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C++ In Depth Series Accelerated C++ 効率的なプログラミングのための新しい定跡


Accelerated C + + Accelerated C 十 十 Andrew Koenig and Barbara. E. 、褒00 C + + ー - e S e ⅱ e s 効 率 的 な プ ロ グ ラ ミ ン グ の た め の 新 し い 定 跡 ア ン ド リ ュ ー ・ コ ー ニ グ バ ー バ ラ ・ E ・ ム ー Pearson Education Japan ピ ア ソ ン ・ エ デ ュ ケ ー シ ョ ン

Two Scoops of Django Best Practices for Django 1.8


Co 〃 〃 倉 A Few Words From Audrey Roy GreenfeId I first discovered Python in a graduate class at MIT in 2005. ln less than 4 weeks ofhomework assignments, each student built a voice-controlled system for navlgating between rooms in Stata Center, runmng on our HP iPaqs running Debian. I was in awe ofPython and wondered why it wasn't used for everything. I tried building a web application with Zope but struggled with it. A couple of s passed, and I got drawn into the Silicon le メ tech startup scene. I wrote graphics libraries in C and desktop applications in C + + for a startup. At some point' I le that job and picked up painting and sculpture. Soon I was drawing and painting frantically for art shOWS, co-directing a 140-person art ShOW, and managmg a series Of real estate renovations. realized that I was doing a 10t at once and had to optimize. Naturally, I turned to Python and began writing scripts to generate some of my twork. was when I rediscovered the joy of working with Python. Many friends from the Google App Engine, SuperHappyDevHouse, and hackathon scenes in Si1icon Valley inspired me to get into l)jango.%rough them and through various freelance propcts and partnerships I discovered how powerful Django was ・ Before I knew it, I was attending PyCon 2010 , where I met my husband Daniel Roy Greenfeld. We met at the end ofJames Bennett's "Django ln Depth" tutorial, and now this chapter in our lives has come ん Ⅱ circle with the publication ofthis book. Django has brought more joy to my li 応 than I thought was possible with a web framework. My goal with this book is to give you the thoughtful guidance on common Django development practices that are normally left unwritten ()r implied), SO that you can get past common hurdles and experience the joy ofusing the Django web framework for your projects ・ XXVZZZ

C++ In Depth Series Accelerated C++ 効率的なプログラミングのための新しい定跡


本 書 の 内 容 に 関 す る ご 質 問 は 、 小 社 出 版 部 宛 ま で 必 ず 書 面 に て お 送 り く だ さ い 。 電 話 に よ る 内 容 の お 問 い 合 わ せ は ご 容 赦 く だ さ い 。 ま た 本 書 の 範 囲 を 超 え る ご 質 問 に つ き ま し て は お 答 え で き か ね る 場 合 も あ り ま す の で 、 あ ら か じ め ご 承 知 お き く だ さ い 。 C + + 旧 Depth Series AcceIerated C + + 効 率 的 な プ ロ グ ラ ミ ン グ の た め の 新 し い 定 跡 ア ン ド リ ュ ー ・ コ ー ニ グ / バ ー ノ ヾ ラ ・ E ・ ム ー 2009 年 9 月 30 日 初 版 第 8 刷 発 行 2001 年 12 月 20 日 初 版 第 1 刷 発 行 ■ 著 者 ー 訳 者 ■ 発 行 人 ■ 発 行 所 ・ 印 刷 十 製 本 .. 小 林 健 一 郎 プ レ ン ダ ン ・ デ ラ ハ ン テ ィ 株 式 会 社 ピ ア ソ ン ・ エ デ ュ ケ ー シ ョ ン 〒 166-0003 出 版 営 業 部 三 美 印 刷 株 式 会 社 東 京 都 杉 並 区 高 円 寺 南 2-44-5 電 話 ( 03 ) 5929-6050 FAX ( 03 ) 3 引 4 ー 8169 http://www.pej-hed.jp 本 書 の 内 容 を 、 い か な る 方 法 に お い て も 無 断 で 複 写 、 転 載 す る こ と は 禁 じ ら れ て い ま す 。 Translation copyright ◎ 2001 by PEARSON EDUCATION JAPAN Original English language title: AcceIerated C + + : PracticaI Programming by Example, First Edition by Andrew Koenig and Barbara E. M00. Copyright ◎ 2000 by AT&T, lnc. , and Andrew Koenig and Barbara E. M00 AII Rights Reserved. Published ト メ arrangement with the original publisher, ADDISON WESLEY LONGMAN,a pearson Education Company ・ Printed ⅲ Japan ISBN 4-89471-422-1

Two Scoops of Django Best Practices for Django 1.8


3.3. ・ Sa ア ん 鑽 ツ “ / カ 0 products/ profites/ ratings/ static/ temptates/ c on fi g/ init-„-. py setti ngs/ urts.py wsgl ・ PY Let's do an in-depth review of this layout. As you can see, in the “ 4 襯 ra 石 れ 学 “ が di- rectory, which is the く r 学 ワ ー r わ , we have the following files and directories. We describe them in the table below: FiIe or Directory Purpose Lists the files and directories that Git should ignore. (This file is different fo 「 Othe 「 version control systems. FO 「 example, if are using Mercurial instead, you'd have an. igno 肥 e. ) Develope 「 -facing project documentation. You'll 「 ead mo 「 e about this in chapter 25 , Documentation. Contains simple deployment tasks and macros. Fo 「 more complex deployments you maywantto 「 elyontools like lnvoke paver 0 「 Fabric. A list of Python packages requi 「 ed by your project, including the Django 1.8 package. You ・ llread more about this in ch 叩 ter 21 , DjangoIsSecretSauce: Third-PartyPackages. The く django=project-root> of the project. TabIe 3.1 : Repository Root Files and Directories . gitignore README.rst and docs/ Makefile requirements.txt た e ( 肥 am gs, / When anyone visits this project, they are provided with a high-level view of the project. We've found that this allows us to work easily with other developers and even non-developers. For 25

When Life is Linear From Computer Graphics to Bracketology


68 When Life is Linear correlation, we may not have found that change in one varlable causes a change ⅲ another. As is Often the case, math can be a powerful tOOl. Yet, one must wield it carefully and not overestimate its abilities. lfwe see that tWO phenomenon are correlated, we dO not know why or that one causes the Other. ln a similar way, finding a least squares fit tO a set Of data may approximate the data but it does not make a definitive claim about the future. lt may but dynamlcs can change. For instance, will 0 m c runners continue tO decrease their times at the rate we've seen? Possibly. But, we may alSO find that the rates plateau and possibly continue tO decrease, but at a much slower rate. Time will tell. Either way, the mathematics Of this section aided us in understanding data and gaimng insights that sometimes foster more questions. Between the last and current chapters, we've lOOked at solving 図 x = b AS we proceed through the remaming ch 叩 ters, we'll continue tO explore 叩 plications 0f algebra with matnces. We'll also see that linear algebra involves much more than solving a linear system. For example, in the next chapter, we discuss a special type Of vector and later, when we discuss data analytics in more depth, we'll see how computing this type 0f vector in the context of modeling the World Wide Web helped Goog 厄 become a billion dollar business.

Two Scoops of Django Best Practices for Django 1.8


C み 4 27. ・ . Q ゾ 4 〃 g Secret 立 〃 化 . ・ 耘 2 り 2 ん g お For supporting python 2.7 and 3.3 + , Twine makes universal wheels when the optional 記 ・ 亟 ・ file is at the same level as れ ア ッ and includes this snippet: Resources: 1 [wheet] # setu p 記 fg EXAMPLE 21 、 8 2 6 https://alexgaynor.net/[email protected]/oct/19/security¯process¯open¯source¯projects/ open source project: python, and pypy developer Alex Gaynor has an incredibly useful article for maintainers of any We discuss security in-depth in chapter 26 , & 覦 召 ぉ / pra は . However' core DjangO' 21.12.6 FoIIow G00d Security Practices lffor no other reason, this is an excellent reason tO include tests in your project. in a virtualenv that contain Django's latest release. is a major l)jango release. When this happens it's very important to run our package's test suite Every once in awhile, Django is updated with a minor release. Approximate1Y once a year there 21.12.5 Upgrade the package t0 New Versions 0f Django Advocacy http: //pythonwheels. com/ Documentation http: //wheel. readthedocs.org/ Whee1PackageonPyPI https: //PYPi ・ PYthon.org/pypi/wheel Specification: PEP427 http: //www.python.org/dev/peps/[email protected]/

Software security. building security in


50 C わ 4 々 右 催 2 A 尺 な た M の g ビ 川 e お ビ ル 0 黻 importance, a subsystem may reside in may be up Of multiple components. The importance Of each subsystem is assessed in terms 0f the identified business goals. AII subsystems are subsequently prior- itized based on the identified business goals, and a decision IS made based on the scope of the RMF project about the depth 0f the analysis that will be conducted against each subsystem. This approach goes hand-in-hand with the concept 0f risk management, as the depth 0f the analysis 0f any subsys- tem depends on the importance 0f the subsystem, and the analyses 0f differ- ent subsystems is likely t0 shed light on the quality and security 0f the software system in general. At the end Of the research activlties, the risk posture Of the entire system is examined based on the results obtained for each Of the subsystems and their interactions. Knowledge and experience with analysis Of similar sys- tems is extremely helpful in this process. 5 During performance 0f this research, analysts generate research notes and gain a general understanding Of the business context, hOW the target products work, and the role that software plays in the final product. ldentifying the Business and Technical Risks The identification Of business risks provides a necessary foundation that allows software risk (especially its impact component) t0 be quantified and described in business terms. Business risk identification helps tO define and steer use Of particular technical methods for extracting, and mit- igating software riSk given varlOLIS SOft 、 artifacts. DeveIoping R な Q リ け 0 0 耘 preliminary research results should be organized SO that an initial set Of business risks is identified. At this point, developing a set Of risk questions tO ask about the project is an lmportant step. These questions should address わ 〃 〃 ss risks (). g. , motivation, market, resource, schedule, people, facili- ties, budget, contracts, program interfaces), 々 0 / e は risks (). g. , development process, development system, management methods, work environment), and 々 rod 〃 け risks (). g. , technical defects, design flaws bugs issues with lan- guages and platforms ). Particular effort should be made t0 address questions regarding risk indicators, the likelihood that risks may occur, and business impact 5See Chapter 11 for a discussion of the kinds of knowledge usefulto software security.

Surreptitious software obfuscation watermarking and tamperproofing for software protection


184 Program Analysis Algorithm 53 Overview of AIgorithm RECG. X is a stripped executable file. DECOMPILE ( X) : goto m achine code tests an d bran ches with i f (a) Perform a reaching definitions data flow analysis on condition codes and replace 7. For each basic block in G recover statements: 6. Optimize G by removrng Jumps-to-Jumps. 5. Replace known idioms with higher-level constructs. 4. Remove any functions from G whose signatures match those in szgs. con trol flow gr 叩 h G. う . Disassemble the text segment and construct a call graph and for every function a library function signatures for this compiler. 2. Heuristically determine the compiler that generated X. Let be the set of known 1. Parse the executable 石 le X and recover the text segment and the entry pornt main. Z : cmp1 尸 , 〃 〃 ′ 〃 ↓ ノ ・ : brg lab ノ : if 尸 > z goto lab (b) Remove a temporary register / 戸 by replacing its use with its symbolic contents. First perform a definition-use data flow analysis to determine the number of uses Of / 2 and then an interprocedural live register data flow analysis to determine registers that are live at entrance and exit of the block. Finally, perform ル ル 4 4 み 立 ″ 4 / あ 〃 tO eliminate / 戸 and its definition: ↓ / : add / 2 , リ ノ : cmpi / 戸 十 , z (c) Replace calls to library functions in 立 with calls to the corresponding symbolic name: / : call ノ ノ Z : ca11 〃 4 / ″ 8. Classify nodes in G by calling RESTRUCTURELOOPS(G) and RESTRUCTUREIFS(G) in Figure 3.4 182 and Figure .5 18 名 respectively. 9. Traverse G and build an abstract syntax tree. For a basic block marked as being the head of a control structure, traverse its body depth first, i. e. , until its follow node is reached, and then continue with the follow node. 10. Traverse the abstract syntax tree and emit source code.

月刊 C MAGAZINE 1992年12月号


Fig. 16 プ ロ フ ァ イ ル し た 結 果 0. 0 0.0 0.0 3918.713 0.0 1058. 278 48.758 284.699 418.222 131.308 127. 164 39.9 794. 799 794. 799 22.660 133. 104 133. 104 195. 512 6579. 536 14.3 57.767 1640.785 85.309 104.717 0. 1 450.908 64.094 226.815 T0taI time: 42915.710 Program Statistics Wed 0ct 14 15 : 36 : 40 1992 Date: Profi le: Function timing, Microsoft PLIST Version 1.20.002 milliseconds sorted by function name. Time outside of functions: 11.223 mi 11 iseconds CaII depth: 7 Total functions : 57 Total hits: 426 Function coverage: 43.9 % M0duIe Statistics for b:}msc}samples#graphics#chrtdemo Time in module: 42904.487 milliseconds Percent of time in module: 100.0 % ModuIe function coverage: 43.9 % Hits in module: 426 Functions in module: 57 . exe Hit count Funct i on 特 集 日 本 版 断 c 几 十 十 了 し た ら , PWB 用 の . MXT フ ァ イ ル を PW 版 て 、 は プ ロ フ ァ イ ラ の イ ン ス ト ー ル が 完 よ う か 。 の 完 全 サ ポ ー ト が 実 現 す る の て 、 は な い て 、 し 次 期 バ ー ジ ョ ン の プ ロ フ ァ イ ラ て 、 は C 十 十 あ り ま せ ん 。 ン グ を 発 生 す る 場 合 が あ り ま す が , 問 題 は ポ ー ト し て い な い の て 、 , 解 析 中 に ウ ォ ー な お , こ の プ ロ フ ァ イ ラ は C 十 十 を 完 全 サ ン が 行 わ れ ま す 。 の よ う な フ ァ イ ル 構 成 て 、 イ ン ス ト レ ー シ ョ ル ト の イ ン ス ト ー ル を 行 っ た 場 合 , Fig. 15 イ ス ク て 、 供 給 さ れ て い る か ら て 、 す 。 デ フ ォ せ ん 。 MS-C7 と プ ロ フ ァ イ ラ は , 別 々 の デ [ 70 の 全 貌 マ ニ ュ ア ル が な い の て 、 , 利 用 は す べ て PW た が , そ れ 以 外 て 、 は 問 題 な く 利 用 て 、 き ま し B デ ィ レ ク ト リ に コ ヒ 。 ー す る 必 要 が あ り ま し Func 0. 000 0. 000 0. 000 0. 000 51. 766 0.361 0. 282 0. 022 0. 000 0. 000 2. 121 0.005 0. 000 0. 0 圓 0. 圓 3 0. 616 0. 圓 9 0. 000 0. 000 0. 000 0. 000 0. 000 0. 000 0. 000 0. 000 1. 976 0.000 0. 008 0. 000 6.120 0. 000 7.317 0.000 0.000 0. 000 0.000 0.000 0.144 0.000 0.000 0. 圓 0 0.000 0.000 0. 000 0. 000 0. 000 15468.811 1543. 802 6125. 841 17101. 839 Func + Chi ld Time 36. 1 18173.587 42354. 957 17474. 515 15468.811 0.000 0.0 圓 0.000 0.000 0.000 0. 圓 0 0.000 0.000 0.000 0.000 0. 圓 0 0.000 0.000 7.317 0.000 6.120 0.000 0.008 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 42904. 487 100.0 0. 009 0. 003 0. 000 0. 000 0. 圓 5 0.000 0. 圓 0 0.000 0.000 0.000 0.000 0 Axes (chrtopt. c : 83 ) 0 Axis (chrtopt. c : 106 ) 0 AxisRange (chrtopt. c: 177 ) 0 AxisScale (chrtopt. c: 204 ) 0 AxisTics (chrtopt. c : 271 ) 0 BlankMenu (chrtsupt. c : 32 ) 0 Border (chrtopt. c : 313 ) 0 ChangeTypeface (chrtopt. c : 363 ) 1 ChartOptions (chrtdemo. c : 119 ) 42.4 98. 7 40. 7 15. 3 36. 1 0 ChartType (chrtdemo. c: 168 ) 0 ChartWindow (chrtopt. c : 433 ) 0 ChooseFont (chrtopt. c : 411 ) 0 ClearData (chrtdemo. c : 21 の 0 ClrForm (chrtsupt. c : 6 の 5 CIrHelp (chrtsupt. c : 74 ) 0 DataWindow (chrtopt. c : 471 ) 7 DefaultData (chrtdemo. c: 238 ) 1 Demo (chrtdemo. c : 335 ) 0 ErrorMsg (chrtsupt. c : 87 ) 1 FindVideoMode (chrtdemo. c : 487 ) 0 Font0ptions (chrtopt. c: 506 ) 5 Help (chrtsupt. c: 11 の 1 lnitial ize (chrtdemo. c : 497 ) 0 InputCh (chrtsupt. c : 133 ) 0 InputFIoat (chrtsupt. c: 192 ) 0 lnputlnt (chrtsupt. c: 168 ) 0 InputStr (chrtsupt. c: 212 ) 0 InRange (chrtsupt. c : 259 ) 0 Justify (chrtopt. c : 548 ) 0 Legend (chrtopt. c : 57 の 0 Legend 円 ace (chrtopt. c : 651 ) 1 main (chrtdemo. c: 101 ) 1 MainMenu (chrtdemo. c: 544 ) 5 Menu (chrtsupt. c : 282 ) 2 PopTitle (chrtsupt. c : 346 ) 243 PrintAt (chrtsupt. c : 361 ) 31 PrintChar (chrtsupt. c : 379 ) 2 PushTitIe (chrtsupt. c : 393 ) 0 Reset0ptions (chrtdemo. c : 622 ) 0 ScreenMode (chrtopt. C:679) 1 SetDisplaYCOIors (chrtsupt. c : 404 ) 1 SetGraphMode ( chr tdemo. c : 643 ) 2 ShowAxisType (chrtdemo. c : 739 ) 1 ShowChartData (chrtdemo. c : 668 ) 0 ShowError (chrtdemo. c : 897 ) 0 ShowFontInf0 (chrtdemo. c : 772 ) 1 ShowLegendType (chrtdemo. c: 794 ) 1 ShowSampleData (chrtdemo. c : 812 ) 6 ShowTitIeType (chrtdemo. c : 859 ) 3 ShowWindowType (chrtdemo. c : 878 ) 89 SprintAt (chrtsupt. c : 424 ) 0 TitIeOpt (chrtopt. c : 744 ) 0 TitIes (chrtopt.c:781) 10 ViewChart (chrtdemo. c : 954 ) 0 Windows (chrtopt. c : 81 の 0 WindowSize (chrtopt. c : 838 ) 5 WrtForm (chrtsupt. c : 443 ) B 上 か ら と な り ま し た が , コ マ ン ド ラ イ ン か ら の 利 用 も 可 能 て 、 す 。 ュ ー ザ が プ ロ フ ァ イ ラ を イ ン ス ト ー ル す る と き に , ひ と つ だ け 気 が っ く 点 が あ る と 田 い ま す 。 そ れ は , プ ロ フ ァ イ ラ が OS/2 を じ 、 サ ポ ー ト し て い る 点 て 、 す 。 OS / 2 最 後 の 名 残 と 思 っ て 見 て み ま し よ う 。 Fig. 16 が プ ロ フ ァ イ ル し た 結 果 て 、 す 。 プ ロ フ ァ イ ラ は ,Table 5 に 示 す い ず れ か の 項 目 を プ ロ フ ァ イ ル し ま す 。 し た が っ て , 目 的 を も た ず に プ ロ フ ァ イ ル を す る と , 時 間 の ム ダ に な っ て し ま い ま す が , ガ べ レ ッ シ な ど を う ま く 使 え ば , 大 規 模 な プ ロ グ ラ ム の デ バ ッ グ を 支 援 す る こ と も 可 能 に な り ま す 。 前 出 の p ー code を 使 う 場 合 に は , タ イ ミ ン グ を 使 っ て 関 数 の 使 用 頻 度 を 計 測 し て か ら 最 適 化 す れ ば よ い て 、 し よ う 。 な お プ ロ フ ァ イ ル に は , デ バ ッ グ 情 報 が 必 要 に な り ま す 。 「 プ ロ グ ラ ミ ン グ 言 語 C 第 2 版 』 , 共 立 出 版 TANSI C 言 語 辞 典 』 , 技 術 評 論 社 fProgramming TechniquesJ , Microsoft 特 集 日 本 版 Mic 「 0S0 代 C/C 十 十 ve 「 .7.0 の 全 貎 59 [ 参 考 文 献 ]

Surreptitious software obfuscation watermarking and tamperproofing for software protection


92 Methods of Attack and Defense every drawer until your secret password has been uncovered. scenarro makes an mportant point: ile covermg is easy for the defender (she just has to find something big enough tO cover the secret with) it's harder for the attacker, since he has tO go through ve ヴ object in the envlronment to see if it covers the secret: Your boss has tO 100k under every object in the envrronment to see if it covers contraband reading material, birds have to dig everywhere along the beach to find where the turtle eggs are hidden, the cops have t0100k inside every drawer for your password, and SO on. TO make our point, the examples in this sectlon are all idealized. ln pracuce, a defender may leave behind clues (such as scents or tracks, in the case of the turtle scenario) that make life easier for the attacker. A turtle species that lays their eggs on the same spot on the same beach, year after year, will face extlnction once predators are clued in tO this behavior. Unless, Of course, the turtles realize the threat and modify their defenses (using other defense primitives you'll soon see) to counter the attacks. lt's often easy to apply the cover transformation multiple times for greater defense-in-depth. For example, after putting the book inside the P / み の magazine, you could sit on them bOth, requlring the boss tO perform two uncoverlng operations tO recover the bOOk: 0 8 working="not much't ang 2 て = 5 ① ang er>70 : you ' re fired ! t itl e=" PI ayboy" O ti tle= "Ki t t ens 第 コ 0 working= ” not much'i titIe="P1ayboy" C 0 tit1eg"Kittenst' [email protected] ange て > 7 ① you're fired! lt may initially not be obvious what the analogy of one object covering another ⅲ the software world is. ln the real world, you cover an object when you put it inside another. ln the software world, you can cover a file or some data by puttlng it inside another file. For example, when mail systems initially began scanning attachments for viruses, virus writers responded by zipping (and occasionally encrypting) the virus before emailing it. The zip-file serves as a cover for the virus itself: