CSIE1212: Data Structures and Algorithms
Hsuan-Tien Lin
Dept. of CSIE, NTU
Course Introduction, March 3, 2020
今天(3/3)不會現場發授權碼
Three Warnings Before (Signing for) the Course (1/3)
警告: High Expectations• goal of NTU DSA class:
as good as the best ones in the world
• tentatively, 6 homework sets and final project
(http://www.csie.ntu.edu.tw/~htlin/course/dsa20spring)
• will haveHW1 next week
• writing assignments andtime-consumingprogramming assignments
be prepared towork hard!
Three Warnings Before (Signing for) the Course (1/3)
警告: High Expectations• goal of NTU DSA class:
as good as the best ones in the world
• tentatively, 6 homework sets and final project
(http://www.csie.ntu.edu.tw/~htlin/course/dsa20spring)
• will haveHW1 next week
• writing assignments andtime-consumingprogramming assignments
be prepared towork hard!
Three Warnings Before (Signing for) the Course (1/3)
警告: High Expectations• goal of NTU DSA class:
as good as the best ones in the world
• tentatively, 6 homework sets and final project
(http://www.csie.ntu.edu.tw/~htlin/course/dsa20spring)
• will haveHW1 next week
• writing assignments andtime-consumingprogramming assignments
be prepared towork hard!
Three Warnings Before (Signing for) the Course (1/3)
警告: High Expectations• goal of NTU DSA class:
as good as the best ones in the world
• tentatively, 6 homework sets and final project
(http://www.csie.ntu.edu.tw/~htlin/course/dsa20spring)
• will haveHW1 next week
• writing assignments andtime-consumingprogramming assignments
be prepared towork hard!
Three Warnings Before (Signing for) the Course (1/3)
警告: High Expectations• goal of NTU DSA class:
as good as the best ones in the world
• tentatively, 6 homework sets and final project
(http://www.csie.ntu.edu.tw/~htlin/course/dsa20spring)
• will haveHW1 next week
• writing assignments andtime-consumingprogramming assignments
be prepared towork hard!
Three Warnings Before (Signing for) the Course (2/3)
警告: Strict Instructor
• Will you give me a second chance if I copy homework from other people? No.
• Could you let me pass because I will be kicked out by the 1/2 rule?No.
• Will you change my score from F to C? No. be prepared tofollow the rules!
Three Warnings Before (Signing for) the Course (2/3)
警告: Strict Instructor
• Will you give me a second chance if I copy homework from other people? No.
• Could you let me pass because I will be kicked out by the 1/2 rule?No.
• Will you change my score from F to C? No. be prepared tofollow the rules!
Three Warnings Before (Signing for) the Course (2/3)
警告: Strict Instructor
• Will you give me a second chance if I copy homework from other people? No.
• Could you let me pass because I will be kicked out by the 1/2 rule?No.
• Will you change my score from F to C? No.
be prepared tofollow the rules!
Three Warnings Before (Signing for) the Course (2/3)
警告: Strict Instructor
• Will you give me a second chance if I copy homework from other people? No.
• Could you let me pass because I will be kicked out by the 1/2 rule?No.
• Will you change my score from F to C? No.
be prepared tofollow the rules!
Three Warnings Before (Signing for) the Course (3/3)
警告: Uncertain Outcome• sixth-time teaching this course, but first timeafter five years
• ambitious and willing toexperiment
—live screencast teaching, for instance
• How many people will not pass? I don’t know yet.
• Will your investment (time) get good return (knowledge)? No guarantees, but I’ll try my best.
be prepared totake some risks!
Three Warnings Before (Signing for) the Course (3/3)
警告: Uncertain Outcome• sixth-time teaching this course, but first timeafter five years
• ambitious and willing toexperiment
—live screencast teaching, for instance
• How many people will not pass? I don’t know yet.
• Will your investment (time) get good return (knowledge)? No guarantees, but I’ll try my best.
be prepared totake some risks!
Three Warnings Before (Signing for) the Course (3/3)
警告: Uncertain Outcome• sixth-time teaching this course, but first timeafter five years
• ambitious and willing toexperiment
—live screencast teaching, for instance
• How many people will not pass?
I don’t know yet.
• Will your investment (time) get good return (knowledge)? No guarantees, but I’ll try my best.
be prepared totake some risks!
Three Warnings Before (Signing for) the Course (3/3)
警告: Uncertain Outcome• sixth-time teaching this course, but first timeafter five years
• ambitious and willing toexperiment
—live screencast teaching, for instance
• How many people will not pass?
I don’t know yet.
• Will your investment (time) get good return (knowledge)?
No guarantees, but I’ll try my best.
be prepared totake some risks!
Three Warnings Before (Signing for) the Course (3/3)
警告: Uncertain Outcome• sixth-time teaching this course, but first timeafter five years
• ambitious and willing toexperiment
—live screencast teaching, for instance
• How many people will not pass?
I don’t know yet.
• Will your investment (time) get good return (knowledge)?
No guarantees, but I’ll try my best.
be prepared totake some risks!
Wise Words
給資訊系的同學們:努力加油
給想加選的同學們:審慎考慮
Some Historical Notes
Once upon a time, when I was a freshman in NTU CSIE (1997)...
• 「計程」有兩學期,上學期教C,下學期教C++
• 大二上學期教「資料結構」
• 大二下學期教「演算法」
Then, in my senior year (2001)...
• 「計程」變成一學期,大一下學期教「物件導向程式設計」(Java)
• 大二上學期教「資料結構與演算法上」
• 大二下學期教「資料結構與演算法下」
Then, starting 2010...
• 物件導向程式設計變為選修
• 大一下學期教「資料結構與演算法」
• 大二上學期教「演算法設計與分析」
Some Historical Notes
Once upon a time, when I was a freshman in NTU CSIE (1997)...
• 「計程」有兩學期,上學期教C,下學期教C++
• 大二上學期教「資料結構」
• 大二下學期教「演算法」
Then, in my senior year (2001)...
• 「計程」變成一學期,大一下學期教「物件導向程式設計」(Java)
• 大二上學期教「資料結構與演算法上」
• 大二下學期教「資料結構與演算法下」
Then, starting 2010...
• 物件導向程式設計變為選修
• 大一下學期教「資料結構與演算法」
• 大二上學期教「演算法設計與分析」
Some Historical Notes
Once upon a time, when I was a freshman in NTU CSIE (1997)...
• 「計程」有兩學期,上學期教C,下學期教C++
• 大二上學期教「資料結構」
• 大二下學期教「演算法」
Then, in my senior year (2001)...
• 「計程」變成一學期,大一下學期教「物件導向程式設計」(Java)
• 大二上學期教「資料結構與演算法上」
• 大二下學期教「資料結構與演算法下」
Then, starting 2010...
• 物件導向程式設計變為選修
• 大一下學期教「資料結構與演算法」
• 大二上學期教「演算法設計與分析」
Some Historical Notes
Once upon a time, when I was a freshman in NTU CSIE (1997)...
• 「計程」有兩學期,上學期教C,下學期教C++
• 大二上學期教「資料結構」
• 大二下學期教「演算法」
Then, in my senior year (2001)...
• 「計程」變成一學期,大一下學期教「物件導向程式設計」(Java)
• 大二上學期教「資料結構與演算法上」
• 大二下學期教「資料結構與演算法下」
Then, starting 2010...
• 物件導向程式設計變為選修
• 大一下學期教「資料結構與演算法」
• 大二上學期教「演算法設計與分析」
Some Historical Notes
Once upon a time, when I was a freshman in NTU CSIE (1997)...
• 「計程」有兩學期,上學期教C,下學期教C++
• 大二上學期教「資料結構」
• 大二下學期教「演算法」
Then, in my senior year (2001)...
• 「計程」變成一學期,大一下學期教「物件導向程式設計」(Java)
• 大二上學期教「資料結構與演算法上」
• 大二下學期教「資料結構與演算法下」
Then, starting 2010...
• 物件導向程式設計變為選修
• 大一下學期教「資料結構與演算法」
• 大二上學期教「演算法設計與分析」
Some Historical Notes
Once upon a time, when I was a freshman in NTU CSIE (1997)...
• 「計程」有兩學期,上學期教C,下學期教C++
• 大二上學期教「資料結構」
• 大二下學期教「演算法」
Then, in my senior year (2001)...
• 「計程」變成一學期,大一下學期教「物件導向程式設計」(Java)
• 大二上學期教「資料結構與演算法上」
• 大二下學期教「資料結構與演算法下」
Then, starting 2010...
• 物件導向程式設計變為選修
• 大一下學期教「資料結構與演算法」
• 大二上學期教「演算法設計與分析」
Some Historical Notes
Once upon a time, when I was a freshman in NTU CSIE (1997)...
• 「計程」有兩學期,上學期教C,下學期教C++
• 大二上學期教「資料結構」
• 大二下學期教「演算法」
Then, in my senior year (2001)...
• 「計程」變成一學期,大一下學期教「物件導向程式設計」(Java)
• 大二上學期教「資料結構與演算法上」
• 大二下學期教「資料結構與演算法下」
Then, starting 2010...
• 物件導向程式設計變為選修
• 大一下學期教「資料結構與演算法」
• 大二上學期教「演算法設計與分析」
Some Historical Notes
Once upon a time, when I was a freshman in NTU CSIE (1997)...
• 「計程」有兩學期,上學期教C,下學期教C++
• 大二上學期教「資料結構」
• 大二下學期教「演算法」
Then, in my senior year (2001)...
• 「計程」變成一學期,大一下學期教「物件導向程式設計」(Java)
• 大二上學期教「資料結構與演算法上」
• 大二下學期教「資料結構與演算法下」
Then, starting 2010...
• 物件導向程式設計變為選修
• 大一下學期教「資料結構與演算法」
• 大二上學期教「演算法設計與分析」
Some Historical Notes
Once upon a time, when I was a freshman in NTU CSIE (1997)...
• 「計程」有兩學期,上學期教C,下學期教C++
• 大二上學期教「資料結構」
• 大二下學期教「演算法」
Then, in my senior year (2001)...
• 「計程」變成一學期,大一下學期教「物件導向程式設計」(Java)
• 大二上學期教「資料結構與演算法上」
• 大二下學期教「資料結構與演算法下」
Then, starting 2010...
• 物件導向程式設計變為選修
• 大一下學期教「資料結構與演算法」
• 大二上學期教「演算法設計與分析」
Reasons
• 兩學期的「計程」變成一學期、「物件導向程式設計」變成選修 :
相信同學們可以有自己學習不同語言的能力。
• 把「資料結構」及「演算法」合成一門課 :
兩者互相依賴,其實不容易分散來教。
• 把「資料結構與演算法上/下」區分成「資料結構與演算法」和
「演算法設計與分析」 :
• 前者以實作為主,銜接計程做更深入的程式練習
• 後者以分析為主,建立在前者的基礎上探討更多不同的演算法
Reasons
• 兩學期的「計程」變成一學期、「物件導向程式設計」變成選修 :
相信同學們可以有自己學習不同語言的能力。
• 把「資料結構」及「演算法」合成一門課 :
兩者互相依賴,其實不容易分散來教。
• 把「資料結構與演算法上/下」區分成「資料結構與演算法」和
「演算法設計與分析」 :
• 前者以實作為主,銜接計程做更深入的程式練習
• 後者以分析為主,建立在前者的基礎上探討更多不同的演算法
Reasons
• 兩學期的「計程」變成一學期、「物件導向程式設計」變成選修 :
相信同學們可以有自己學習不同語言的能力。
• 把「資料結構」及「演算法」合成一門課 :
兩者互相依賴,其實不容易分散來教。
• 把「資料結構與演算法上/下」區分成「資料結構與演算法」和
「演算法設計與分析」 :
• 前者以實作為主,銜接計程做更深入的程式練習
• 後者以分析為主,建立在前者的基礎上探討更多不同的演算法
Basic Information
• instructor:
林軒田Hsuan-Tien Lin (htlin@csie.ntu.edu.tw)
• office hour: after class or by appointment
• course webpage, mailing list:
http://ceiba.ntu.edu.tw/1082dsa01(CEIBA)
• course contents actually in
www.csie.ntu.edu.tw/~htlin/course/dsa20spring
• course time: Tuesdays 13:20–16:20
• 10-min break liberally in the middle
• 10-min more teaching to fit 16 weeks
• 10-min earlier ending (i.e. usually ends 16:10) to be fair
Update your secondary email address on CEIBA!
Basic Information
• instructor:
林軒田Hsuan-Tien Lin (htlin@csie.ntu.edu.tw)
• office hour: after class or by appointment
• course webpage, mailing list:
http://ceiba.ntu.edu.tw/1082dsa01(CEIBA)
• course contents actually in
www.csie.ntu.edu.tw/~htlin/course/dsa20spring
• course time: Tuesdays 13:20–16:20
• 10-min break liberally in the middle
• 10-min more teaching to fit 16 weeks
• 10-min earlier ending (i.e. usually ends 16:10) to be fair Update your secondary email address on CEIBA!
Instructor: Strict but Friendly
• Will you repeat the previous code/slide again? Yes.
• Will you discuss with me after class if I don’t understand? Yes.
• Will you pardon my silly questions? There arenosilly questions. Feel free to ask me questions and give me feedback!
Instructor: Strict but Friendly
• Will you repeat the previous code/slide again? Yes.
• Will you discuss with me after class if I don’t understand? Yes.
• Will you pardon my silly questions? There arenosilly questions. Feel free to ask me questions and give me feedback!
Instructor: Strict but Friendly
• Will you repeat the previous code/slide again? Yes.
• Will you discuss with me after class if I don’t understand? Yes.
• Will you pardon my silly questions?
There arenosilly questions. Feel free to ask me questions and give me feedback!
Instructor: Strict but Friendly
• Will you repeat the previous code/slide again? Yes.
• Will you discuss with me after class if I don’t understand? Yes.
• Will you pardon my silly questions? There arenosilly questions.
Feel free to ask me questions and give me feedback!
Instructor: Strict but Friendly
• Will you repeat the previous code/slide again? Yes.
• Will you discuss with me after class if I don’t understand? Yes.
• Will you pardon my silly questions? There arenosilly questions.
Feel free to ask me questions and give me feedback!
Enrollment
• 98 seats in room 102, limit = 98 ∗ 125% ≈ 123
• priority-based:
• zeroth: NTU CSIE
• first: NTU EECS
• other: NTU
• signup form: https://forms.gle/ETFC3AsQXW2GYYFU7
—will start processing on 03/04/2020
• auditing: welcomed (to sit) only if there is an empty chair please think before you choose to enroll
Enrollment
• 98 seats in room 102, limit = 98 ∗ 125% ≈ 123
• priority-based:
• zeroth: NTU CSIE
• first: NTU EECS
• other: NTU
• signup form: https://forms.gle/ETFC3AsQXW2GYYFU7
—will start processing on 03/04/2020
• auditing: welcomed (to sit) only if there is an empty chair please think before you choose to enroll
Enrollment
• 98 seats in room 102, limit = 98 ∗ 125% ≈ 123
• priority-based:
• zeroth: NTU CSIE
• first: NTU EECS
• other: NTU
• signup form: https://forms.gle/ETFC3AsQXW2GYYFU7
—will start processing on 03/04/2020
• auditing: welcomed (to sit) only if there is an empty chair please think before you choose to enroll
Enrollment
• 98 seats in room 102, limit = 98 ∗ 125% ≈ 123
• priority-based:
• zeroth: NTU CSIE
• first: NTU EECS
• other: NTU
• signup form: https://forms.gle/ETFC3AsQXW2GYYFU7
—will start processing on 03/04/2020
• auditing: welcomed (to sit) only if there is an empty chair
please think before you choose to enroll
Enrollment
• 98 seats in room 102, limit = 98 ∗ 125% ≈ 123
• priority-based:
• zeroth: NTU CSIE
• first: NTU EECS
• other: NTU
• signup form: https://forms.gle/ETFC3AsQXW2GYYFU7
—will start processing on 03/04/2020
• auditing: welcomed (to sit) only if there is an empty chair please think before you choose to enroll
Teaching Assistants
• TAs (tentatively): 陳佳佑、周侑廷、李鈺昇、楊皓丞、吳崇維
• TA email: dsa_ta@csie.ntu.edu.tw
—5 TAs and 1 instructor around, usually faster than sending to individual
• office hours: to be announced
very friendly TAs; ask them more questions!
Teaching Assistants
• TAs (tentatively): 陳佳佑、周侑廷、李鈺昇、楊皓丞、吳崇維
• TA email: dsa_ta@csie.ntu.edu.tw
—5 TAs and 1 instructor around, usually faster than sending to individual
• office hours: to be announced
very friendly TAs; ask them more questions!
Teaching Assistants
• TAs (tentatively): 陳佳佑、周侑廷、李鈺昇、楊皓丞、吳崇維
• TA email: dsa_ta@csie.ntu.edu.tw
—5 TAs and 1 instructor around, usually faster than sending to individual
• office hours: to be announced
very friendly TAs; ask them more questions!
Teaching Assistants
• TAs (tentatively): 陳佳佑、周侑廷、李鈺昇、楊皓丞、吳崇維
• TA email: dsa_ta@csie.ntu.edu.tw
—5 TAs and 1 instructor around, usually faster than sending to individual
• office hours: to be announced
very friendly TAs; ask them more questions!
THE Principle
Taking any unfair advantages over other class members is not allowed.
It is everyone’s responsibility to maximize the level of fairness.
• eating? fine, but no smells and no noise
• sleeping? fine, but no snoring
• cellphone? fine, but silent mode, and speak outside
• ...
applies to instructor, TAs, students
THE Principle
Taking any unfair advantages over other class members is not allowed.
It is everyone’s responsibility to maximize the level of fairness.
• eating? fine, but no smells and no noise
• sleeping? fine, but no snoring
• cellphone? fine, but silent mode, and speak outside
• ...
applies to instructor, TAs, students
THE Principle
Taking any unfair advantages over other class members is not allowed.
It is everyone’s responsibility to maximize the level of fairness.
• eating? fine, but no smells and no noise
• sleeping? fine, but no snoring
• cellphone? fine, but silent mode, and speak outside
• ...
applies to instructor, TAs, students
THE Principle
Taking any unfair advantages over other class members is not allowed.
It is everyone’s responsibility to maximize the level of fairness.
• eating? fine, but no smells and no noise
• sleeping? fine, but no snoring
• cellphone? fine, but silent mode, and speak outside
• ...
applies to instructor, TAs, students
THE Principle
Taking any unfair advantages over other class members is not allowed.
It is everyone’s responsibility to maximize the level of fairness.
• eating? fine, but no smells and no noise
• sleeping? fine, but no snoring
• cellphone? fine, but silent mode, and speak outside
• ...
applies to instructor, TAs, students
Honesty
NO CHEATING NO LYING NO PLAGIARISM
very very very very serious consequences
Honesty
NO CHEATING NO LYING NO PLAGIARISM
very very very very serious consequences
Grade
• homework (best * 1.5 + worst * 0.5 + others), midterm, final project
• supplementary reference: participation in discussions
• raw score goes through some order-preserving normalization steps,not just using default thresholds of university
• raw score 80 with term rank A: possible
• raw score 80 with term rank B: possible
• raw score 60 with term rank F: possible
• raw scores 80, 60 with term scores B, B: possible, but unlikely
• raw scores 80, 60 with term scores F, B:impossible from the principle: no individual score change
Grade
• homework (best * 1.5 + worst * 0.5 + others), midterm, final project
• supplementary reference: participation in discussions
• raw score goes through some order-preserving normalization steps,not just using default thresholds of university
• raw score 80 with term rank A: possible
• raw score 80 with term rank B: possible
• raw score 60 with term rank F: possible
• raw scores 80, 60 with term scores B, B: possible, but unlikely
• raw scores 80, 60 with term scores F, B:impossible from the principle: no individual score change
Grade
• homework (best * 1.5 + worst * 0.5 + others), midterm, final project
• supplementary reference: participation in discussions
• raw score goes through some order-preserving normalization steps,not just using default thresholds of university
• raw score 80 with term rank A: possible
• raw score 80 with term rank B: possible
• raw score 60 with term rank F: possible
• raw scores 80, 60 with term scores B, B: possible, but unlikely
• raw scores 80, 60 with term scores F, B:impossible from the principle: no individual score change
Grade
• homework (best * 1.5 + worst * 0.5 + others), midterm, final project
• supplementary reference: participation in discussions
• raw score goes through some order-preserving normalization steps,not just using default thresholds of university
• raw score 80 with term rank A: possible
• raw score 80 with term rank B: possible
• raw score 60 with term rank F: possible
• raw scores 80, 60 with term scores B, B: possible, but unlikely
• raw scores 80, 60 with term scores F, B:impossible from the principle: no individual score change
Grade
• homework (best * 1.5 + worst * 0.5 + others), midterm, final project
• supplementary reference: participation in discussions
• raw score goes through some order-preserving normalization steps,not just using default thresholds of university
• raw score 80 with term rank A: possible
• raw score 80 with term rank B: possible
• raw score 60 with term rank F: possible
• raw scores 80, 60 with term scores B, B: possible, but unlikely
• raw scores 80, 60 with term scores F, B:impossible from the principle: no individual score change
Grade
• homework (best * 1.5 + worst * 0.5 + others), midterm, final project
• supplementary reference: participation in discussions
• raw score goes through some order-preserving normalization steps,not just using default thresholds of university
• raw score 80 with term rank A: possible
• raw score 80 with term rank B: possible
• raw score 60 with term rank F: possible
• raw scores 80, 60 with term scores B, B: possible, but unlikely
• raw scores 80, 60 with term scores F, B:impossible from the principle: no individual score change
Grade
• homework (best * 1.5 + worst * 0.5 + others), midterm, final project
• supplementary reference: participation in discussions
• raw score goes through some order-preserving normalization steps,not just using default thresholds of university
• raw score 80 with term rank A: possible
• raw score 80 with term rank B: possible
• raw score 60 with term rank F: possible
• raw scores 80, 60 with term scores B, B: possible, but unlikely
• raw scores 80, 60 with term scores F, B:impossible
from the principle: no individual score change
Grade
• homework (best * 1.5 + worst * 0.5 + others), midterm, final project
• supplementary reference: participation in discussions
• raw score goes through some order-preserving normalization steps,not just using default thresholds of university
• raw score 80 with term rank A: possible
• raw score 80 with term rank B: possible
• raw score 60 with term rank F: possible
• raw scores 80, 60 with term scores B, B: possible, but unlikely
• raw scores 80, 60 with term scores F, B:impossible from the principle: no individual score change
Collaboration and Open-Book
• homework discussions: encouraged
• but fairness?
write the final solutions alone and understand them fully
• references (books, notes, Internet): consulted, butnot copied from
• no need to lend/borrow solutions
to maximize fairness (everyone’s responsibility), lending/borrowing/buying/selling not allowed
Collaboration and Open-Book
• homework discussions: encouraged
• but fairness?
write the final solutions alone and understand them fully
• references (books, notes, Internet): consulted, butnot copied from
• no need to lend/borrow solutions
to maximize fairness (everyone’s responsibility), lending/borrowing/buying/selling not allowed
Collaboration and Open-Book
• homework discussions: encouraged
• but fairness?
write the final solutions alone and understand them fully
• references (books, notes, Internet):
consulted, butnot copied from
• no need to lend/borrow solutions
to maximize fairness (everyone’s responsibility), lending/borrowing/buying/selling not allowed
Collaboration and Open-Book
• homework discussions: encouraged
• but fairness?
write the final solutions alone and understand them fully
• references (books, notes, Internet):
consulted, butnot copied from
• no need to lend/borrow solutions
to maximize fairness (everyone’s responsibility), lending/borrowing/buying/selling not allowed
Collaboration and Open-Book
to maximize fairness (everyone’s responsibility), lending/borrowing/buying/selling not allowed
to maximize fairness (everyone’s responsibility), lending/borrowing/buying/selling not allowed to maximize fairness (everyone’s responsibility), lending/borrowing/buying/selling not allowed Deal? If your classmate wants to borrow homework from you,
what do you say?
Collaboration and Open-Book
to maximize fairness (everyone’s responsibility), lending/borrowing/buying/selling not allowed to maximize fairness (everyone’s responsibility), lending/borrowing/buying/selling not allowed
to maximize fairness (everyone’s responsibility), lending/borrowing/buying/selling not allowed Deal? If your classmate wants to borrow homework from you,
what do you say?
Collaboration and Open-Book
to maximize fairness (everyone’s responsibility), lending/borrowing/buying/selling not allowed to maximize fairness (everyone’s responsibility), lending/borrowing/buying/selling not allowed to maximize fairness (everyone’s responsibility), lending/borrowing/buying/selling not allowed
Deal? If your classmate wants to borrow homework from you, what do you say?
Collaboration and Open-Book
to maximize fairness (everyone’s responsibility), lending/borrowing/buying/selling not allowed to maximize fairness (everyone’s responsibility), lending/borrowing/buying/selling not allowed to maximize fairness (everyone’s responsibility), lending/borrowing/buying/selling not allowed Deal? If your classmate wants to borrow homework from you,
what do you say?
Homework
• students: justify solutions clearly
• TAs: evaluate solutions fairly
• no individual extension unless not violating the principle (e.g. institute-established cases of illness or emergency)
• late penalty:
90% of the value for 12-hour late, 80% of value for 24-hour late, ... four penalty-free late half-days (金金金牌牌牌) per person
Homework
• students: justify solutions clearly
• TAs: evaluate solutions fairly
• no individual extension unless not violating the principle (e.g.
institute-established cases of illness or emergency)
• late penalty:
90% of the value for 12-hour late, 80% of value for 24-hour late, ... four penalty-free late half-days (金金金牌牌牌) per person
Homework
• students: justify solutions clearly
• TAs: evaluate solutions fairly
• no individual extension unless not violating the principle (e.g.
institute-established cases of illness or emergency)
• late penalty:
90% of the value for 12-hour late, 80% of value for 24-hour late, ...
four penalty-free late half-days (金金金牌牌牌) per person
Homework
• students: justify solutions clearly
• TAs: evaluate solutions fairly
• no individual extension unless not violating the principle (e.g.
institute-established cases of illness or emergency)
• late penalty:
90% of the value for 12-hour late, 80% of value for 24-hour late, ...
four penalty-free late half-days (金金金牌牌牌) per person
Textbook
Data Structures and Algorithms in C++, 2nd Edition by Goodrich, Tamassia and Mount.
• please get it as early as possible
• will teach selected parts from it, andask you to read others learning to read a textbook is part of the course
Textbook
Data Structures and Algorithms in C++, 2nd Edition by Goodrich, Tamassia and Mount.
• please get it as early as possible
• will teach selected parts from it, andask you to read others learning to read a textbook is part of the course
Getting the Book to Read
• NTU Library: reserved copy in the shared course material area
• R536: will put some shared copies to be read in the room
• If the book is not affordable to you: email me
(htlin@csie.ntu.edu.tw) and I’ll see how I can help.
Getting the Book to Read
• NTU Library: reserved copy in the shared course material area
• R536: will put some shared copies to be read in the room
• If the book is not affordable to you: email me
(htlin@csie.ntu.edu.tw) and I’ll see how I can help.
Getting the Book to Read
• NTU Library: reserved copy in the shared course material area
• R536: will put some shared copies to be read in the room
• If the book is not affordable to you: email me
(htlin@csie.ntu.edu.tw) and I’ll see how I can help.
Reading Assignments
• weekly
• sections related to what we teach, or sections that are worth reading by yourself
—we cannot teach all, but with reading you can learn all
• 3-6: 3 hour teaching, 6 hour reading/writing after class
some problems related to reading assignments may show up in your writing assignments as well
Reading Assignments
• weekly
• sections related to what we teach, or sections that are worth reading by yourself
—we cannot teach all, but with reading you can learn all
• 3-6: 3 hour teaching, 6 hour reading/writing after class
some problems related to reading assignments may show up in your writing assignments as well
Reading Assignments
• weekly
• sections related to what we teach, or sections that are worth reading by yourself
—we cannot teach all, but with reading you can learn all
• 3-6: 3 hour teaching, 6 hour reading/writing after class
some problems related to reading assignments may show up in your writing assignments as well
Reading Assignments
• weekly
• sections related to what we teach, or sections that are worth reading by yourself
—we cannot teach all, but with reading you can learn all
• 3-6: 3 hour teaching, 6 hour reading/writing after class
some problems related to reading assignments may show up in your writing assignments as well
Mandarin and English
• Mandarin: main language
• English: often encountered
—coding, website, assignments, some teaching . . .
—important for your future and you are recommended to practice don’t be afraid of English
Mandarin and English
• Mandarin: main language
• English: often encountered
—coding, website, assignments, some teaching . . .
—important for your future and you are recommended to practice don’t be afraid of English
Mandarin and English
• Mandarin: main language
• English: often encountered
—coding, website, assignments, some teaching . . .
—important for your future and you are recommended to practice
don’t be afraid of English
Mandarin and English
• Mandarin: main language
• English: often encountered
—coding, website, assignments, some teaching . . .
—important for your future and you are recommended to practice don’t be afraid of English
How to Pass the Class?
• catch up from day 1
• ask questions!
• have fun writing programs
• understand writing proof
Important TODOs
• Update your secondary email address on CEIBA
• Read the policy on the website thoroughly Enjoy the Class! Questions?