On Quantifying the Benefits of Dead Code Removal

Engineers consider the presence of dead code as an undesirable attribute of the code base. The industry lacks methods to quantify the benefits of deleting dead code efficiently. The current approach utilizes a simplistic metric that uses the lines of code (LOC) deleted as a proxy to estimate the benefit gained. However, not all LOC are equal. The research community can support the industry and propose methods and metrics that can help to (a) determine the priority order for dead code removal, and (b) quantify the benefits of dead code removal. Improved metrics can result in a more objective ranking of dead code deletion efforts when compared to other competing tasks

A New Generation of Class Blueprint

International audienceIn object-oriented programming, classes are the primary abstraction mechanism used by and exposed to developers. Understanding classes is key for the development and evolution of object-oriented applications. The fundamental problem faced by developers is that while classes are intrinsically structured entities, in IDEs they are represented as a blob of text. The idea behind the original CLASS BLUEPRINT visualization was to represent the internal structure of classes in terms of fields, their accesses, and the method call flow. Additional information was depicted using colors. The thus created visualization proved to be an effective means to support program comprehension. However, a number of omissions rendered it only partially useful. We propose CLASS BLUEPRINT V2 (in short BLUEPRINTV2), which in addition to the information depicted by CLASS BLUEPRINT also supports dead code identification, methods under tests, and calling relationships between class and instance level methods. In addition, BLUEPRINTV2 enhances the understanding of fields by showing how fields of super/subclasses are accessed. We present the enhanced visualization and report on a first validation with 26 developers and 18 projects

How much does unused code matter for maintenance?

Abstract—Software systems contain unnecessary code. Its maintenance causes unnecessary costs. We present tool-support that employs dynamic analysis of deployed software to detect unused code as an approximation of unnecessary code, and static analysis to reveal its changes during maintenance. We present a case study on maintenance of unused code in an industrial software system over the course of two years. It quantifies the amount of code that is unused, the amount of maintenance activity that went into it and makes the potential benefit of tool support explicit, which informs maintainers that are about to modify unused code. Keywords-Software maintenance, dynamic analysis, unneces-sary code, unused code I