The Study of Automatic Collection of Personal Effort Data for Software Engineer

碩士 === 國立臺灣科技大學 === 管理學院MBA === 96 === The purpose of the training of Personal Software Process (PSP) is to improve the software quality and to help software engineers shape good working habits. The well-trained engineers are the basis of a good team and also the factors in improving a team’s compet...

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Bibliographic Details
Main Authors: TSEN-CHUNG WENG, 翁叁忠
Other Authors: none
Format: Others
Language:zh-TW
Online Access:http://ndltd.ncl.edu.tw/handle/89642302163706948694
Description
Summary:碩士 === 國立臺灣科技大學 === 管理學院MBA === 96 === The purpose of the training of Personal Software Process (PSP) is to improve the software quality and to help software engineers shape good working habits. The well-trained engineers are the basis of a good team and also the factors in improving a team’s competence. Therefore, any engineer who participates in the Team Software Process (TSP) training project needs the training of PSP because the introduction of PSP is a direct boost to the practice of TSP and Capability Maturity Model Integration (CMMI). The emphasis of PSP is on the collection and analysis of quantitative data, with which the effectiveness and productivity of individual process can be improved. Among the quantitative data, personal effort data is one of the most important software measures. However, at the present time, the non-automatic collection of personal effort data is time-consuming in reality. It also affects individual effectiveness and the quality of the data collected. Thus the practice of non-automatic collection of the personal effort data for software engineers is an obstacle to the effectiveness of a team. Based on the theory of PSP, this study is conducted to develop an automatic system of collection and analysis of personal effort data for software engineers. A goal-driven software measurement method is applied to examine the case study. The system of automatic personal effort collection is installed into the user’s computer to record in every 10 second the following items: the applied program in use, the time in the computer and the condition of the keyboard and the mouse. The data thus collected in the database can be used to compute the time each movement takes and to analyze the working time of each procedure. The conclusions from the results of the case study are the followings: (1) The collected personal effort data can be used as the basis of analysis. (2) The collected effort data can be compared with the original plan and the current project status can be evaluated. (3) Manpower, cost and time of the future project can be estimated if the data of effort is available. (4) The quantitative working time facilitates the understanding of the problems in software development project and thus helps improve the quality and effectiveness of software development project.