2.5链表链式A+B

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T711Ak3e2u/SXYpF1lRAihOOWte32swKT37l27fu/h3a1rdx9tX7fjVzmSvrlzur9zO7l+77Fpvdqfkkl3CTb7CjBpwdql9K1sD5n0YrEI7Os2FuqeVFrdyHoc6j2j5+fnB4vFhLxVRZYVtUNmjkhaD4CHursH8l7vTj0qwSbtKiNCCMUpb7XtY26Tbh/1asakw5786k26CZ3bSNrg+r1tZyTd2/BqTDpIL1++9M8KUmRpWhtb/f80L5uQ0zkqPTaSvri4ePny5aS8dUbqdcl6vcHB44FIuvd7w/sttx9RRoQQilMDFaabWU1653b3JFf/4NjevWuJFgqL1mubdJtsYHe3ZtISS3Z3B2nQCKtKjROLLM1LPeK0Fkh4HWyySSshfZElbWNCz1tVVUWepkmW51mey7HycP6blazmQNiDY54yIoRQnAqp2URmM+mHt1Qj1J/u3rt3zTI/46WpmztPtq8nkknXnipGydMi6RVqqEtZDRmzQgs25Ui6zNOs0B41W113d5e5NMvSNMvSrKi7pIusHj+vnynL8zxL2p/aDaVM6U+Gl3na23GZp1mWdSbdFrA16cHOA7q7EUKbJW+17WMek354K2mHk6XIqX3+q36f6uGtre095YHw7tfr9x4rsXitx3e3kluP6v/uB5j047u3XV3ZjfbuXbt+73Gb8v6iGws/dT2JFq6Ah7PMSNoMRxV36l2uDU5D+r2XeHBMzaH5QFvSPOqW5WVXADtmbjNYZInyCLhais6oiyVMmgfHEEKbpaC6V2Jt70l3K9RurTzdrY4Zd/9uXoP2m/T23a2kM+DGdx/d1IP4PoV+vFzZY9PlLmd7+OnusNeckqwo89wXSdcvIqdK72/bPzzIkq9gtWZb5FIkXeTCiLXhqUXm6vZuHzXTX9SaYNK8goUQ2iwN190OLt2kd24n17fqF6CHRn91f927d+36vW3XZCb1S9W3HjXd45rRKv6qPcj26GbbOFC83xVMB5l00IQh7YNX9f9tN+rsuGx8sltLf0tZYpnJTIqsTrkO4EvRpNsVfSZt4PpVi6StzhdPgkxmghDaOLkqtEEu26T7V6Lbd6llbj0SH7R2RtJ1BGz1lqv56Z9Qs1Lru74Xp/s7t5d5duzo+MQfsDaDs21ftmlQ1ktMYY9SNQxNCzqQt3qv2utQfUaM96Qd74k1zuthuEB+12daUITQxim0ErfgAxszq/6IxevXryefkskEfmBjLXmbCz6wgRDaRE2u9DDp+fXi6PTg4OCSvbB2r5BPVV5+3uYisIwIIRSbJtd7mPRK9OLw9PDw8OTkZOiDFjNwfn5+cnJyeHj44jC6vM3F2DIihFBUmlz7YdKr0vODk6OT04ODg5OTky+//PL8/Hx4npNgLi4uzs/Pv/zyy5OTk4ODg6Pj0xfR5G0uliwjQgjFo8k1ISa9Wj0/fHV4/Oro6HixWLx8+fLFTLx8+XKxWBweHR8ev3o+9TnnFeVtLmYpI0IIxSBMGiGEEIpUmDRCCCEUqTBphBBCKFJh0gghhFCkwqQRQgihSIVJI4QQQpEKk0YIIYQiFSaNEEIIRSpMGiGEEIpUmDRCCCEUqTBphBBCKFJh0gghhFCkWrNJ/+b5wc6vn97/938z9NP//Wt1nX9+9n/sbe/vvv/Op6WypPxgx1hyur/47MZHD+4Pb3u6vzjd/3z3HWllW598+mG3+f3d99/+yFabztMHb+/sftKnb625+5mY8ieffigku7P7yaL8YEfNZPnBzvs3ntr/lkoqZCCovAghhNaiNZv0X/3yZ5LDvf/2R+/XPv2b5wd/+i8/efuj940NbWu8sftAsLTPy/uffvj2Rx9+8Lm5uW3S93dNy7T20qXTNwikpLSWQb/C57vvdIa9ON2vnbjZY/nBzocffN57s9oIMHx3/+kDxVy9Jv20PybdciVBuQWDEEIoEq3ZpF0O/fZH7//1v/5z59CGSd/frWPK008+/bCNUzu/+ezGR6ZrNl741HJx1XqtKPOdT0vdgBsfbf9s9ugxac3jdz/rTfrpg9qbRZPWU5N9VFnNbdJdx4AazaulCO45QAghtBbFa9J/+i8/6RzajqRrQ3Jv3niP5XmNbGdtw2jN57wm7UzKctY2zXEm/dkNsTFh5NlxBG48lTobnprtFfHgIIQQikTxmrQha1vZMvcXp6pHfvL0wTvWuO++a0zaSlYy6a5x0Oxi0KR733WatNDgeOfTXcvpxfKqy43u7ubPun+76UjX+9sRQgjFrI026eFIen8hd+rKkbQ1pP2BM5LubXjApNWYtTXpLoBWImlbTSKtx+tNBLH7WjJpI5Juu74ZjUYIoQ3QRpv0cCTdS3yyWvFjxfNCurs1k3a2Ep4+eHt3t97q/u77Nz4dNmllj6JJn+4v3GPMQ5G02AdOjzdCCEWreE36r375s3t7v5whkl58dsMYzdVMzlA9EixGyaMj6fu7D+4bD2o171A17qiYdJPJJrWnD97efTBk0vagtSJlfL036U9332kOBZE0QghtgOI16f/+5F/3F6edTztSMONpoQPZsOS+91uIxevNu0QGTfqTTx84onlnDvefPnj7ow9v7OpPtLWZvL/7/ju7D9756MH9ZhddcOyKpFW7Herutt9SY5QaIYQi1ppN+v6//5vLpD/7f7+t16l9WtvK/VSzZT+Gb+lRtTlc3f3avAbtN+kP2hfA9DfB7ClWjD2+X7cD+qfJPnpfeXJbfZfswf1mSFuPyJ8+eHvnwY0d5Wntfl9CYdXubuUnImmEEIpdazbp/cXpb54f/K/PPzdkryNvrk3rcbpvR9KaDWsO3Tu96K+f776zs/uBazKT1mub7nEtdi8/2HE82FU7bjsabc1wUge+WlisvcPdplk/p930ims9+bpJ610ImDRCCG2c1m/SE1UbntVVa5i0+qcRfxszcLnmIJMj6fodKtMj9Wz01ts9la34ojKzSh2yq0n1NiynWcsaazefetObFNrKmDRCCG2ANtakEUIIoasuTBohhBCKVJg0QgghFKkwaYQQQihSYdIIIYRQpMKkEUIIoUiFSSOEEEKRCpNGCCGEIhUmjRBCCEUqTBohhBCKVJg0QgghFKkwaYQQQihSYdIIIYRQpMKkEUIIoUiFSSOEEEKRCpNGCCGEIhUmjRBCCEWq+U36+eGrtZcKIYQQ2nQ9P3w1v0kfnrxee8EQQgihTdfh6ev5Tfrs62/WXjCEEEJo03X29Tfzm3RVVa++OFt72RBCCKHN1e+++GqyQw+YdFVVZ199c3jy+vnh+suJEEIIbYqeH54enrw++2p6DB1k0gAAALAuMGkAAIBIwaQBAAAiBZMGAACIFEwaAAAgUjBpAACASMGkAQAAIgWTBgAAiBRMGgAAIFIwaQAAgEjBpAEAACIFkwYAAIgUTBoAACBSMGkAAIBIwaQBAAAiBZMGAACIFEwaAAAgUjBpAACASMGkAQAAIgWTBgAAiBRMGgAAIFIwaQAAgEjBpAEAACIFkwYAAIgUTBoAACBS1mvSZZ4maV72C4qs/7vIkiQrtJW1dc1EiixJxBUAAAA2Ep9JF1mikxXWohrNWP2otjvSpMs8MxMwEinzVFgBAABgIxkw6d5ByzxV7c90UP9i16+dv5Z56rV21bnNaNlyegAAgCvByEi6/cmwbG2TMJPWE1eWOiNpX84clg4AALDBjI2kxZC3t9KpkbS0S39aWqLYMgAAXEHGRtKSrRom7cdv0gGZ0X27aTRg0gAAcPUY+3R3Z6ttzGub9LRI2mfv3TZmL3uZp0mW49MAAHAlcZq0bJppls1t0o0NGx3dcqe3/fRaF9zLT34DAABsLgGRtOaMbeyrRtSTTLprBPSR9DiT1p4M7x8RJ6AGAICrQsCDY5JJ934415j0yO5u4+Xo1prxaQAAuDoMmHRWaO8w1/ZX+2k7Fqy57lJj0uGRtLVQ9WXhVWoAAIANxGPStRenedFH0qXtyzM+OBZq0sb8oExmAgAAVxO3SddOKdiyj0uKpDUwaQAAuJr4nu7WvDFspHmVY9J9LrBkAAB4E5j5K1jjn+5uDdc1ktxu02873GTgXSwAALgK8D1pAACASMGkAQAAIgWTBgAAiBRMGgAAIFIwaQAAgEjBpAEAACIFkwYAAIgUTBoAACBSMGkAAIBIwaQBAAAiBZMGAACIFEwaAAAgUjBpAACASMGkAQAAIgWTBgAAiBRMGgAAIFIwaQAAgEgJNekiS9K8dP0URFbY25Z5Kv/Q/haUYpmnzb/7fw1kut3O+3vQmoPZVDfU8zeUR/M3a90uW0VWJ2v+fzK+EzNxoyKzfhw6QSGr2Ic0KJuDOx6Js+yjz5F+rZV5ulRWyzw19zKYpJIz6eiurES+miTgFPebu6qakOsk4JoUb8TAnYYkH85QDVZk+tGo17fPwLQjP1RJBJ53/bJpD5n3fAXU7CtwhFWfTReBJh2cGf3+HtimzNMkTV0n2tjeyIJ6wIxKpV3NzEBYayIrxqw5DvEsS3WoRZqXch1YLyyyJCv634WaeXQ+/Qhn1n82u8x50pY2FE+FsnfB+r201VaRzenTIWUPPEf2rTapweRL0FUBCmarrGnfcXOXyFnLmFe+fH/2q5SleHWGHMPA9YysOnIedL8vg6uOdd013fqGYwYfeX3fnmteTFQ+7+NNetCOZncENWeunK8Mp0kP19NixTrCpLvq1VHPBpt0f6gbK0vz3Dr63iBnkPA1fUlYGbIOcncHpXnZFbkuqn1BZbl0jrLCSnZc1ss8neBf3rOpxl4BdZuRrmcV711mbVcbdK5WVLPcZL6yi/eR5xwVWZIVvptvwnXYmulQmopJtxnN69usvSbKslxhiYLjucDKMaAOS/MyvK7T6p9Sr4us0zLifh+FZhVj66VRpi4deW0LX+0ddt7V/SrVmXmsmug/BOMCnssRVnU2gwiJpAdvidCbQU9TWRZ0lTtOSFVk4sGRjvdwy0mpWUaWaAgtP90FrB5YrZkr7K/I88JOqs2r2KczvnHR3HOegy8k6D+b6rG0etkcqQUdeF80rCdt9HD3h6X+YRmnDriSq+BztGzn9nI4IulEPEIrKNGYSHqOqNje31CrUbo0s8xeWN9Boff7KGyTLtR71Txx/W2TZdYtrTaPxkTSgbV3YOlGRtLDfR0rcIRVnc0gBk06pHdSHgHQakIzCE66yErtBdWOfVgkrebPGnwZHmNYLpIObd5pPU1tYVLzKtZ30qWtlKrImjZlt6zIkqRvJ9ZFztIuncn9Mf3R1i9G+0AEnk0lHdeNofSlOk+Lni93Ikod0XRwu/batLUnOXVY2YPPkdqUEAKUsT37VX+oHZsZKfq7u6v+6K+oRGMiaR/u/kmr+NqF5uqy6kqpH6Z+I22XUqUXcL+HYl/3WoNo8MSleW5XCiMi6aBrftR5H2XShvkLa63EEVZ1NoPwm7QnzlCPrGbSauusv1W1CFWPhbSzpVt/gEkXWTs41iYgdo4YXSv+Wzx8TccxG+xJEapD04DqHHf/Vc+IejA73+vD36xom5IB3ckyalhUqjnQUww/m8PNX3Hn7t+k1qzyZ1BD3qg+xjS5gssefo7KZoxPbBzZuQ2nvcjMu9lKULkq07TLpnmfR1Mi6Tox40y15OYZFHpbHK6gd9iYN20/gOKo9Abv9/BiGxWP3a4fNGn9lI4j8Jofed6LLMmyTO2RMKIvT9AunLRVOMIqzmY4HpP2tivNS0W9GfoGlGHd9k1pL+lPw3CdqcaTdlPW/kujaVQGHNiANVVTUyNGjwWIIV9T5/ULmkNRFErU0leLxg7VfTUB4ujrJvTCreOowLNZZEnXK+e8OfTeAd+eXfWqYdJDfWJL3FTjruSwc1RkeovM2GZ6frXrsL1FC6EV0x/4NCtKdX372M9botD2UR+3icGWK8zSqwG1oadFofIBsS4j9frsqiorxdD7fSxmM8RR24ntknoF4XoIOfLh13w+5koujGETTyTdnSNnDbEyR1jV2QzCaYt4R0sAABgaSURBVNJia0H4varUqLbr1y06h0+Nnl4zFWfRjD3LkbR+8NomT2FfeVbfRN+s6CxVuiND1pSb70adIbbFtF+6hSE3TnO8HcU02rJjUY+1dUu5L0XX2eyas85ExgTaxmbybWom6D2kc7SA/WUPPkemb6i1ztRsyofbuNhLe4DCndxllMjzc38raXdYYT6iEG7SRduBaT9fZBVT6jesl7n903+/j8Jj0sIh01ZoNh3ab/Cl5u0JCTrvQmTvNOkiU681Y219iVYdzOIIqzqbQQyOSYdH0srBV85emadplk0wadPZZZPufgtvN5n9V00JA3q65DXd4ZxWibhPc+VbKJXdsW9tLavGGoHWIi+11yonmbSwnucYtnvX7hbpIHq8XY3gpQ0dhV0Cd9lHnSPtd2XLZeJ+9XAr7SXBqb19GI4oes4SqQnbeZFu9651IV3vWsUrlKXNQuHqPRePumbt0oHtdj75fvchmHRfvN6Ci+4B0K76VWIpq+kSeOStAoSZtP+8d4df2592ztqBdGtjVw0wtyOs6mwGEWLSQZG0UijpSI43aXPHwyZdZFkxcEocob3Q1xW65uBl064weJpts9diBOmuKYtCHWzpt243mGao3rrak7D3pu3yKQ2KiTex5NJ2Be2Kl5tuFqWtuB6THneO9MupK4B1xIZPsJkzsybqfxxb/NWUyMyMu1li/eJqZjsiaUdCgSatpKU7gZGFsfe7UR7vfeSIpPslXcbL7nGpJFHaJu0pUKOqgCM/Jp/h5z0wkhaz5jfp+RxhibO5PFNN2ooXfRmcYNJ2kgMmnWiPBzjOm15lG/0n/bbhawolE3Oe2S81DV2Ahkk7b5u2hsrahzqK7ukOoe3hzmUYUyJpyx7kRoDR2aSlpxyA4Tatul/zlImsNpKuxpwj8UxbJ0uJiQbyXmcrtIsjnLlL1KTYp+csm9Hpkmi7Tdx1hFyIsSZtXlNt0Kq0g/qaY9T97j04k39Vu6WMtoXqm0FH3mKESfsyvyKTntMRljibMzDWpMUWtP9IOY9R5T7Ngvk1R0HKQNsO7LYSXMC8ed15MvIRuKayT+etJ5iLdvI7QwpDua+0/FpLhAyN65xRsuS7EkO9wB1JG7+oAYF6uq2eKQdaf9t6Iuli3Dkq2gf6BwoVGEn3h8p/oIzuRu/OV1Ei7SFET4Oq7YURHNnY2FnPV65bVW8ICitU3fXZJtCMYVuhWWIGcL77Xcqe97QOnkq9DFZrrs9Dc9rDjryckQGTDjjvidyycpu097mBvg6d1RGmn80Z4AMbbyTjPBoALgvuTdDBpAEAACIFkwYAAIgUTBoAACBSMGkAAIBIwaQBAAAiBZMGAACIFEwaAAAgUoZNenDuL3W5OTuA493xQMT5/6QZvgbpNvKtLUx9ocygJ05qZybnm7KozFPz/UdxppHQyUxcE8ENzoRgzr1gzeETVnZ57+08BPLpLuzJC5ZE2pc8UVTY0ewvd/3CH5pRyDknimPX+pSDg7MoGCfWOwOLdpBDriZ9Yk97JjB55igPK5t7CeDNIySS1qzR9mzHDatO0TxpEkrfbDFKXTA8Y9TAGt0McubSrJmtXiuHpxiD8woKKwTMXKjYx3BB6w8BizPLiodPdN4JZdcKY3yUQz2DnsmNptfs2gUqToNkHDt7BtZuE/2Ay5ORVqEtKdv5rQM+NEtba9Kl8eXRfjvrSDYrlWVpF1VK3y774MxTpWc+5JmmcAOAqqo8Jh0UoLY3rWY16pyw9q/BaDMayvP/qSbtqRpUt0+1z6m2U/jVK2W5EglKBRXiZrXOLbKk/lydjTZtrq+Cl9sKejGcByzp5+J12pQyu6qUkywPLnsx5gppsqD9YfjkyJo9yCYdHus2aX3GSMcshIET2Wo/Ciatz6YZesNZ14P/9go2aeMu8SdAJA1wWYSPSQ/0drb3sm6BWbGcRRdZO0X1UF3gq7OVDKV5URbdPPhKptvJ2JWsFpm6sTm5r+a7xs/WURlHQH0tmLkxO29Ih2+aF3neBcr24Rwqu5Bvz6me16Sde5WSCu3uLpyffJ8wKqGfD8OkQ+c5Hx5lCDRp+xCoLWi1NNYQk2jSRNIAl4LfpEM+X+Cq/5pPgJbql2GC0fpHQ5wuqCmgJNQF1anymTIzotImgC/zLJU+UtduZUT25h7bErkn1ZdCTrVYfcK2wakjkEqPpTQGbuaiyMzmyciy616U2IUXrpA0Ly7bpAMiaTWjSorDfTVDBfB0d7uWhf3YJu5uIqgmrTuprxPMeecr41eDNQMAzMCgSbsqiADn1Ia4xt+3av+bI5oOf67HWqntyUyzrMtcW0f1Vtd3BiT1KLvYI9iOBff1sKOnXh0A8Dyvo5m0muO+ilR2YH6uXE/WHGFVWyfK7tQcjyq7MDqath+IS/OiNNoS64ukA0y6yNqh+Ep5VEEa8w0bkk6cwx/9xavcG1Ki4tdQ9QZfmafGZ6TEK3DYpEf0eRFJA1wWy0fS3q2FJ2cC0euZLMuaYKb2jcZKPY8hCfVhm2bblVuWubFAy6WQ56b+sVsEmh3qAYlk0kqe67FdPTmtBtUe09Wt2+4ytZeUeao1RPpKuyjUD8V1Zjy67Ea+c8dX34osTZXvSi9p0sEjuP7uHusS8TwF4Mli0+LzHxg7ktavGtexcLSUrWGWtr1mNdTCTLoeC+qaWfKtL9/D2DLA6pglkhaqQMFFx9zHSopplqWDJu0vgxZ2GhWy9JtQQSmxdpqKL/2Ib9X4TFotqG2s/ZB5mad17Vk/6KX2z0uFdVekg4Y2rex68l23sRVu18/l5U2TZNZIWtvUMYCsHhY5ktYPUTuCUUid9c4mldpZrLXHzMECrXep1J6cDzs0SsRvdIrIRR0w6a7jQD5iypqB7SNsG2AWZomkjbhLue+nR9JGaq6G/XAILXY+d8mZ1bswFqxXg/oTWv2yrJBiTI9JK7Wi6dRdke0+6KrM0zTLxpu0tKqcyPiyq+Vot9R8qu85766L2UzaurSEpMxFju5uJa/CZo5udNPadHu20rTNzzpnvtxql3BzTI1rSM+TatL2zeG+M90mbS/Mmw73iXc4AHiYLZJ2mHT3Rk9fXYvVmEBfq6R5WSwTSSsVpNcJ+vCiKNShSGOUN7FiFWd9p++xWdOs2fsflZhV2YmV7SmRtLWh1expWwGhZbejNusANP25RWYfn1CTHmp22OdUHsQ18zVg0kWWFQMm7ejWcHQjCG2AdmWzeFYB9FF/teGj9FGbPt+PkoSOSWv9IYMmrTcy+w534QoIu98BQGK2SFqo8d33+ZBb9o7VbzHRpNVK3l8cozZpg6Ks7cnuu7SVeljrtbSzZEXDQaHuUL/DXCbtPAdhZR+bb9kP7MspPEkptLePjp3GgEkn2gNjjjhT7drohnDbVNVtrYaa2l6VEtcOTWe16kMT7q4bKachDVOr4egek7Z7C/Qjrvhy8P0OAC5WHUmbW49sWXeDdfoLrEaVKORNst2QvfXV0EB4VLuzo49PyUDfQDBHv92NBE8X5EChXCYd0jyp082Cy15KyQ+0LUZH0v4r0OVxQ2PURT+ji5nv1ve7rdyD9F2hfOU2/cnopTbK47msFW8ccy2Napjquwvp7m5/GboViaQBJsIHNiBiAoc0wEnwEA8ARAkmDQAAECmYNAAAQKRg0gAAAJGCSQMAAEQKJg0AABApmDQAAECkYNIAAACRMmDS5luWvvmm1JW88zFMmlxBnEBR+U2YczvkHdHZJ0Iqy5kT3ESu1kHQP3/RLxRnsnZfUNoMPFPnGJmDwRnYtCx7J7pVUvQw/2xjV+sCA/DhNWnzbi6Nzx76thusYpwfMnClmKauVPWk1LkZHfNiDVaN0oxQTRKenKpbWTNWjp01ImgCUf9kH7/+0R++9dZbb7317sfhu1XY9IPw8btvWfzhj34dvnczGz4vUr7c0rcXpTVqfxk9x4g9U7o/u26/Fz3aO+mYp9zdCs5Jzj1TqW/iBcYMp3DZeEy6ubvae0JxXnPW4UlhwQiT7u4k+Zbqd99MM53mubeaMkool33CvWhWH+bXK+etPoosSbMszTLXiq1HT3XpTT8IkklP9emACcGNNQdnHR9l0kWWuL8TKiRubyx+CqudhNZuTajTohoz8i4XSSsl28wLbBX9bwBunCatfNlG+s6O1rAfnLwxpE0u3tGV2VgW7mt9Wm+rAGZaQXsfbuMrJbHqv+6bAurU3q7PS8jBft3OGFrf22VRe/S777471aU3/SDUJq0W3V4yEucFJBtXgEnbd0QXZBrN4Pr7GsIJsYzGvUC7KYpM+WaHku3+eyFC0VwmHRpJF8bVsIkXGNE0XCYuk1aj0yKXv+jsjuGcyKPH/X1sf3ZBHcRTjF66sYQP8/hbveMj6fb2VKtBPWdKGz/VvmOoF13bWmgZFMpX/7TMKH/032qQTkLj0R+3/3cdBDebfhAcJj0yknZ8ImIwZHO0R/tsd64jBYLywxXyGRk06d4YTZO2g3N1jT4TrsaJEhJ70NvYfc429gLDpeESGRqTDvDggOi4u1O1e6i7zsVKpNA/x6RXPH2He5FlRZdA1/sldeGNeWxtTPWhHwm9+lCOoaP+7dMy0nT28Yf16PXePNmlN/0giN3dkwelpWaqfoXlmp2XeWoEamrdPsaklSMq9hqIJi3dfVIkXam3n5bHET3HoZG0cUVt7gWGS8Pl4TZpu9HruvNtnNewdg8ZH8ttfnfcnvYSq7VbqSlIf9l5zOWu8uGOuP546OG7XQu3meuKbh6cZitzl+364458i+rMU1160w+CY0x6Snulu8CEK9sKsvQ128am1coMNWn9mCjJSI0Gp+H0jWRrdfFWUoa53C1c2cXcN52Rsc29wEY0YACWxGnS6l1Zd/cYl6xwF6ihsd+klW6qoutM1zuuhPwIt4V+c7UZLexbzurUMytDtetruPowjlJfp9jVR3Nklqk+Rrfa+2fGlvCmTT8Iwgj01EFp1Xr9bqWZXJvh+ioVhzUHTVrao34oBru7+yViJN3uuW1TtAGn0ZHl6O8f05FmnPXNvcAmXY8AkwidzGTQpLW2pV2xKOaXFXq3n9rVnWUjTbr7MTySVoN4JbNa4qHVh76yo/qo85fP1REXgOTR471pww/Cqkw6JJLWjkbXelQuOyFY1G4V1WwEw7U8bGmTtko6tFgMJss8TbK86egXEx8VSZtJR3OBEUnD5eE36dZss2LIpNtOPek3hb7OktcbHUl3P2ZFVWRWyG+m5wjY+/5AZYGv+lBz06/rrD70OL3M3Y+06F2ZyvrqsR1qxNcerY6+eszJfWA3+yCM7e4evsDKPBPe7ZMiaaWv2NH2C42kpVyZ52XQpLWT4zdpzX26BkRWDJq0EnorQXniyohYECWtyC8wrZvdbuMDzIjLpM0OOu+YTXPd90Y92N3tYrpJJ9oDY45gQA3au3E2rRRJ/+CYVBHbN6e2N6UNInW3CdWf8BJps9T1csiwOTVxtOpFwiIlZcdx3eiDUI18cMx7ZfZF8kbS9RXmvPhVhlaqE3W4mH4YxcSF06YUxD5pRr7M3iZHN3/fMW4EyMKWQny7sReY1g8i5QNgPmbo7i5c17lw+7mqQuVmdFQ+PpNum71dJoUqxYyT3Xt6s3B0b75xeI9D/6NaG/dXWevR6iCOG8XavKzgvMiRtHbTynsN7O62dyIktPF2Jl0E3ESwKvjAxpsNHl1z2cchLJK+vPxcHhtfMm8bBGB2MGkAuEw22qavQk8AbBaYNAAAQKRg0gAAAJGCSQMAAEQKJg0AABApmDQAAECkYNIAAACRgkkDAABEivdTlf1kh+JESMoXZHxTD5lvFhrz9fg+h+GbN2Cj37YEAAAYxhdJNzNxWl+aaRdpkxZLZtp6rPWdIGNSfPGzNd0io5GgTrWNSQMAwBVm8CtYaZ6rjiybtGNqbekbVEpEnjvm+Va+BuBxZEwaAACuOE6TNr8pMGDSVVWWpf+zAf0XqAY+ydvnQN1G7WVvP9QjmbT12UkAAIDNxDsmrX530mnS7Sd0HJ/Ukz6GG2LS6rcy1a/0dJ+2xqQBAOCK4+3urr04JJJ2POElf+CuG1uWv2vZfdIya7buQup6LwMmDQAAcEUIeAWrc+Q0LwdM2nDdLDMfKCuybqH6/JhluEXWNQj6jz83a2HSAADwZuA16e7p6v5FqpBIuv/DCLDV9IQdmbsvsnrtrOieOWuibEwaAADeAHwm7X5622XSRaa4aL9iu0KeNX7bjnU7aLbWO8v1pDBpAAC48nhMWnHBIqv7rvUQ2DDptH1gS42fFUdW/H5EJN2vYGzEg2MAAHDF8T/d3T7DlfTd14nWra26uDbNSPcMWD8jymSTLvM04CVsNS1MGgAArgBuky6y5v0q69GvNM+z3oWrSp9azHodq3/yS0kh3KStaVK0NgAAAMCVhQ9sAAAARAomDQAAECmYNAAAQKRg0gAAAJGCSQMAAEQKJg0AABApmDQAAECkYNIAAACRgkkDAABECiYNAAAQKZg0AABApGDSAAAAkYJJAwAARAomDQAAECmYNAAAQKRg0gAAAJHiNOnf++nf/95P//4CAAAAlgOTBgAAiBRMGgAAIFIwaQAAgEjBpAEAACIFkwYAAIgUTBoAACBSMGkAAIBIwaQBAAAiBZMGAACIFEwaAAAgUjBpAACASMGkAQAAIgWTBgAAiBRMGgAAIFIwaQAAgEjBpAEAACJl3Sb9LE+TJLlTqMuKO0liLfTQrJ8kSZqP20DYb/Bea6T8u9IfzE5g/l3HZ0r+AQAgYtZs0s/yNM2fGUuSO8VFccdY7kmh87bizrBJPcvTbqXiTmLspbgzzuXk/LvTnyf/7uMzNv8AABAz0Zl0Q7BJ6ysWdwKD6XZ1w9Oe5emSJu1PX1plUv4dx2ds/gEAIGY23qSX2cr20HlNenRcG55/TBoA4A3gCpl00xEchGtYdy6THjus3qQ1ZhwekwYAuPKs06TV4ViTsSZd3EmGx3+FjaxtQsaFG3z5d6bvXnVU/p3HZ0T+AQAgctZp0hczRdLqs1ojMceAZx6TDhtjnpJ/ImkAgDeAjTLpuhPZfm+qN0LdFKX187SPWO2oUzY5KR1X/n3pz5F/ZUVMGgDgihOdSfcvDVuvDkvvAZurD61/cXFxkafO95JFk/O8fyw2Mlzpz5J/z/Fx5R8AADaU6Ezazfhh2/HD1NLz2L50NiH/AACwqazZpOUZu5xrjjGgseubPc9h6cSffwAA2FjWbdIAAADgAJMGAACIFEwaAAAgUjBpAACASMGkAQAAIgWTBgAAiBRMGgAAIFIwaQAAgEjBpAEAACIFkwYAAIgUTBoAACBSMGkAAIBIwaQBAAAiBZMGAACIlPlNGgAAANYLJg0AABApmDQAAECkYNIAAACRgkkDAABECiYNAAAQKZg0AABApGDSAAAAkYJJAwAARAomDQAAECmYNAAAQKRg0gAAAJHCBzYAAABWCyYNAAAQKZg0AABApGDSAAAAkYJJAwAARAomDQAAECmYNAAAQKRg0gAAAJGCSQMAAEQKJg0AABApmDQAAECkYNIAAACRgkkDAABESnQmnbTMWEgAAIBNZG0mrdpwoiCuOcichwQAACAO1mbSF4pP+1120IMxaQAAuJK82Sb9LE+TJLlTWD8Ud+TlLmZYf2wSAABw5VmnSXf4e7BVLxfXmWzSz/I0zZ+Jy+/keRrsmHOtX9zBpQEAoCcWk/YscZnxqkz6WZ6m+cWzYNOdb/3wNAAA4E1gPSYthsJjzdizPNC2RZNulgUb5ozrY9IAAKCyHpOusV3WcGvXaoPLJ5t0vyTMMOddH5MGAACVuEz6wtv1PW9397M8TdLcWFjc0ca8xRHrVa5f3OHhMQAAaInLpAcj6ct5cKz5bZRbzrE+kTQAAKis36QH4+lBD553TLr/zTDMOgp2uejy62PSAACgs36Ttv/t/8mfzsUcJt11Squ/et5jnmX9C0waAAB01mbSYs+2a81BphXeF0mbFHcChpyXWL/ZBpMGAICO9Zi0ESj7rXdsJD0C54xj4ppjDHTs+q2rj9kCAACuOOsxaQAAABgEkwYAAIgUTBoAACBSMGkAAIBIwaQBAAAiBZMGAACIFEwaAAAgUjBpAACASMGkAQAAIgWTBgAAiBRMGgAAIFIwaQAAgEjBpAEAACIFkwYAAIgUTBoAACBS5jdpAAAAWC+YNAAAQKRg0gAAAJGCSQMAAEQKJg0AABAp/x+cZAx8FEbqbAAAAABJRU5ErkJggg==" alt="" />

把测试代码也写上。

 #include <iostream>

 #include <vector>

 #include <string>

 #include <queue>

 #include <algorithm>

 using namespace std;

 struct ListNode

 {

     int val;

     struct ListNode *next;

     ListNode(int x):val(x), next(NULL) {}

 };

 ListNode* create(vector<int> v)

 {

     ListNode *p = new ListNode();

     ListNode *temp1 = p;

     for (int i = ;i < v.size();i++)

     {

         ListNode *temp2 = new ListNode(v[i]);

         temp1->next = temp2;

         temp1 = temp1->next;

     }

     return p->next;

 }

 void printList(ListNode* result)

 {

     queue<int> que;

     ListNode* temp = result;

     while (temp)

     {

         que.push(temp->val);

         temp = temp->next;

     }

     while (!que.empty())

     {

         cout << que.front();

         que.pop();

     }

 }

 class Plus {

 public:

     int cal(int a, int b, int &flag)

     {

         int sum = a + b + flag;

         if (sum > )

         {

             flag = ;

             return sum % ;

         }

         else

         {

             flag = ;

             return sum;

         }

     }

     ListNode* plusAB(ListNode* a, ListNode* b)

     {

         queue<int> qua, qub;

         while (a)

         {

             qua.push(a->val);

             a = a->next;

         }

         while (b)

         {

             qub.push(b->val);

             b = b->next;

         }

         while (qua.size() < qub.size())

         {

             qua.push();

         }

         while (qua.size() > qub.size())

         {

             qub.push();

         }

         ListNode* pHead = new ListNode();

         ListNode* pM = pHead;

         int flag = ;

         while (!qua.empty())

         {

             int ans = cal(qua.front(), qub.front(), flag);

             ListNode* temp = new ListNode(ans);

             pM->next = temp;

             pM = pM->next;

             qua.pop();

             qub.pop();

         }

         if (flag)

         {

             ListNode* temp = new ListNode();

             pM->next = temp;

             pM = pM->next;

         }

         return pHead->next;

     }

 };

 int main()

 {

     vector<int> v1{ ,, };

     vector<int> v2{ ,, };

     ListNode* p1 = create(v1);

     ListNode* p2 = create(v2);

     ListNode* ret;

     Plus solution;

     ret=solution.plusAB(p1, p2);

     printList(ret);

     return ;

 }

巴特西

2.5链表链式A+B

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巴特西

2.5链表 链式A+B

最新文章

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2.5链表链式A+B