本文選題：程序員行為分析　切入點(diǎn)：時(shí)間序列交互數(shù)據(jù)　出處：《浙江大學(xué)》2016年博士論文　論文類型：學(xué)位論文

【摘要】：軟件工程是一種以人為中心的活動(dòng),因此人的因素對(duì)軟件開發(fā)過程的效率和產(chǎn)出都有著極為重要的影響,其中程序員是軟件工程中最為核心的參與人員。程序員是一種典型的知識(shí)工作者,他們的工作包括在不同的應(yīng)用之間生產(chǎn)、轉(zhuǎn)移和消費(fèi)大量的不同種類的信息,因此程序員有很多的信息需求從而使他們的行為變得更加復(fù)雜。通過理解程序員行為,研究者可以提出更好的程序編寫規(guī)范、項(xiàng)目管理方法以及軟件工具來(lái)支持程序員的工作,從而提高程序員的工作效率。近些年軟件工程的研究者們?cè)絹?lái)越關(guān)注人行為的研究,例如已經(jīng)有很多軟件工程的研討會(huì)和學(xué)術(shù)會(huì)議(如CHASE、VL/HCC)專注于人和人社會(huì)關(guān)系方面的研究。這些研究的目的包括調(diào)查程序員的能力、程序員在軟件開發(fā)和維護(hù)過程中的信息需求、程序員如何合作以及如何提高程序員效率等。在這些軟件工程的研究中,通常會(huì)采用很多的數(shù)據(jù)追蹤和收集方法,比如采訪、問卷、觀察、出聲思考、插裝等。在程序員行為研究中有兩種技術(shù)被廣泛地用來(lái)收集數(shù)據(jù)：截屏錄像和插裝。截屏錄像是一種通用而且容易部署的方法,但是分析截屏錄像數(shù)據(jù)需要大量的時(shí)間和人力；而插裝一個(gè)軟件可以自動(dòng)化地記錄一個(gè)應(yīng)用中的用戶交互數(shù)據(jù),但是插裝當(dāng)前很多的應(yīng)用軟件都比較復(fù)雜,而且程序員在軟件開發(fā)過程中會(huì)使用多個(gè)軟件(如IDE、瀏覽器等),插裝所有的軟件需要相當(dāng)大的代價(jià)。針對(duì)這兩個(gè)問題,本文提出了相應(yīng)的方法并實(shí)現(xiàn)了兩個(gè)工具：scvRipper和ActivityS-pace。利用這兩個(gè)工具收集到的數(shù)據(jù),本文同時(shí)還做了一些程序員行為的分析。具體的,本文的主要貢獻(xiàn)有以下部分：1.本文提出了一種基于計(jì)算機(jī)視覺技術(shù)可以自動(dòng)化地從截屏錄像中抽取出時(shí)間序列的程序員交互數(shù)據(jù)的方法,并實(shí)現(xiàn)了一個(gè)截屏錄像挖取工具scvRipper。利用29個(gè)小時(shí)的截屏錄像數(shù)據(jù),本文評(píng)估了scvRipper的可用性、有效性和性能。2.利用scvRipper從29個(gè)小時(shí)截屏錄像數(shù)據(jù)中抽取的時(shí)間序列交互數(shù)據(jù),本文做了一個(gè)程序員在軟件開發(fā)過程中網(wǎng)上搜索行為的細(xì)粒度定量分析,同時(shí)這個(gè)定量分析也證明了scvRipper的可用性。利用同樣的數(shù)據(jù),本文還提出了一種基于數(shù)據(jù)挖掘技術(shù)的方法BPMiner,它可以從scvRipper挖取的截屏錄像數(shù)據(jù)中分析出程序員行為模式。3.本文基于操作系統(tǒng)(OS)層面的插裝方法來(lái)跟蹤和收集程序員與應(yīng)用交互時(shí)的鼠標(biāo)和鍵盤事件,從而追蹤程序員在各個(gè)不同應(yīng)用中的活動(dòng),并且不需要對(duì)所有軟件進(jìn)行插裝。本文通過對(duì)這些數(shù)據(jù)做了進(jìn)一步地抽象和分析,并提供了一些情景式的和語(yǔ)義的UI來(lái)幫助程序員搜索跨應(yīng)用的相關(guān)信息,這個(gè)工具稱之為ActivitySpace。同時(shí)本文設(shè)計(jì)了一個(gè)評(píng)估ActivitySpace的案例研究,從8個(gè)參與者中搜集了417個(gè)小時(shí)的有效活動(dòng)數(shù)據(jù)。利用這些數(shù)據(jù),本文分析了軟件開發(fā)過程中的信息碎片問題以及評(píng)估了ActivitySpace的有效性。4.與以前規(guī)模較小并且在控制的實(shí)驗(yàn)環(huán)境下進(jìn)行的程序理解行為研究相比,本文利用ActivitySpace,做了一個(gè)在實(shí)際的開發(fā)環(huán)境中大規(guī)模的關(guān)于程序理解行為的探索性研究。本文收集了來(lái)自5個(gè)真實(shí)項(xiàng)目組共48個(gè)程序員,1725個(gè)小時(shí)的有效工作數(shù)據(jù),這些數(shù)據(jù)包括來(lái)自多個(gè)應(yīng)用(比如IDE、瀏覽器)的程序員交互數(shù)據(jù)。本文通過這個(gè)案例研究驗(yàn)證了程序理解在軟件開發(fā)中的重要作用,以及影響程序員程序理解效率的若干主要因素及其初步的相關(guān)性探索。
[Abstract]:Software engineering is a kind of human centered activities, so the factors of efficiency and output of the software development process has a very important influence, which is involved in the programmer is the core of software engineering. The programmer is a kind of typical knowledge workers, their work includes production between different applications transfer, and the consumption of a large number of different kinds of information, so programmers have a lot of information needs in order to make their behavior become more complex. Through the understanding of programmer behavior, researchers can put forward written specification better procedures, project management methods and software tools to support the programmer's job, so as to improve programmer productivity. Researchers and more attention to the behavior of people in recent years, researchers in software engineering, for example, there has been a lot of software engineering seminars and academic conferences (such as CHASE, VL/, HCC) focus Study on the relationship between the people and society. The purpose of these studies including the investigation ability of programmers, programmers in the process of software development and maintenance of the information needs, how to cooperate and how to improve the programmer programmer efficiency. In the study of these software projects, often use a lot of data tracking and collection methods, such as interviews. The questionnaire, observation, thinking aloud, inserted. The programmer behavior research has two kinds of techniques are widely used to collect data: screencasts and cartridge. Screencasts is a universal and easy deployment method, but the analysis of screencasts data requires a lot of time and manpower; and a cartridge the software can automatically record the user interaction data for an application, but the current inserted many software applications are more complex, and the programmer will make use in the software development process A software (such as IDE browser, etc.), inserted all software requires considerable cost. To solve these two problems, this paper puts forward the corresponding method and the realization of the two tools: scvRipper and ActivityS-pace. using the two tools of the collected data, this paper also analyzes the behavior of some programmers. Specifically, the main contributions of this paper are as follows: 1. this paper presents a method of computer vision technology can automatically extract video screenshot from time series programmer interaction based on the data, and implements a video screenshot digging tool scvRipper. uses screencasts 29 hours of data, this paper evaluates the available scvRipper, time series of interactive data availability and performance of.2. using scvRipper extracted from 29 hours screencasts data, this paper made a programmer in software development process Quantitative analysis of fine-grained search behavior, while the quantitative analysis also proved the availability of scvRipper. Using the same data, this paper also proposes a BPMiner method based on data mining technology, it can dig out the.3. analysis mode of programmer behavior based on operating system data extracted from the video screen scvRipper (OS) insertion method to track and collect the interactive programmer and application of mouse and keyboard events level, so as to track each programmer in different applications, and do not need to all software plug-in. Based on these data further abstraction and analysis, and provides some situational and semantic UI to help the programmer to search related information across applications, this tool called ActivitySpace. at the same time this paper designed a case study to evaluate ActivitySpace, from 8 The participants were collected effective activity data for 417 hours. Using these data, this paper analyzes the information fragmentation problem in the process of software development and evaluation of the effectiveness of.4. ActivitySpace with the previous smaller and the environmental control of program comprehension for study compared to using ActivitySpace, do a the actual development environment in large scale on program understanding behavior research. This paper collected from 5 real project group of 48 programmers, working 1725 hours of data, these data from multiple applications (such as IDE, browser) programmer interaction data. Through this case study verifies the important in software development program understanding, explore some and main factors affecting the efficiency of the programmer program understanding and preliminary correlation.

【學(xué)位授予單位】：浙江大學(xué)
【學(xué)位級(jí)別】：博士
【學(xué)位授予年份】：2016
【分類號(hào)】：TP311.52

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