Software Engineering Research

Software engineering research in information systems examines how large codebases evolve over time, asking practical questions about why software breaks, how duplicated or tangled code accumulates, and whether the structure of source code can predict where defects will surface. By combining static analysis of code attributes with machine learning, researchers can build models that flag risky components before bugs are reported or help developers trace how a written requirement connects to the lines of code meant to satisfy it. Refactoring—restructuring existing code without changing its behavior—sits at the center of many of these concerns, since it both reduces future maintenance cost and complicates efforts to track defects across version histories. Open questions include how well defect prediction models generalize across different projects and programming languages, and how to automate requirements traceability reliably enough to be useful in industrial settings where documentation is often incomplete.

Works

110,544

Total citations

1,603,251

Keywords

RefactoringCode Clone DetectionSoftware Defect PredictionRequirements TraceabilityStatic Code AttributesMachine Learning