In this course, students learn and gain practical experience with software engineering principles and techniques. The practical experience centers on a semester-long team project in which a software development project is carried through all the stages of the software life cycle. Topics in this course include requirements analysis, specification, design, abstraction, programming style, testing, maintenance, communication, teamwork, and software project management. Particular emphasis is placed on communication and negotiation skills and on designing and developing maintainable software.

In this course, students learn and gain practical experience with software engineering principles and techniques. The practical experience centers on a semester-long team project in which a software development project is carried through all the stages of the software life cycle. Topics in this course include requirements analysis, specification, design, abstraction, programming style, testing, maintenance, communication, teamwork, and software project management. Particular emphasis is placed on communication and negotiation skills and on designing and developing maintainable software.

Design and analysis of efficient algorithms for important computational problems. Emphasis on the relationships between algorithms and data structures, measures of algorithmic efficiency, reasoning about correctness. Graph algorithms, design strategies (greedy, divide and conquer, dynamic programming), intractability. Use of computer required.

Design and analysis of efficient algorithms for important computational problems. Emphasis on the relationships between algorithms and data structures, measures of algorithmic efficiency, reasoning about correctness. Graph algorithms, design strategies (greedy, divide and conquer, dynamic programming), intractability. Use of computer required.

Design and analysis of efficient algorithms for important computational problems. Emphasis on the relationships between algorithms and data structures, measures of algorithmic efficiency, reasoning about correctness. Graph algorithms, design strategies (greedy, divide and conquer, dynamic programming), intractability. Use of computer required.

Design and analysis of efficient algorithms for important computational problems. Emphasis on the relationships between algorithms and data structures, measures of algorithmic efficiency, reasoning about correctness. Graph algorithms, design strategies (greedy, divide and conquer, dynamic programming), intractability. Use of computer required.

Design and analysis of efficient algorithms for important computational problems. Emphasis on the relationships between algorithms and data structures, measures of algorithmic efficiency, reasoning about correctness. Graph algorithms, design strategies (greedy, divide and conquer, dynamic programming), intractability. Use of computer required.

Design and analysis of efficient algorithms for important computational problems. Emphasis on the relationships between algorithms and data structures, measures of algorithmic efficiency, reasoning about correctness. Graph algorithms, design strategies (greedy, divide and conquer, dynamic programming), intractability. Use of computer required.

Design and analysis of efficient algorithms for important computational problems. Emphasis on the relationships between algorithms and data structures, measures of algorithmic efficiency, reasoning about correctness. Graph algorithms, design strategies (greedy, divide and conquer, dynamic programming), intractability. Use of computer required.

Design and analysis of efficient algorithms for important computational problems. Emphasis on the relationships between algorithms and data structures, measures of algorithmic efficiency, reasoning about correctness. Graph algorithms, design strategies (greedy, divide and conquer, dynamic programming), intractability. Use of computer required.