结构体在内存中的表示形式是怎么样的？
结构体在内存中和普通变量存储没有太大的区别。
首先我们看看，计算机如何读取普通变量：
普通变量例如int是占据4个字节，计算机读内存的时候会从起始地址开始读，读4个字节，按照int的规则将二进制转化为整形。所以读取普通变量我们要知道起始地址和数据类型（占据长度，解读方式）。
再看看计算机如何读取结构体变量：
结构体是自定义变量，是由多个普通变量组成的。我们读取结构体变量，实际上是读取结构体包含的数据成员。例如结构体T包含三个数据成员：char var1，int var2，long var3。计算机如果读取结构体变量 t 的数据成员var1，计算机需要知道结构体变量的地址 &t，已知这个结构体变量占据16个字节，那么从起始地址开始往后16个字节，都存储了结构体变量的数据成员。如果我们再知道数据成员var1相对于结构体起始地址的偏移，我们就可以像读取普通变量一样读取结构体数据成员。
#include<stdio.h>
#pragma pack()
#define offset(type, name) (size_t)(&(((type *)0)->name))
typedef struct Test{
char var1; //1
int var2; //4
long var3; //8
char var4; //1
}Test_t;
/*
64bit:
Test_t:
cxxx iiii //在char后面填充，使得后一个变量int从对齐参数的整数倍
llll llll
cxxx xxxx //结构体总长度必须为对齐参数的整数倍，因此在结构体尾部填充。
32bit:
Test_t:
cxxx iiii
llll cxxx
*/
int main(int argc, char** argv){
Test_t t1;
t1.var1 = 'A';
t1.var2 = 99;
t1.var3 = 999;
printf("struct->var1: %ld \n", offset(Test_t, var1));
printf("struct->var2: %ld \n", offset(Test_t, var2));
printf("struct->var3: %ld \n", offset(Test_t, var3));
printf("struct->var4: %ld \n", offset(Test_t, var4));
printf("struct: %ld \n", sizeof(t1));
return 0;
}
针对上述测试代码，我使用了GDB调试工具对程序内存进行查看。想看看结构体在内存中的表现形式是怎样的。
$ gcc -g -o struct_test struct_test.c
$ gdb
(gdb) file struct_test
(gdb) start
编译，打开gdb，在gdb中加载程序，调用main函数，创建结构体变量，此时下一步是对结构体成员赋值。
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HO3plqvreuchrLeqeV+dk6ej4qm+XlqnNEee/Z67eyGi8XxVbnTLu5wctrrMpXuv3ZzGq/znmimk6v5fVkc1b3WJnfqc32z3KqWxeJ+nfmej3ZnNU9zpxfzcp6VbcuEvXvzPV6jp4Pn+/QpTB7rnoj0cwsFsVtbKyV5iq2x+vPZnbqx1ppbuZtbNKc12/z3vNc21hX1uflNLaS956rfm+tOv0zFs2x8WptZfXj2a7ncydfqeZp3Mamas8qP2hN9OzFqrwXs3mvfjo639aOtRfTtdWp11g1zxP17+y12uPVT6+eP9ZVvzdPY16+EvXv7LXTA/y4FFq2eIryGveelfZZXo322nwnpjmtsbGIzrF9M6Y0H9XZnK41pj2TrdW66DnLjWdv3ZX1zJlaU8WiuK6jZ41Ndq28Hi8247rWuEfzWh/xemdc85rr5DtmrzdLcxqvclpjY5FshspyNq+8fFY/zB7l1Q1R3vbq2rK900qNl+uI+mfcy9uczSsvn9UPs0d5dYPNa4/NKZv3am2Np8pXov4Z9/I2Z/OqyuO7pf9N4SfxfghWfjCu/iE6er67Pf2sZ51vd87R/av+b3n/r/L083063n/gGb7mUjiMP3iUV+PZ6dmh+1y9F9bc+ZlU34mVvMfrwefwPnPl9eA83nuuvB7gLl91KQQAAICPSyEAAAC4FAIAAIBLIQAAAP7BpRAAAABcCgEAAMClEAAAAP/gUggAAAAuhQAAAOBSCAAAgH9wKQQAAACXQgAAAHApBAAAwD+4FAIAAIBLIQAAALgUAgAA4B9cCgEAAMClEHhXv379cuMAzsXPGr4Fl0LgDfFLCngtfubwDf69FI4ve8Rrwnd6ynfiqd/LV70/T339Xe9+/iN2vyOzz/Jq8ed3zL5vU1ajOa3x4sBR2ffP5iatOcvvS+EMRM+IXfkBdbxq/6e8zjvPkHnV2Z76+ivz/XnX8x+lr3v1PfDqoxkjns1/ev4ob763n8aqfBYDjtr5fl7lj399zJd+z93v27t8bmec85u/o5/w2r/x8/Ne85H3IerVeLXnE/NnGHOr2Tbv1UczqtlHXDl7uHp+5ej+n/r+ePtq7JXn4lJ4krvft3f53M445zd/R5/62se5PFGtF39n9nVPmtf6KNYV9VYzn54/as5fPYdXH82oZh9x5ezh6vmVo/u/+/sz5nt7VLGrz6WWLoUjp6K40rx9tmbO1tiYXUd1UbxaR7HMrPN6ZszWzLVXZ3M27+X0WeuiZ2vmvJoorrmsTuNefsWRXo89l4rqNN7NVXUdWV8028bt2qvz8rbG5rqO9Gais9m4XXt1mq/WHV6txuxMfba8+KxX75T3anby3rMV5Y72V0bflOWimko2o5vL1rM+imk8qo/ylU7/al5rstyKqn9lttbNvpX+Xe1LoRfXWPU8/hnVeGsvls3wanU9Y93+KBbJZmssqonqvedqHc3KaqKeTmzGd2euOmOGpTO9Z7tndIYs3p2R6e7r1Y2YxqNnb+3FvJqO3b5M9/waj5531hWvPpuZzd/NDU/Ne3GNVXm79uqnKpflhyrvsT3RjJ3Zg9fXjU0jp/noOYpV6yi2Iuqv9uqeJZrfYXuvnHVkduWll8IZszn7HMW8Gs+o68yzNN/da+rsl83s9Gs8mp31ZLEqn8Wi+Er/ijNmWDozetZYdIaVeFSb6fSMmtX9bK5aWyPviWq9+FmivbN9bW5n7Ynqs5gXn7Lc8K55L66x1bxXn8WHbJ7Kch2jP5qxO7vbl9Wt5jR2xv4dUf/d59vt81x91srSpdCj+exZYzZnn6OYV6NGftZ05lmar2qtzn7ZzJHzeDXz2cvZuOazWJXPYlF8pX/FGTMsnZk9z7XG1Uo8qs1kPSM38zv7zf6d3hVnzlJ69p3XMPujuhmv5ni8niiWza/2ftf8iHuO5odZM+t0ncVXajtG3+w9e/Yw509RjRcfVnMay3pVty4S9Y+4J6vRnNZ48cpun7Uy56w9rUN/U6g07z17/VFPFPNqpk5t1j+Nmk6d1dkvm1vtWc3StTeriu30VPGV/hVnzLB0pvds94zOsBKPaiudWav7VWep8ivOnDXZmd4e2b6dM82aTq3VPc+IZfOrvd81f3SutbqPF+/GOmzfyjl2rZ5/NaexrFd16yJR/85cr2f3fEdf15DNOPOslbf7bwp1rezszjxP1Fuxfd6MbG5Vb59tfWetsap+JRbFq1g0qxLN3Z03ROeazzama7USj2or1azxvLPf7Ov2ezUd0ezdeYP2RrOq+bMv6p81XrxDe705VT6LT++a9+Iaq/LWyj5RfHXPjPaN52iOrdNcxqutYjaf7efVVv3ePI15+UrUv7PXSs949uqVzXv10ZwqZvNe/Vl+XArHRpMWeXmtsTHv2ctZWqs1Nq45pTnvWWmfynKZ2efNnzGl+aguykfP0XrGbJ81c16NzWm+G7M5G6/oTG+GXXfZeavPulZeLout8Pp0nvestG/WdGPRjIr2ejPsepXO9J6V9s2a3diKbP8Zn89RnY3NuPVOea9mNe/V2Dq7VlnfzNvYCp0b7VHlIrNHeXWDzWuPzSmb92ptjafKV6L+GffyNmfzystXPdOsi2qjnPapqEbjZ/vjbwqvcvULOcu7nHPVp74u9Q2vUZ35er1Zr34/7/z8nvD68Vx8F/AtXnIpHD9Qk5d/gqef74h3eP+P+uTX9ir6PXn1+/mEz+/O1w98K/tzZ3k9uM7L/qYQAAAAz8WlEDjB0f9Vy/8qBgDcjUshcJKjlzouhQCAO/24FM6/rZi00OYmrcF3ePrnftf5OvtmNfw8AQDu9PtS6P1C0hi/sDC+A5OXv9ud5+vuGdXdcWYAABSXQvzQ+Zyf/l148vnG2fhZAgA8EZdC/ND5nJ/+Xdg53+jxeLW75ryz5wIAcIb0/2iiv7zmL8lJ6/D+7OebfcZZzmNn2nVUF8Xt2orid9Pz21zXU18bAOD9hZdC+8unWuMzdD7Xnc9+9fvk7TFiGvdqsvjdOmcHAOAu7qWw+wuLX2yfp/OZ7nzutiebMXJevrtvt07NPS2vdteVswEAOOqPS+HKLyt+sX2ezme6+7nPvqh/xLOaqM/q1r2SPdMTzwgA+G4/LoXZLyovxy+2z9P5THc/99nX+S51aiLdulc68noAAHiF35fC6peWzfML7TNln3kWH7HOd6IzM5rVmT90617pyOsBAOAVflwKPVocxfFZos9YP39bY9eRrEZneM9K+6Zu3at55/FiHav1AAB0uf9HEwDPxKUQAHAVLoXAG+FSCAC4CpdCAAAA5JfCV/6tBH8DAgAAcJ/wUnjHJe3Ve3IRBQAA+D/upfDOy9Kr9vb2GTFl86rKX6Fzro47zg4AAJ7sr//8L4tglCBKCvCqAAAAAElFTkSuQmCC" alt="进入main函数">
我们在赋值前查看一下此时结构体变量t1在内存的表现是怎样的。
(gdb) print &t1 #打印结构体变量t1的地址
(gdb) x/24xb &t1 #读取24次内存，每次读一个字节，以16进制的形式打印
使用print打印了结构体变量t1的地址，通过x/<n/f/u> <addr>的形式查看程序的内存，详情见以下博文。
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" alt="赋值前内存">
我们看到此时的内存杂乱无章。我们步进程序，给结构体变量var1赋值，再查看一次内存。
(gdb) step #执行下一条语句
(gdb) x/24xb &t1
(gdb) x/24db &t1 #以十进制的形式打印内存
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qXdRaHyPzVeP1pXdZZHCLzV+P1p3VZZ3GIzF+N15/WZZ3FITJ/NV5/Wpd1FofI/LN5/MOvvocGIYQQQgi5Jx/+L1pCCCGEEHJv3n7JghBCCCGE7MHjy5cv0CCEEEIIIfeEFzxCCCGEkM34cME7+lsekmdBsa9K9mwyX8cg7wyO1pc8ixdn9avwrP6u+gyu/n5mw/k5/5H5Jc+CYq/MaN9Z/mj92Yz2l+WP1u/l3QVPH9zbBIr3ajQ9qn91/wiontYy3+5R/Cgj9VG81UbqP4Nn9ddq7zz/VefLeNb8mb8K3dNIf9l8mb8K3VNvfyjeq9H03vrPQPd0pL8sf7T+bEb7y/JH6x/h7YKXNdSLl5sNeXX/KDN6QdpRzq5vc2f3P8oz+2t1rzR746z5dc7VZox41vyZv4qs1yrZfJm/iqzXXrzcXefP8kfrz2a0vyx/tP5Rll7wEFf3z0Sfhc7t8bWG9Ixq/So29+z6Z/Os/qTmlWZvnDX/1eaq8qz5r/p8OP858wte7q7zZ/mj9Wcz2l+WP1r/KOULXlsLei++BukSr7mTj2J6fY2Xj9ZoH2lIz8jqS13R9NqC9Kq2iqy/thb0XnwbYz3x0foKVPoV9B751vNirL8Sr1+91n3rtfWtV/FXg/rRmu1br61vvYq/GtSP1mzfem1BusRrbMxKUD9as33rtY1FWuavptK/oPcoFmmZP4uur+BlDQtHvcZVfaRrLfO1hnTB86vaUSr19T46u1LL01ZR6U/vI8/TovzVnNV/j+7FrqDSn957vWczZf4qUF9W03tvjmy+zF8F6stqeh/NcdRbCerLanofeUjL/NVU+ovmyfIzfxbd36JtWtRY1vRdfaRrLfMtvfV66/dSrd+06FzPq9ZfRbW/pvXEojXar6Znpqh3z6vWX0W1v6ZFfWczZf4qvFmRFs2QzZf5q/BmRVo0QzZf5q/CmxVpPbFoHWmr6JmpJxatI+1seMEzeH7TEVUfoX0U2+OPUq3ftOhcz6vWX0W1v6ZFuiXzG7rOKlAfnhb17HmSZ0GxK0C9eFrUdzZT5q/CmxVp0QzZfJm/Cm9WpEUzZPNl/iq8WZHWE4vWkbaKnpl6YtE60s6GFzyD58+oq7VRf5Rq/aZF53petf4qqv017YxZeuNnU52paVHvnhflXAFvVqRFs2RzZv4qvFmRFs2QzZf5q/BmRVo0QzZf5q/CmxVpPbFoHWmr6JmpJxatI+1sHp+++/y26WnIay5r+q4+0rU227d7FC+652Vk9TM/0huV/JVk/UV+Fm+JvFVE81nN679H92JXkc2X+ZEuZP5KsvkyP9KFzF9JNl/mR7qQ+SvJ5pvtr2a0/1F/Bo9vv/vxndAO9poTXdZenNVEt9zJRzHP9nUM8hqZn+Hla13WXpzVNF7eVYjmEl3WNk7r1vNivLhVeD1pXdY6TmvW82KsfwW83rQuax2nNetV/Kvg9aZ1Wes4rVmv4l8Frzety9qLs5roFhS3Gq83rcs6i0Nk/mq8/rQu6ywOkfln8+GCRwghhBBC7g0veIQQQgghm8ELHiGEEELIZoQXvGd+r/iZZxFCCCGE7Ix7wVtx4Xr2mbxUEkIIIWRH4AVv5cXnWWejc5qmsb4m82dQ6avCit4JIYQQ8jymXfD0ZUSvM844u4I9B53r9dL0rE8dU4nP0PlHa0kfo70QQggh5Np8uOCd+clf1+qp+4wLiD0Dnen10fRKjzqmEh9RrdXbFyGEEEL24yUveKh+r1bpUcdU4iOqtXr7IoQQQsh+dF3wmmep+rK2OiLzEVJXcvXa4ukWG6f3qEbTLNrTMaJX0fnWE92C4hqRRwghhJD7U77gWT3bW62t7V7WlsiLqNSv1kZxUf1KfJSfofNljWogzVKJIYQQQsh9eeoFT3ueFukVWm6UX6mNYqyW7a1WqekhcVm9SNdUzyWEEELIPTn8LVrkRVo1J9IrtNwoP6sd9eQhPspB60hDoDpebqVm9VxCCCGE3JMPF7wGugBkl4Isp1ozOyej5Xs1sto9Z9tYlKu1zI+wdaK8Ss3quYQQQgi5J+ULnuga69m91tBe1hpPr5DVj2qPxqO91tBe1hk2NqpTOcPTCSGEELIH8ILXiC4Ontb2gt7rWK1ZPL2CritrXU+vETpHU4lDnt7L2mo9SF6ljueJrrExhBBCCLk/7gWvoS8A6DJw5gVh9mWDlxlCCCGEvArhBc/SLkkaFEMIIYQQQtbSdcEjhBBCCCHXhxc8QgghhJDN4AWPEEIIIWQzPlzwjv58nf7ZPA2KfVWiZ2M9QcfoOKufRXauxcbdFTRbA8XuTHXuXZ/Nq753gfNzfs6/z/zvLnh6sN4hUbxXo+lR/av7R0D1tJb5do/iR4nqzzjvSuw+X4Xo/Wuat+Pzqs6/K5yf86P1q7Dj/G8XPDTQyJBebvYQr+4fJTvLYr3e/F6yWmeedUV2ny+jZ/4Wu9vzQvO80scE5+f8FW1Xdp1/6QUPcXX/TKKzrIdiPS2q65HlHKl5J3afL6M6v8Tt9rzQPK/0McH5OX9F25Vd5y9f8Npa0HvxNUiXeM2dfBTT62siH3k9WlTbQ3Ik39bQuvV2YPf5MmTm6BloDfl3Jpt3dzg/569ou7Lr/I8ffvjh66IyoN5Hwx/1Glf1ka61zNca0jU9tax2FNSX3kfeDuw+X0abN3sGer/b80Hz7DZjBOfn/BVtV3ad//Hb3/3u66I6YNOiwbOHclcf6VrLfEvPOZ4e1e/lSP0zz78iu8+nyd6/9Xd7Ntn8u8P5OX9F25Vd5398/tz3M3hNiwbPHspd/aYjqj4C+V5OT+wRjtQ/8/wrsvt8muz9t7WHzrkraI5dZqvA+Tl/RduVXed//OEPf/y6qA7YtGjw7KHc1Z9Rt6p5enZmD1n92eevZvf5Mnrn3+3Z8P1z/oq2K5x/z/kfP/3009tGD5QN7A2fPZS7+kjX2qgfaUJWT/SoRoTNi847esZV2X2+Cj3PYMfno2d69ffP+Tm/9l6BHed//Onnn98JbTA0nNZl7cVZTXTLnXwUc7YvMUgXotxG5mdIPqoReTuw+3wVsmeg/Sjuruw4Uw+cn/Nz/n3mf/z885+hQQghhBBC7gkveIQQQgghm/H48uULNAghhBBCyD3hBY8QQgghZDN4wSOEEEII2YwPF7yjv0UieRYU+6pEz8Z6QhSjvbNB9Z95/mp2n8+j+m53fT7V+XeF83N+zr/P/O8ueHqw3iFRvFej6VH9q/tHQPW0NuqfSatraz/z/NWg+V8BPXM0/67Ppzr/rnB+zo/Wr8KO879d8NBAI0N6udlDvLp/lOwsi/V680dodVeevxo0/+70zLvj80HzvNLHAOfn/BVtV3adf+kFD3F1/0yis6yHYj0tqpshubaGd5bV7o43/+5U5931+aB5XuljgPNz/oq2K7vOX77gtbWg9+JrkC7xmjv5KKbX10S+52k9iolqR2T1M//u7D5fhMzb/hW8GLvegWze3eH8nL+i7cqu83d9BU/vo+GPeo2r+kjXWuZrDemayK/kH0XX9c6Yef5qKvPvCnqv0X6354Pm2W3GCM7P+Svaruw6f/e3aJsWDZ49lLv6SNda5lt6zhGy80aw9VD9meevpjL/zvS+792eTzb/7nB+zl/RdmXX+XnBM3h+0xFVH4F8L6cn9gitlof4KMdqd0XPa0Hxu4Hm1Jp+Hhadc1fQHLvMVoHzc/6Ktiu7zs8LnsHzZ9Stap6enTmCrf3s81ez82yI3ve72/PpnX83OD/nr2i7suv8bxe8hh4oG9gbPnsod/WRrrVRP9I83dO8Gj3YGtXzd2Hn2Twq71zY8fnomV79/XN+zq+9V2DH+d9d8BptMDSc1mXtxVlNdMudfBRzti8xSG9U8z2vgq5va3n6TtgZd53TI5tb+1HcXdlxph44P+fn/PvM/+GCRwghhBBC7g0veIQQQgghm8ELHiGEEELIZvCCRwghhBCyGbzgEUIIIYRsxocL3tHfIpE8C4p9VbJnk/k6BnlnkdXPehNQzJ3J5sv8u7P7fFVeefbG7vN788nHvRB5go65A3ft+yx2m//dBU8P1jskivdqND2qf3X/CKie1jLf7lH8KK2m0OtXtbuSzffq878CbV4B+buz+/zRfJlWzbky2Ty7s+P8bxc8NNDIkF5u9hCv7h9lRi9IO4OsbrWXWf2tIJvv1ed/JV51bmH3+asf69FzuNsz6p1vN3adf+kFD3F1/0z0WejcHl9rSO8hy+/pxWp3JZvv1ed/JV51bmH3+asf69FzuNsz6p1vN3adv3zBa2tB78XXIF3iNXfyUUyvr/Hy0RrtIw3pPWT51fqjfVwdO5/e7z574xVmRLzq3MLu81fn8+Lu+HxQz7u/Z82u83d9BU/vo+GPeo2r+kjXWuZrDemC51e1M8jqVs6d1dssWr8IFNvwvCzvqkjfFhTbiLw7YucWvFik3xk7t+DFIn0XKvNFMXd8Pqjn3d+zZtf5u79F27Ro8Oyh3NVHutYy39Jbr7f+CFndUf/uePNpfednsPv7zeD8e8+fzRf5d302qO/d37Nm1/l5wTN4ftMRVR+hfRTb459JVjfyZ/V0Fbz5kL7js9j9/VZ49Wew+/zRfNnsd302qO/d37Nm1/l5wTN4/oy6Whv1zySr6/mz+rkK0XzI2+157P5+q7z6c9h9fm++ytx3fTao793fs2bX+d8ueA09UDawN3z2UO7qI11rs327R/Gie16VLB/5Ve2uZPO9+vyvxKvOLew+f/VjvardBd37nec4yo7zv7vgNdpgaDity9qLs5roljv5KObZvo5BXiPzIyRXU/WR19D5dwbN1ohitHd37GwCit0Vzr/3/NF8yGvofImz2p3w5noVdpv/wwWPEEIIIYTcG17wCCGEEEI2gxc8QgghhJDNCC94z/xe9Ct/358QQggh5EzcC96KC9ezz+SlkhBCCCE7Ai94Ky8+zzobndM0jfU1mT+DSl8VVvROCCGEkOcx7YKnLyN6nXHG2RXsOehcr5em9/TZG4/Q+UdrSR+jvRBCCCHkynzz1/8FACLbYxq6Db8AAAAASUVORK5CYII=" alt="赋值变量1后内存">
我们很明显发现在0x7ffffffee370的值发生了改变，也就是结构体变量t1所在地址的第一个字节被修改了。结合我们我们的赋值语句：给结构体第一个char变量赋值，我们很容易发现：结构体第一个char变量就在结构体变量t1地址0偏移的地方。十六进制的0x41转换为十进制就是65，正好是A的ascii码。
再次步进，给第二个结构体变量赋值，再次查看内存。
(gdb) step #执行下一条语句
(gdb) x/24xb &t1
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" alt="赋值变量2后内存">
对比上一次的内存，我们发现不是第二个字节的值被修改，而是第五个字节的值被修改了。这是结构体存储时候做的字节对齐，给第一个char变量后填充了3个字节，避免第二个变量int横跨边界。十六进制的0x63就是十进制的99。我们知道int变量占据4个字节，因此下一个long变量存储从0x7ffffffee378开始，长度为8个字节。显然存储采用了小端存储的方式：低字节存储在内存的低地址。
下一条语句是给变量3赋值999，十进制的999对于十六进制的0x3E7，因此我们猜测下一次内存在0x7ffffffee378开始的前两个字节会被修改。
0x7ffffffee378 0xe7 0x03 0x00 0x00 ...
我们继续步进，给变量3赋值，查看内存验证我们的想法。
(gdb) step #执行下一条语句
(gdb) x/24xb &t1
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" alt="赋值变量3后内存">
显然我们的猜测是正确的！