The actual transforma top plot these smooths are

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Unformatted text preview: ctions of factors too of effort as for e modules that affect effort. are sample form for suchmost purposes. under study. There, we display the chance tha a regression However, effort A data (person hours) are available only at time an MR touches more than one file by sm issue could relationship is: endent, but this level. (Further analysis of factors affecting effort, in which each point corresponds to an MR based onclarger ‡ a FILES…c† ‡ a X 1fc > imputation of coordinate is time represented by the openin EFF… † ˆ a0 data sets but requiring the f gjf j 1 2 e ing the CDI effort for individual changes givfen aggregated effort y-coordinate is one when more than one file i …6† zero otherwise. Three local linear smooths ar model, is values, is in [25].) a ADD…c† ‡ a DEL…c† ‡3 4 Extreme variability of the feature-level data necessitated and [22] for introduction and discussion.) are m† ‡ a5 all …c† ‡ a6 DEV…c† : …10† taking logarithms of INTvariables. (The :actual transforma- top plot. These smooths are essentially w averages, where the weights have a Gaussian tion, denotes avoids negative numbers.) Here, jf jlog‰1 ‡ ÁŠ, the size in NCSL of the file f .The resultant s that have model is One motivation for the form used in (6) is to distinguish widths of the windows (i.e., standard dev ely free of the dependency overhead associated with a change, captured weight function) are h ˆ 0:3 (purple curve), h log…1 ‡ EFF…c†† ˆ :32 ‡ :13 …log‰1 ‡ FILES…c†Š†2 year older in the terms involving a0 , a1 , and a2 , from the nominal effort, colored curve), and h ˆ 7:5 (blue curve). The central curve, h ˆ 1:5, shows an initi two-thirds represent ed by the À e09…logi1 voDELgc†Š†32 and a4 . The t : rms ‰n ‡ lvin … a remaining terms incorporate interval and †Š log‰1 ‡ DEL…c†Š . trend, which is natural because many files a ‡ :12 log‰1 ‡ ADD…c developer overhead co m mo n c h a n g e s i n t h e i n i t i a l de v e l o p comparison A statistical analysis of this index appears in Section 5.4. ‡ :11 log‰1 ‡ INT…c†Š followed by a steady upward trend starting r of future À :47 log‰1 ‡ DELTAS…c†Š: last trend reflects breakdown in the modu the number ases, (10) is 5 THE EVIDENCE FOR DECAY …11† code, as we discuss further in Section 5.2. F some of our major results to correlation. m o d e l ( a s In this section, we discuss ile span has positive date. substantial increase comes from the fact th coefficients shown are statistically significantly ss, this still AllAll these analyses are based on a single subsystemdifferent the y-axis represent probabilities (local in of Large deletionsisare Despiteand of the change will touch more than one file, whi danger from zero; the of approximately 10038. implemented rather easily. multiple R2 value : modules the 2,500 eltas cause code, consisting s a model files. The Hardest changesroughly 6,000 IMRs,additions andfrom a low of less than 2 percent in change data consist of require both 27,000 doubles deletions. 12. One might expect that modules modified by many developers would aults over MRs, and 130,000 as a result Somedifferent styles and,login names than 5 percent in 1996. have confused logic deltas. of the 500 different hence, be difficult Large number of editing changes are rather In the absence of more detailed analysis, easy to implement. to change. made changes to the code in this subsystem. The results yield very strong evidence that code does the top plot in Fig. 3 depend on the window larger window width, h ˆ 7:5, shows only decay. Tuesday, September 10, 13 First, in Section 5.1, statistical smoothing demon- Results: (4) Prediction of efforts increases over time Expected results? •Changes will take longer to implements as modules age •Modularity breaks down over time. •The number of files that changed increases over time. •Large deletions are easier than large deletions and additions together. Tuesday, September 10, 13 Any unexpected results? •Older code is less likely to have fault. •More modules are affected by changes together....
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