Method for forecasting software development cost and execution time aiming at reworking

Abstract

The invention belongs to the field of software process simulation and modeling and discloses a method for forecasting the execution time and the software development cost. The method comprises the following steps of: establishing a software process model through an as-TRISO / ML process simulation and modeling language; designating the attribute of an actual activity in the model and the attribute of a human resource to be distributed according to historic experience and the like; distributing workers to a process activity; and inputting the process model, the attributes and the human resource distribution into a software process random simulation tool, simulating the simulation model for many times by simulating appointed parameters, and analyzing a simulated result to acquire the execution time and the development cost of the same activity of the software process, a probability distribution of the process execution time and the development cost, and other derivative indexes. By the method, the complexity of the process modeling is simplified; by taking reasons and influences of reworking into consideration, the method is more accurate than the conventional experience-based reworking analysis method; moreover, the simulation analysis result can be displayed in a plurality of angles, so the accuracy and the practicability of the software process analysis can be enhanced.

Description

technical field [0001] The invention belongs to the field of software process modeling and simulation, and specifically relates to a method for predicting software development cost and execution time by establishing a software process simulation model and software process simulation considering personnel ability and possibility of rework. Background technique [0002] "Software crisis", a concept that began in the 1960s, has always been accompanied by the entire historical development process of the software industry. Over the past few decades, software organizations have often faced software project overruns and delays, and the quality of software products has often failed to meet customer expectations. Many studies from industry and academia have attempted to address this issue. In these attempts, research based on software process technology, such as: software process modeling, software process simulation, etc., are very effective methods. [0003] At present, people ha...

AI Technical Summary

Problems solved by technology

The weakness of this method lies in: first, this method is relatively complicated, and the calibration process of parameters requires a large amount of historical data, which are generally not easy to collect and analyze; to use this method for progress prediction, the software organization needs to prepare early. Constantly calibrate model parameters

For general small and medium-sized software companies, the cost of accumulating process historical data is very high, so their accumulation of software process historical data is often not enough to support the calibration of the parameters in the model, so this method is not applicable in such software organizations

Second, this method only estimates the process progress based on the process workload and personnel work efficiency, without considering the structure of the software process. If the process structure is unreasonable, it will often affect the work efficiency of the process executives and cause problems such as delays in work. greatly affects the accuracy of the method in predicting the progress of the process

Third, this method does not consider the impact of software reuse, COTS software, management strategies, etc.

Based on the above points, COCOMO's prediction of the progress of the software process is not practical and accurate enough

Fourth, although the COCOMO model considers rework factors macroscopically, it does not explicitly analyze the relationship between rework, cost and schedule, so its estimation results are far from specific enough to show sufficient reference value for project management

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