Something Borrowed: A Novel. La ya comme ceci sur personnes quel gagner lu la carnet. PDF Formatted 8. Eh bien! Comment obtenir ce livre? Obtenir ce livre est simple et pas fatiguant. Ce site est disponible avec des livres fructueux et gratuits en ligne. Menu Home. Rachel White is the consummate good girl. A hard-working attorney at The novel concerns morals regarding friends and relationships. It addresses the stigma against single women in their thirties and the pressure that society places on them to get married.
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Log in with Facebook Log in with Google. Remember me on this computer. Enter the email address you signed up with and we'll email you a reset link. Need an account? Click here to sign up. Download Free PDF. A short summary of this paper. Download Download PDF. Translate PDF. Anton Spraul. All rights reserved. No part of this work may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopying, recording, or by any information storage or retrieval system, without the prior written permission of the copyright owner and the publisher.
Other product and company names mentioned herein may be the trademarks of their respective owners. Rather than use a trademark symbol with every occurrence of a trademarked name, we are using the names only in an editorial fashion and to the benefit of the trademark owner, with no intention of infringement of the trademark. While every precaution has been taken in the preparation of this work, neither the author nor No Starch Press, Inc. I must also thank Bill Pollock for his decision to sign me up in the first place—I hope he is as pleased with the result as I am.
The folks at No Starch have been unfailingly kind and helpful in their correspondence with me. I hope one day to meet them in person and see to what degree they resemble their cartoon avatars on the company website.
Dan Randall did a wonderful job as technical editor. His numerous sug- gestions beyond the technical review helped me strengthen the manuscript in many areas. On the home front, the most important people in my life, Mary Beth and Madeline, provided love, support, and enthusiasm—and, crucially, time to write. The techniques and strategies described in this book were developed through our joint efforts.
I have taught programming for over 15 years, and most of my students would have fit this description at some point in their instruc- tion.
We will call the missing skill problem solving, the ability to take a given problem description and write an original program to solve it. Not all pro- gramming requires extensive problem solving. But all programs require problem solving at some point, and all good programmers can solve problems. Problem solving is hard. For these select few, high-level ideas are effortlessly translated into source code. In the worst cases, they give up programming entirely, convinced that they can never be programmers, that the only good programmers are those born with an innate gift.
Why is learning to solve programming problems so hard? You head into your garage and look for something, or a combination of things, that will enable you to remove the branch from the gutter.
Is there some way to extend the ladder? Is there something you can hold at the top of the ladder to grab or dislodge the branch? Maybe you could just get on the roof from another place and get the branch from above. Believe it or not, when you design an original program, your mental process is quite similar to that of the person figuring out how to remove the branch from the gutter and quite different from that of a person debugging an existing for loop.
Most programming books, though, focus their attention on syntax and semantics. In essence, most programming books for beginners teach how to read a program, not how to write one.
Such books can be quite valuable as time savers, but not as a path toward learning to write original code. Think about cookbooks in the original sense. Although great cooks own cookbooks, no one who relies upon cookbooks can be a great cook. A great cook understands ingredients, prepa- ration methods, and cooking methods and knows how they can be combined to make great meals.
All a great cook needs to produce a tasty meal is a fully stocked kitchen. In the same way, a great programmer understands language syntax, application frameworks, algorithms, and software engineering princi- ples and knows how they can be combined to make great programs.
Give a great programmer a list of specifications, turn him loose with a fully stocked programming environment, and great things will happen. The journey from initiation to enlightenment can be filled with frustration, and too many who start the journey never reach the destination.
Instead of learning by trial and error, you can learn problem solving in a systematic way. You can learn techniques to organize your thoughts, procedures to discover solutions, and strategies to apply to certain classes of problems. By studying these approaches, you can unlock your creativity. Make no mistake: Programming, and especially prob- lem solving, is a creative activity. Creativity is mysterious, and no one can say exactly how the creative mind functions.
Yet, if we can learn music composi- tion, take advice on creative writing, or be shown how to paint, then we can Download from Wow! This book is about helping you become the programmer you are meant to be. My goal is for you and every other reader of this book to learn to system- atically approach every programming task and to have the confidence that you will ultimately solve a given problem. When you complete this book, I want you to think like a programmer and to believe that you are a programmer.
About This Book Having explained the necessity of this book, I need to make a few comments about what this book is and what it is not. Chosen Topics The topics covered in this book represent areas in which I have most often seen new programmers struggle.
They also present a broad cross-section of different areas in early and intermediate programming. Instead, I would work through the entire book, skipping material only if you lack the prerequisites needed to follow the discussion. Programming Style A quick note here about the programming style employed in this book: This book is not about high-performance programming or running the most com- pact, efficient code.
The style I have chosen for the source code examples is intended to be readable above all other considerations. Some aspects of programming style will be covered in this book—but larger issues, like what should or should not be included in a class, not small issues, like how code should be indented.
As a developing programmer, you will of course want to employ a consistent, readable style in all of the work you do. Exercises The book includes a number of programming exercises.
The exercises provide opportunities for you to apply the concepts described in the chapters. Whether you choose to try any of the exercises is, of course, up to you, but it is essential that you put these concepts into practice.
Simply reading through the book will accomplish nothing. Remember that this book is not going to tell you exactly what to do in each situation. In applying the techniques shown in this book, you will develop your own ability to discover what to do. Furthermore, growing your confidence, another primary goal of this book, requires success. Lastly, programming exercises should be fun. You should think of this book as an obstacle course for your brain.
Obstacle courses build strength, stamina, and agility and give the trainer confidence. Object-oriented programming is so common now that it could not be omitted from a discussion on problem solving, but many funda- mental problem-solving concepts can be discussed in strictly procedural programming terms, and doing so simplifies both the code and the discus- sion.
When people use the term in ordinary conversation, they often mean something very different from what we mean here. If your Honda Civic has blue smoke coming from the tailpipe, is idling roughly, and has lost fuel efficiency, this is a problem that can be solved with automotive knowledge, diagnosis, replacement equipment, and common shop tools.
Problem solved. Problems include constraints, unbreakable rules about the problem or the way in which the problem must be solved. With the broken-down Civic, one of the constraints is that you want to fix the current car, not purchase a new car. The constraints might also include the overall cost of the repairs, how long the repair will take, or a requirement that no new tools can be pur- chased just for this repair. When solving a problem with a program, you also have constraints.
Com- mon constraints include the programming language, platform does it run on a PC, or an iPhone, or what? For programmers, then, we can define problem solving as writing an original program that performs a particular set of tasks and meets all stated constraints.
Beginning programmers are often so eager to accomplish the first part of that definition—writing a program to perform a certain task—that they fail on the second part of the definition, meeting the stated constraints. I call a program like that, one that appears to produce correct results but breaks one or more of the stated rules, a Kobayashi Maru.
If that name is unfamiliar to you, it means you are insufficiently familiar with one of the touchstones of geek culture, the film Star Trek II: The Wrath of Khan. The film contains a sub- plot about an exercise for aspiring officers at Starfleet Academy.
The cadets are put aboard a simulated starship bridge and made to act as captain on a mission that involves an impossible choice. Toward the end of the film, we discover that Captain Kirk modified the simulation to make it actually winnable. Kirk was clever, but he did not solve the dilemma of the Kobayashi Maru; he avoided it. In some cases, they do so accidentally. My solution only works if there are a hundred data items or fewer.
In the worst cases I have seen, the programming student has paid someone else to write the program. Regardless of the motivations, we must always be diligent to avoid the Kobayashi Maru. Classic Puzzles As you progress through this book, you will notice that although the particu- lars of the source code change from one problem area to the next, certain patterns will emerge in the approaches we take. This is great news because this is what eventually allows us to confidently approach any problem, whether we have extensive experience in that problem area or not.
If we recognize that a feature of problem A is analogous to a feature of problem B and we have already solved problem B, we have a valuable insight into solving problem A. The Fox, the Goose, and the Corn The first classic problem we will discuss is a riddle about a farmer who needs to cross a river.
You have probably encountered it previously in one form or another. A farmer with a fox, a goose, and a sack of corn needs to cross a river. The farmer has a rowboat, but there is room for only the farmer and one of his three items. Unfor- tunately, both the fox and the goose are hungry. The fox cannot be left alone with the goose, or the fox will eat the goose.
Likewise, the goose cannot be left alone with the sack of corn, or the goose will eat the corn. How does the farmer get everything across the river? The setup for this problem is shown in Figure If you have never encountered this problem before, stop here and spend a few minutes trying to solve it. If you have heard this riddle before, try to remember the solution and whether you were able to solve the riddle on your own.
The boat can carry one item at a time. The fox cannot be left on the same shore as the goose, and the goose cannot be left on the same shore as the sack of corn. On the first trip, if the farmer takes the fox, the goose would be left with the sack of corn, and the goose would eat the corn.
Likewise, if the farmer took the sack of corn on the first trip, the fox would be left with the goose, and the fox would eat the goose. Therefore, the farmer must take the goose on the first trip, resulting in the configuration shown in Figure From this step, however, all further steps appear to end in failure.
So far, so good. But on the second trip, the farmer must take the fox or the corn. Whatever the farmer takes, however, must be left on the far shore with the goose while the farmer returns to the near shore for the remaining item. This means that either the fox and goose will be left together or the goose and corn will be left together.
Because neither of these situations is acceptable, the problem appears unsolvable. Again, if you have seen this problem before, you probably remember the key element of the solution. The farmer has to take the goose on the first trip, as explained before. Instead of leaving the fox with the goose, though, the farmer takes the goose back to the near shore. Then the farmer takes the sack of corn across, leaving the fox and the corn on the far shore, while returning for a fourth trip with the goose.
The complete solution is shown in Figure This puzzle is difficult because most people never consider taking one of the items back from the far shore to the near shore.
With that suggestion in plain sight, more people would figure out the problem. This illustrates an important principle of problem solving: If you are unaware of all possible actions you could take, you may be unable to solve the problem. We can refer to these actions as operations. By enumerating all the possible opera- tions, we can solve many problems by testing every combination of opera- tions until we find one that works.
More generally, by restating a problem in more formal terms, we can often uncover solutions that would have other- wise eluded us. The key constraints here are: 1. The farmer can take only one item at a time in the boat.
The fox and goose cannot be left alone on the same shore. The goose and corn cannot be left alone on the same shore. This problem is a good example of the importance of constraints. If we remove any of these constraints, the puzzle is easy. If we remove the first con- straint, we can simply take all three items across in one trip. Even if we can take only two items in the boat, we can take the fox and corn across and then go back for the goose.
If we remove the second constraint but leave the other constraints in place , we just have to be careful, taking the goose across first, then the fox, and finally the corn. Therefore, if we forget or ignore any of the constraints, we will end up with a Kobayashi Maru. There are various ways of stating the oper- ations for this puzzle. We could make a specific list of the actions we think we can take: 1.
Operation: Carry the fox to the far side of the river. Operation: Carry the goose to the far side of the river. Operation: Carry the corn to the far side of the river. Remember, though, that the goal of formally restating the problem is to gain insight for a solution. Instead, we should try to make operations generic, or parameterized.
Operation: Row the boat from one shore to the other. Operation: If the boat is empty, load an item from the shore. Operation: If the boat is not empty, unload the item to the shore. The inherent difficulty of the puzzle will have been sidestepped through the formal restatement of constraints and operations. Restating the problem in a more formal manner is a great technique for gaining insight into a problem.
Many programmers seek out other program- mers to discuss a problem, not just because other programmers may have the answer but also because articulating the problem out loud often triggers new and useful thoughts. Restating a problem is like having that discussion with another programmer, except that you are playing both parts.
The broader lesson is that thinking about the problem may be as produc- tive, or in some cases more productive, than thinking about the solution.
In many cases, the correct approach to the solution is the solution. Ini- tially, the grid is in a jumbled configuration. The goal is to slide the tiles to place the grid in an ordered configuration, from tile 1 in the upper left. The goal of this problem is shown in Figure A suggested starting configuration is shown in Figure The empty square represents the empty space into which an adjacent tile may slide.
The difficulty in that problem came from overlooking one of the possible operations. From any given configura- tion, up to four tiles may be adjacent to the empty space, and any of those tiles can be slid into the empty space. That fully enumerates all possible operations. The difficulty in this problem arises instead from the long chain of oper- ations required by the solution.
A series of sliding operations may move some tiles to their correct final positions while moving other tiles out of position, or it may move some tiles closer to their correct positions while moving oth- ers farther away. Many people who attempt a sliding tile puzzle simply move the tiles around randomly, hoping to hit upon a configuration from which a path to the goal configuration can be seen. Nevertheless, there are strategies for sliding tile puzzles.
The goal is to slide the tiles to place the grid in an ordered configuration, from tile 4 in the upper left. You may have noticed that our five tiles are numbered 4 through 8 instead of 1 through 5. The reason for this will become clear shortly. Although this is the same basic problem as the sliding eight, it is much easier with only five tiles. Try the configuration shown in Figure If you play around with these tiles for just a few minutes, you will probably hit upon a solution.
From playing around with small-count tile puzzles, I have 6 8 developed a particular skill. It is this one skill, cou- pled with an observation we will discuss shortly, that I use to solve all sliding tile puzzles.
Figure illustrates the smallest possible train of four positions. From the first config- uration, the 1 can slide into the empty square, the 2 can slide into the space vacated by the 1, and finally the 3 can slide into the space vacated by the 2.
This leaves the empty space adjacent to the 1, which allows the train to continue and, thus, the tiles to be effectively rotated anywhere along the train path.
Although none of the tiles in this grid is in its correct final position, some tiles are adjacent to the tiles they need to border in the final configuration. For example, in the final configuration, the 4 will be above the 7, and currently those tiles are adjacent. As shown in Figure , we can use a six-position train to bring the 4 and 7 to their correct final positions. When we do that, the remaining tiles are nearly correct; we just need to slide the 8 over.
From there, a single tile slide results in the goal, configuration 3. So how does this one technique allow us to solve any sliding tile puzzle? We can use a six-position train to move the adjacent 1 and 2 tiles so that the 2 and 3 are adjacent, as shown in Figure This puts 1, 2, and 3 in adjacent squares. With an eight-position train, we can shift the 1, 2, and 3 tiles to their correct final positions, as shown in Figure Notice the positions of tiles 4—8.
This is the key observation. Having placed tiles 1—3 in their correct positions, we can solve the rest of the grid as a separate, smaller, and easier puzzle.
Note that we have to solve an entire row or column for this method to work; if we put tiles 1 and 2 in the correct positions but tile 3 is still out of place, there is no way to move something into the upper-right cor- ner without moving one or both of the other upper-row tiles out of place. This same technique can be used to solve even larger sliding tile puzzles. At that point, the problem has been reduced to an 8-tile puzzle.
Lessons Learned What lessons can we learn from the sliding tile puzzles? The number of tile movements is large enough that it is difficult or impossible to plan out a complete solution for a sliding tile puzzle from the initial configuration. However, our inability to plan a complete solution does not prevent us from making strategies or employing techniques to systemati- cally solve the puzzle.
Often, I use a similar technique in programming. When faced with an onerous problem, I experiment with a reduced version of the problem.
These experiments frequently produce valuable insights. The other lesson is that sometimes problems are divisible in ways that are not immediately obvious. Because moving a tile affects not only that tile but also the possible moves that can be made next, one might think that a sliding tile puzzle must be solved all in one step, not in stages. Looking for a way to divide a problem is usually time well spent. When solving problems, working with a specific goal in mind is always better than random effort, whether you achieve that specific goal or not.
Sudoku The sudoku game has become enormously popular through appearances in newspapers and magazines and also as a web-based and phone-based game. Variations exist, but we will briefly discuss the traditional version.
If you have played this game before, you probably already have a set of strategies for completing a square in the minimum time. Figure An easy sudoku square puzzle Sudoku puzzles vary in difficulty, their difficulty determined by the number of squares left to be filled. By this measure, this is a very easy puzzle. As 36 squares are already numbered, there are just 45 that must be filled to complete the puzzle.
The question is, which squares should we attempt to fill in first? These rules dictate where we should begin our efforts.
The missing number in that area is 7, so we would place that in the middle square. With that value in place, note that the centermost column now has values in seven of its nine squares, which leaves only two squares remaining, each of which has to have a value not already in the column: The two missing num- bers are 3 and 9.
The constraint on this column would allow us to put either number in either place, but notice that 3 is already present in the third row and 9 is already present in the seventh row. Therefore, the row constraints dictate that 9 go in the third row of the middle column and 3 go in the sev- enth row of the middle column.
These steps are summarized in Figure Lessons Learned The main lesson from sudoku is that we should look for the most constrained part of the problem. While constraints are often what make a problem diffi- cult to begin with remember the fox, the goose, and the corn , they may also simplify our thinking about the solution because they eliminate choices.
If your goal is to minimize the amount of time it takes to find a restaurant, you should start by talking to the coworker with the most onerous restrictions. If Bob has a number of broad food allergies, for example, it would make sense to start by finding a list of restaurants where he knows he can eat, rather than starting with Todd, whose dislike of Chinese food can be easily mitigated.
The same technique can often be applied to programming problems. If you can solve part of the problem, go ahead Download from Wow! You may learn something from seeing your own code that will stimulate your imagination to solve the rest. Read carefully because the wording of this problem is a little complicated. To open the door, you have to slide the three bar-shaped Kratzz along tracks that lead from the right receptor to the left receptor, which lies at the end of the door, 10 feet away.
On each Kratzz are one or more star-shaped crystal power gems known as Quinicrys. Each receptor has four sensors that light up if the number of Quinicrys in the column above is even. An alarm goes off if the number of lit sensors is ever exactly one. The good news is that each alarm is equipped with a suppressor, which keeps the alarm from sounding as long as the button is pressed. Given all of this, how do you slide the Kratzz to open the door without activating either alarm?
For clarity, Figure shows a bad idea: Sliding the upper- most Kratzz to the left receptor causes an alarm state in the right receptor. You must slide the three Kratzz bars, currently in the right receptor, to the left receptor without setting off either alarm.
A sensor is lit when an even number of star-shaped Quinicrys appear in the column above, and an alarm sounds if exactly one connected sensor lights up. Suppressors can keep an alarm from sounding, but only for the receptor where you are standing. You just slid the upper Kratzz to the left receptor, so the right receptor is out of reach. The second sensor for the right alarm is lit because an even number of Quinicrys appears in the column above, and an alarm sounds when exactly one of its sensors is lit.
Before moving on, take some time to study this problem, and try to develop a solution. Depending on your point of view, this problem is not as hard as it looks. Seriously, think about it before moving on! Were you able to come up with a solution?
There are two possible paths to an answer here. The first path is trial and error: attempting various Kratzz moves in a methodical way and backing up to previous steps when you reach an alarm state until you find a series of moves that succeeds. The second path is realizing that the puzzle is a trick. Although the rules for the alarm are written generally, there are only so many combinations for this specific lock.
With only three Kratzz, we just have to know which combinations of Kratzz in a receptor are acceptable. We slide the middle Kratzz goose over to the left receptacle. Next, we start sliding the middle goose back to the right receptacle. Then, we slide the bottom corn to the left, and finally, we slide the middle goose to the left once again, opening the lock. Lessons Learned The chief lesson here is the importance of recognizing analogies.
Here, we can see that the Quarrasi lock problem is analogous to the fox, goose, and corn problem. If we discover that analogy early enough, we can avoid most of the work of the problem by translating our solution from the first problem rather than creating a new solution.
The story that sets up the Quarrasi problem is irrelevant, as are the names for all of the alien technology, which serve to heighten the sense of unfamiliarity. The middle Kratzz, however, interacts with the other two. General Problem-Solving Techniques The examples we have discussed demonstrate many of the key techniques that are employed in problem solving.
Always Have a Plan This is perhaps the most important rule. You must always have a plan, rather than engaging in directionless activity. By this point, you should understand that having a plan is always possible.
That will come later. Even at the beginning, though, you should have a plan for how you are going to find the solution. To be fair, the plan may require alteration somewhere along the journey, or you may have to abandon your original plan and concoct another. Why, then, is this rule so important? General Dwight D. But no army can succeed with- out planning and organization. In the same way, you must always have a plan for solving a problem.
It may not survive first contact with the enemy—it may be discarded as soon as you start to type code into your source editor—but you must have a plan. Without a plan, you are simply hoping for a lucky break, the equivalent of the randomly typing monkey producing one of the plays of Shakespeare. Lucky breaks are uncommon, and those that occur may still require a plan. Many people have heard the story of the discovery of penicillin: A researcher named Alexander Fleming forgot to close a petri dish one night and in the morning found that mold had inhibited the growth of the bacteria in the dish.
But Fleming was not sitting around waiting for a lucky break; he had been experimenting in a thorough and controlled way and thus recognized the importance of what he saw in the petri dish. If I found mold growing on something I left out the night before, this would not result in an important contribution to science. Planning also allows you to set intermediate goals and achieve them. Without a plan, you have only one goal: solve the whole problem.
Therefore, working only toward the pri- mary goal inevitably leads to frustration, as there is no positive reinforcement from your efforts until the end. Restate the Problem As demonstrated especially by the fox, goose, and corn problem, restating a problem can produce valuable results. In some cases, a problem that looks very difficult may seem easy when stated in a different way or using different terms.
Restatement sometimes shows us the goal was not what we thought it was. I once read about a grandmother who was watching over her baby granddaughter while knitting.
The grandmother tried all sorts of toys to make the pen more fun for the baby, until she realized that keeping the baby in the pen was just a means to an end. The goal was for the grand- mother to be able to knit in peace. The solution: Let the baby play happily on the carpet, while the grandmother knits inside the pen.
This is another reason why having a plan is essential. Without a plan, your only goal is to have working code, and restatement is taking time away from writing code. For example, if a problem has been assigned to you by a supervisor or an instructor , you can take your restatement to the person who assigned the problem and confirm your understanding. Also, restating the problem may be a necessary prerequisite step to using other common techniques, like reducing or dividing the problem.
More broadly, restatement can transform whole problem areas. The technique I employ for recursive solutions, which I share in a later chapter, is a method to restate recursive problems so that I can treat them the same as iterative problems. Divide the Problem Finding a way to divide a problem into steps or phases can make the problem much easier. Suppose someone initially separates the files into 4 groups of roughly equal size, A—F, G—M, N—S, and T—Z, and tells you to alphabetize the 4 groups individually and then drop them one after the other into the box.
If each of the groups contained about 25 files, then one might think that alphabetizing 4 groups of 25 is about the same amount of work as alpha- betizing a single group of If you doubt this, think of a more extreme version— compare the thought of ordering 50 groups of 2 files, which you could prob- ably do in under a minute, with ordering a single group of files.
In the same way, dividing a problem can often lower the difficulty by an order of magnitude. Combining programming techniques is much trickier than using techniques alone. For example, a section of code that employs a series of if statements inside a while loop that is itself inside a for loop will be more difficult to write—and to read—than a section of code that employs all those same control statements sequentially.
Remember that some problems, like our sliding tile puzzle, often hide their potential subdivision. But it means that the further away a writer gets from his or her own experience, the more difficult writing may be. In the same way, when programming, you should try to start with what you already know how to do and work outward from there. Once you have divided the problem up into pieces, for example, go ahead and complete any pieces you already know how to code.
Having a working partial solution may spark ideas about the rest of the problem. Also, as you may have noticed, a common theme in problem solving is making useful progress to build confi- dence that you will ultimately complete the task. By starting with what you know, you build confidence and momentum toward the goal.
A particular problem may be entirely solvable with the skills you already have or it may not, but you should fully investigate the problem using the skills already in your head before looking elsewhere. If we think of programming skills as tools and a programming problem as a home repair project, you should try to make the repair using the tools already in your garage before heading to the hardware store.
This technique follows the principles we have already discussed. It follows a plan and gives order to our efforts. When we begin our investigation of a problem by applying the skills we already have, we may learn more about the problem and its ultimate solution. Reduce the Problem With this technique, when faced with a problem you are unable to solve, you reduce the scope of the problem, by either adding or removing constraints, to produce a problem that you do know how to solve.
Suppose you are given a series of coordinates in three-dimensional space, and you must find the coordinates that are closest to each other. For example, what if the coordinates are in two-dimensional space, instead of three-dimensional space? Now the question essentially becomes, in a list of numbers, find the two numbers with the minimum absolute difference.
Or you could reduce the problem by keeping the coordinates in three- dimensional space but have only three values, instead of an arbitrary-sized series. These reductions simplify the problem in different ways. The first reduc- tion eliminates the need to compute the distance between three-dimensional points. The second reduction, by con- trast, focuses almost entirely on computing the distance between three- dimensional points but eliminates the problem of finding a minimal value in an arbitrary-sized series of values.
Great book, Something Borrowed pdf is enough to raise the goose bumps alone. Add a review Your Rating: Your Comment:. Baby Proof by Emily Giffin. Where We Belong by Emily Giffin. The Diary of Darcy J. Rhone by Emily Giffin. First Comes Love by Emily Giffin.
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