAN.