Although software managers are generally good at new project estimation, their experience of scheduling rework tends to be poor. Inconsistent or incorrect effort estimation can increase the risk that the completion time for a project will be problematic. To continually alter software maintenance schedules during software maintenance is a daunting task. Our proposed framework, validated in a case study confirms that the variables resulting from requirements changes suffer from a number of problems, e.g., the coding used, end user involvement and user documentation. Our results clearly show a significant impact on rework effort as a result of unexpected errors that correlate with 1) weak characteristics and attributes as described in the program’s source lines of code, especially in data declarations and data statements, 2) lack of communication between developers and users on a change effects, and 3) unavailability of user documentation. To keep rework effort under control, new criteria in change request forms are proposed. These criteria are shown in a proposed framework; the more case studies that are validated, the more reliable the result will be in determining the outcome of effort rework estimation.

Detection of code clones — similar or identical source code fragments — is of concern both to researchers and to practitioners. An analysis of the clone detection results for a single source code version provides a developer with information about a discrete state in the evolution of the software system. However, tracing clones across multiple source code versions permits a clone analysis to consider a temporal dimension. Such an analysis of clone evolution can be used to uncover the patterns and characteristics exhibited by clones as they evolve within a system. Developers can use the results of this analysis to understand the clones more completely, which may help them to manage the clones more effectively. Thus, studies of clone evolution serve a key role in understanding and addressing issues of cloning in software. In this paper, we present a systematic review of the literature on clone evolution. In particular, we present a detailed analysis of 30 relevant papers that we identified in accordance with our review protocol. The review results were organized to address three research questions. Through our answers to these questions, we present the methods that researchers have used to study clone evolution, the patterns that researchers have found evolving clones to exhibit, and the evidence that researchers have established regarding the extent of inconsistent change undergone by clones during software evolution. Overall, the review results indicate that whereas researchers have conducted several empirical studies of clone evolution, there are contradictions