Bilgisayar Mühendisliği

CE 221 | Ders Tanıtım Bilgileri

Dersin Adı

Data Structures and Algorithms I

Kodu	Yarıyıl	Teori (saat/hafta)	Uygulama/Lab (saat/hafta)	Yerel Kredi	AKTS
CE 221	FALL	3	2	4	7

Ön-Koşul(lar)	SE 116 To get a grade of at least FD
Dersin Dili	English
Dersin Türü	Zorunlu
Dersin Düzeyi	Lisans
Dersin Veriliş Şekli	Face-To-Face
Dersin Öğretim Yöntem ve Teknikleri	Problem Solving Application: Experiment / Laboratory / Workshop Lecture / Presentation
Ulusal Meslek Sınıflandırma Kodu	-
Dersin Koordinatörü	Prof. Dr. Cem Evrendilek
Öğretim Eleman(lar)ı	Dr. Öğr. Üyesi Kaya Oğuz Prof. Dr. Cem Evrendilek Dr. Öğr. Üyesi Çağlar Durmaz
Yardımcı(ları)	Araş. Gör. Melek Büşra Temuçin

Dersin Amacı

The objective of this course is to teach students the notion of an abstract data type (ADT) which is central to the design and analysis of computer algorithms. This course introduces abstract data types, and presents algorithms and data structures for implementing several ADTs. It emphasizes the efficiency of algorithms as evaluated by asymptotic analysis of running time. The programming assignments will be given in the programming languages taught in SE 115 and/or SE116.

Öğrenme Çıktıları

Bu dersi başarıyla tamamlayabilen öğrenciler;

Ad	Açıklama	PC Alt	* Katkı Düzeyi
Ad	Açıklama	PC Alt	1	2	3	4	5
LO1	will be able to analyze the loop structures of either recursive or non-recursive algorithms to express their asymptotic running times using big-Oh notation.					X
LO2	will be able to assess the relative advantages of using array or linked list implementations versus hashing in efficiently solving search problems with concurrent insertion, and/or deletions on collections of data.					X
LO3	will be able to develop efficient computer programs running in O (log n) per searching, insertion and/or deletion of data items by employing correct variants of tree data structures covered in the course.						X
LO4	will be able to select the right sorting algorithm for efficient applications requiring an order on data items.					X
LO5	will be able to describe the usage of various data structures.					X
LO6	will be able to explain the operations for maintaining common data structures.					X
LO7	will be able to devise appropriate data structures for solving specific computing problems.						X
LO8	will be able to use various graph algorithms to design solutions to simple computing problems.						X

Ders Tanımı

Algorithm analysis, linear data structures, trees, hashing, priority queues, sorting, and graph algorithms.

Dersin İlişkili Olduğu Sürdürülebilir Kalkınma Amaçları

Dersin Kategorisi	Temel Ders	X
	Uzmanlık/Alan Dersleri
	Destek Dersleri
	İletişim ve Yönetim Becerileri Dersleri
	Aktarılabilir Beceri Dersleri

HAFTALIK KONULAR VE İLGİLİ ÖN HAZIRLIK ÇALIŞMALARI

Hafta	Konular	Ön Hazırlık	Öğrenme Çıktısı
1	Introduction: Mathematics Review and Recursion	M. A. Weiss, Data Structures and Algorithm Analysis in Java, 3/e, Pearson, 2012 (Ch. 1.1, 1.2, 1.3)	LO1
2	Algorithm Analysis (basic concepts of algorithms, modeling runtimes, recurrences, Big-Oh notations, Running Time Calculations)	M. A. Weiss, Data Structures and Algorithm Analysis in Java, 3/e, Pearson, 2012 (Ch. 2.1, 2.2, 2.3)	LO1
3	Algorithm Analysis and Linear Data Structures: (Linked Lists)	M. A. Weiss, Data Structures and Algorithm Analysis in Java, 3/e, Pearson, 2012 (Ch. 2.4, 3.1 - 3.5)	LO2
4	Linear Data Structures (Linked Lists, Stacks, Stack Applications)	M. A. Weiss, Data Structures and Algorithm Analysis in Java, 3/e, Pearson, 2012 (Ch. 3.5, 3.6)	LO2
5	Linear Data Structures (Queues) and Trees (Binary trees)	M. A. Weiss, Data Structures and Algorithm Analysis in Java, 3/e, Pearson, 2012 (Ch. 3.7, 4.1, 4.2)	LO5
6	Trees (Binary search trees)	M. A. Weiss, Data Structures and Algorithm Analysis in Java, 3/e, Pearson, 2012 (Ch. 4.3)	LO3
7	Trees (AVL Trees)	M. A. Weiss, Data Structures and Algorithm Analysis in in Java, 3/e, Pearson, 2012 (Ch. 4.4)	LO3
8	Midterm		-
9	Hashing	M. A. Weiss, Data Structures and Algorithm Analysis in Java, 3/e, Pearson, 2012 (Ch. 5.1 – 5.5)	LO6
10	Priority Queues: Binary Heaps	M. A. Weiss, Data Structures and Algorithm Analysis in Java, 3/e, Pearson, 2012 (Ch. 6.1, 6.2, 6.3)	LO7
11	Sorting (Insertion Sort, Shellsort, Heapsort)	M. A. Weiss, Data Structures and Algorithm Analysis in Java, 3/e, Pearson, 2012 (Ch. 7.1, 7.2, 7.3, 7.4, 7.5)	LO4
12	Sorting (Mergesort, Quicksort)	M. A. Weiss, Data Structures and Algorithm Analysis in Java, 3/e, Pearson, 2012 (Ch. 7.6, 7.7)	LO4
13	Graph Algorithms (Definitions, Representation, Topological Sort)	M. A. Weiss, Data Structures and Algorithm Analysis in Java, 3/e, Pearson, 2012 (Ch. 9.1 - 9.2)	LO8
14	Graph Algorithms (Shortest Path Algorithms)	M. A. Weiss, Data Structures and Algorithm Analysis in Java, 3/e, Pearson, 2012 (Bölüm 9.3)	LO8
15	Semester Review		-
16	Final Exam		-

Ders Kitabı	M. A. Weiss. Data Structures and Algorithm Analysis in Java. 3/e. Pearson. 2012. 978-0132576277
Önerilen Okumalar/Materyaller	R. Sedgewick. K. Wayne. Algorithms. 4/e. Addison-Wesley Professional. 2011. 978-0321573513.

DEĞERLENDİRME ÖLÇÜTLERİ

Yarıyıl Aktiviteleri	Sayı	Katkı Payı %	LO1	LO2	LO3	LO4	LO5	LO6	LO7	LO8
Laboratuvar / Uygulama	1	40	X	X	X	X	X	X	X	X
Ara Sınav	1	20	X	X	X		X
Final Sınavı	1	40				X		X	X	X
Toplam	3	100

AKTS / İŞ YÜKÜ TABLOSU

Yarıyıl Aktiviteleri	Sayı	Süre (Saat)	İş Yükü
Katılım	-	-	-
Teorik Ders Saati	16	3	48
Laboratuvar / Uygulama Ders Saati	16	2	32
Sınıf Dışı Ders Çalışması	14	3	42
Arazi Çalışması	-	-	-
Küçük Sınav / Stüdyo Kritiği	-	-	-
Portfolyo	-	-	-
Ödev	13	3	39
Sunum / Jüri Önünde Sunum	-	-	-
Proje	-	-	-
Seminer/Çalıştay	-	-	-
Sözlü Sınav	-	-	-
Ara Sınavlar	1	24	24
Final Sınavı	1	25	25
		Toplam	210