WEBVTT 1 00:00:00.000 --> 00:00:01.320 In this lesson, 2 00:00:01.320 --> 00:00:04.380 we will learn about safe functions. 3 00:00:04.380 --> 00:00:07.200 Safe functions are programming functions 4 00:00:07.200 --> 00:00:10.620 that operate securely and reliably. 5 00:00:10.620 --> 00:00:14.670 Safe function concepts include atomic functions, 6 00:00:14.670 --> 00:00:18.810 memory-safe functions, and thread-safe functions. 7 00:00:18.810 --> 00:00:20.880 Atomic functions are designed 8 00:00:20.880 --> 00:00:25.650 to complete operations in a single indivisible step, 9 00:00:25.650 --> 00:00:27.390 ensuring that the operation 10 00:00:27.390 --> 00:00:31.590 is either fully completed or not executed at all. 11 00:00:31.590 --> 00:00:34.530 Next, memory-safe functions are used 12 00:00:34.530 --> 00:00:37.980 to prevent common memory-related vulnerabilities 13 00:00:37.980 --> 00:00:42.000 such as buffer overflows or memory leaks. 14 00:00:42.000 --> 00:00:44.340 Finally, thread-safe functions 15 00:00:44.340 --> 00:00:48.720 ensure that when multiple threads execute simultaneously, 16 00:00:48.720 --> 00:00:51.630 the thread-safe function operates correctly 17 00:00:51.630 --> 00:00:55.380 without causing race conditions or data corruption. 18 00:00:55.380 --> 00:00:58.140 Let's learn more about atomic functions, 19 00:00:58.140 --> 00:01:02.130 memory-safe functions, and thread-safe functions. 20 00:01:02.130 --> 00:01:05.430 First, we have atomic functions. 21 00:01:05.430 --> 00:01:08.160 Atomic functions are designed to ensure 22 00:01:08.160 --> 00:01:13.160 that an operation completes as a single indivisible action, 23 00:01:13.200 --> 00:01:15.600 providing strong data consistency 24 00:01:15.600 --> 00:01:19.200 and stability in concurrent environments. 25 00:01:19.200 --> 00:01:20.430 In other words, 26 00:01:20.430 --> 00:01:23.730 atomic functions either fully complete an action 27 00:01:23.730 --> 00:01:25.860 or they do nothing at all. 28 00:01:25.860 --> 00:01:28.350 There's no in-between state. 29 00:01:28.350 --> 00:01:32.370 This quality is critical in systems where multiple threads 30 00:01:32.370 --> 00:01:36.150 or processes operate simultaneously 31 00:01:36.150 --> 00:01:38.550 as it prevents one process 32 00:01:38.550 --> 00:01:41.160 from partially completing an operation 33 00:01:41.160 --> 00:01:44.490 and leaving data in an inconsistent state. 34 00:01:44.490 --> 00:01:46.830 In this way, atomic functions 35 00:01:46.830 --> 00:01:49.800 help avoid issues like race conditions 36 00:01:49.800 --> 00:01:52.380 where two or more processes attempt 37 00:01:52.380 --> 00:01:55.860 to modify the same data simultaneously, 38 00:01:55.860 --> 00:01:59.940 leading to conflicts and unpredictable results. 39 00:01:59.940 --> 00:02:02.820 To better understand atomic functions, 40 00:02:02.820 --> 00:02:05.160 let's think about a banking system 41 00:02:05.160 --> 00:02:08.790 where users can transfer money between accounts. 42 00:02:08.790 --> 00:02:12.360 If a function handling the transfer is atomic, 43 00:02:12.360 --> 00:02:15.540 it ensures that either the full amount is transferred 44 00:02:15.540 --> 00:02:19.500 or nothing at all is, there's no partial transfer. 45 00:02:19.500 --> 00:02:23.550 This concept prevents issues where one account is debited, 46 00:02:23.550 --> 00:02:26.160 but the other is not credited, 47 00:02:26.160 --> 00:02:29.160 which could lead to inaccurate balances. 48 00:02:29.160 --> 00:02:31.260 By implementing atomic functions 49 00:02:31.260 --> 00:02:35.040 in critical areas like financial transactions, 50 00:02:35.040 --> 00:02:38.160 we ensure that processes execute in a way 51 00:02:38.160 --> 00:02:40.650 that either completes entirely 52 00:02:40.650 --> 00:02:43.050 or does not affect the data at all, 53 00:02:43.050 --> 00:02:46.920 maintaining data integrity and consistency. 54 00:02:46.920 --> 00:02:49.920 So, to implement atomic functions, 55 00:02:49.920 --> 00:02:53.460 developers use built-in atomic operations 56 00:02:53.460 --> 00:02:57.090 provided by programming languages or libraries, 57 00:02:57.090 --> 00:03:01.410 such as atomic variables or mutex locks. 58 00:03:01.410 --> 00:03:04.830 A mutex lock is a synchronization mechanism 59 00:03:04.830 --> 00:03:06.840 that allows only one thread 60 00:03:06.840 --> 00:03:10.140 to access a shared resource at a time, 61 00:03:10.140 --> 00:03:13.590 preventing concurrent access conflicts. 62 00:03:13.590 --> 00:03:16.530 Atomic functions then protect data 63 00:03:16.530 --> 00:03:19.230 by preventing partial modifications 64 00:03:19.230 --> 00:03:21.330 and ensuring exclusive access 65 00:03:21.330 --> 00:03:25.470 to a resource or variable during operation. 66 00:03:25.470 --> 00:03:27.630 So, by designing functions 67 00:03:27.630 --> 00:03:30.840 to execute in a fully contained manner, 68 00:03:30.840 --> 00:03:34.080 atomic functions provide a reliable way 69 00:03:34.080 --> 00:03:36.630 to manage data consistency 70 00:03:36.630 --> 00:03:40.050 in complex concurrent environments. 71 00:03:40.050 --> 00:03:43.710 Second, we have memory-safe functions. 72 00:03:43.710 --> 00:03:48.300 Memory-safe functions focus on securely managing memory 73 00:03:48.300 --> 00:03:51.270 in a way that avoids common vulnerabilities 74 00:03:51.270 --> 00:03:53.100 like buffer overflows, 75 00:03:53.100 --> 00:03:56.970 memory leaks, and segmentation faults. 76 00:03:56.970 --> 00:03:59.190 Memory-safe functions ensure 77 00:03:59.190 --> 00:04:03.600 that allocated memory does not exceed what is available, 78 00:04:03.600 --> 00:04:05.430 and that memory boundaries 79 00:04:05.430 --> 00:04:09.540 are respected during data storage and access. 80 00:04:09.540 --> 00:04:12.600 So, when functions are memory-safe, 81 00:04:12.600 --> 00:04:16.710 they automatically free up memory no longer in use 82 00:04:16.710 --> 00:04:20.580 and avoid scenarios where invalid memory access 83 00:04:20.580 --> 00:04:22.020 can lead to crashes 84 00:04:22.020 --> 00:04:25.770 or even exploitation by malicious actors. 85 00:04:25.770 --> 00:04:29.100 To better understand memory-safe functions, 86 00:04:29.100 --> 00:04:33.150 consider an application that handles large data files. 87 00:04:33.150 --> 00:04:37.080 If the application uses memory-safe functions, 88 00:04:37.080 --> 00:04:39.870 it ensures that each chunk of data 89 00:04:39.870 --> 00:04:42.660 fits within the available memory, 90 00:04:42.660 --> 00:04:46.590 avoiding buffer overflows that could cause the application 91 00:04:46.590 --> 00:04:49.890 to crash or behave unpredictably. 92 00:04:49.890 --> 00:04:52.770 when handling memory in this controlled way, 93 00:04:52.770 --> 00:04:56.580 memory-safe functions prevent unintentional access 94 00:04:56.580 --> 00:04:59.130 to other parts of system memory, 95 00:04:59.130 --> 00:05:03.300 protecting data integrity and application stability. 96 00:05:03.300 --> 00:05:08.300 Additionally, by automatically managing memory deallocation, 97 00:05:08.310 --> 00:05:12.300 memory-safe functions help prevent memory leaks, 98 00:05:12.300 --> 00:05:15.960 which can gradually consume all available memory 99 00:05:15.960 --> 00:05:20.960 and degrade performance over time or cause system crashes. 100 00:05:21.450 --> 00:05:24.690 So, to create memory-safe functions, 101 00:05:24.690 --> 00:05:27.180 developers use programming languages 102 00:05:27.180 --> 00:05:32.010 that emphasize memory safety like Rust or Java, 103 00:05:32.010 --> 00:05:35.820 which manage memory automatically through garbage collection 104 00:05:35.820 --> 00:05:38.610 or strict compile time checks. 105 00:05:38.610 --> 00:05:42.960 For languages that do not provide inherent memory safety, 106 00:05:42.960 --> 00:05:47.960 like C or C++, developers use specific libraries 107 00:05:47.970 --> 00:05:52.530 designed for safe memory allocation and deallocation, 108 00:05:52.530 --> 00:05:55.290 employing things like smart pointers. 109 00:05:55.290 --> 00:05:57.750 A smart pointer is an object 110 00:05:57.750 --> 00:06:01.230 in a programming language that manages the lifetime 111 00:06:01.230 --> 00:06:05.820 and ownership of dynamically allocated memory automatically, 112 00:06:05.820 --> 00:06:07.830 ensuring proper allocation 113 00:06:07.830 --> 00:06:11.250 and deallocation to prevent memory leaks. 114 00:06:11.250 --> 00:06:14.220 In the end, adopting memory-safe functions 115 00:06:14.220 --> 00:06:17.520 and using secure memory management practices 116 00:06:17.520 --> 00:06:19.200 ensures applications 117 00:06:19.200 --> 00:06:22.860 can handle data efficiently and securely. 118 00:06:22.860 --> 00:06:27.270 Third and last, we have thread-safe functions. 119 00:06:27.270 --> 00:06:29.280 Thread-safe functions ensure 120 00:06:29.280 --> 00:06:32.010 that a function operates reliably 121 00:06:32.010 --> 00:06:34.230 when accessing shared data 122 00:06:34.230 --> 00:06:38.190 with multiple execution threads at the same time, 123 00:06:38.190 --> 00:06:42.600 preventing issues like race conditions and data corruption. 124 00:06:42.600 --> 00:06:44.383 Unlike atomic functions, 125 00:06:44.383 --> 00:06:48.497 which complete operations in a single indivisible step 126 00:06:48.497 --> 00:06:50.790 and memory-safe functions, 127 00:06:50.790 --> 00:06:54.120 which protect against memory-related vulnerabilities, 128 00:06:54.120 --> 00:06:57.150 thread-safe functions specifically focus 129 00:06:57.150 --> 00:07:00.120 on managing execution concurrency 130 00:07:00.120 --> 00:07:03.330 to prevent conflicts between threads. 131 00:07:03.330 --> 00:07:06.480 So, in multi-threaded applications, 132 00:07:06.480 --> 00:07:09.900 thread-safety ensures concurrent operations 133 00:07:09.900 --> 00:07:12.240 do not interfere with each other, 134 00:07:12.240 --> 00:07:15.900 creating predictable and expected outcomes. 135 00:07:15.900 --> 00:07:20.250 So, thread-safe functions are needed when data consistency 136 00:07:20.250 --> 00:07:23.580 and reliability must be maintained 137 00:07:23.580 --> 00:07:25.380 even when multiple threads 138 00:07:25.380 --> 00:07:29.010 are modifying shared data simultaneously. 139 00:07:29.010 --> 00:07:32.010 Now, let's think of an online shopping cart 140 00:07:32.010 --> 00:07:33.450 where multiple users 141 00:07:33.450 --> 00:07:36.990 may be trying to add items simultaneously 142 00:07:36.990 --> 00:07:40.320 to the same application's shopping cart. 143 00:07:40.320 --> 00:07:44.640 If the functions handling the cart updates are thread-safe, 144 00:07:44.640 --> 00:07:46.500 they prevent data conflicts 145 00:07:46.500 --> 00:07:50.940 and maintain accurate cart totals for each user. 146 00:07:50.940 --> 00:07:52.590 Without thread-safety, 147 00:07:52.590 --> 00:07:55.890 two users adding items at the same time 148 00:07:55.890 --> 00:07:59.820 could inadvertently overwrite each other's changes, 149 00:07:59.820 --> 00:08:02.910 leading to incorrect cart totals. 150 00:08:02.910 --> 00:08:06.180 By making these operations thread-safe, 151 00:08:06.180 --> 00:08:09.480 each action can proceed without interference 152 00:08:09.480 --> 00:08:11.820 from or to the others, 153 00:08:11.820 --> 00:08:15.840 ensuring data integrity for all users. 154 00:08:15.840 --> 00:08:20.310 So, to make functions thread-safe, developers use techniques 155 00:08:20.310 --> 00:08:23.160 like locking mechanisms, such as mutexs 156 00:08:23.160 --> 00:08:26.250 to control access to shared resources, 157 00:08:26.250 --> 00:08:28.260 ensuring that only one thread 158 00:08:28.260 --> 00:08:32.040 can modify a single resource at any one time. 159 00:08:32.040 --> 00:08:35.880 Alternatively, developers could use atomic functions 160 00:08:35.880 --> 00:08:38.040 or thread-safe data structures 161 00:08:38.040 --> 00:08:39.687 that are specifically designed 162 00:08:39.687 --> 00:08:42.254 to handle concurrent modifications. 163 00:08:42.254 --> 00:08:46.620 At any rate, by prioritizing thread-safe practices, 164 00:08:46.620 --> 00:08:48.720 developers enable applications 165 00:08:48.720 --> 00:08:52.320 to run reliably in multi-threaded environments, 166 00:08:52.320 --> 00:08:55.440 maintaining stable consistent behavior 167 00:08:55.440 --> 00:08:59.610 even when multiple operations are occurring at once. 168 00:08:59.610 --> 00:09:04.200 So, remember, safe functions are programming methods 169 00:09:04.200 --> 00:09:08.250 designed to execute securely and reliably, 170 00:09:08.250 --> 00:09:13.250 ensuring data integrity and consistent application behavior. 171 00:09:13.320 --> 00:09:17.340 Safe function concepts include atomic functions, 172 00:09:17.340 --> 00:09:21.128 memory-safe functions, and thread-safe functions. 173 00:09:21.128 --> 00:09:26.010 Atomic functions operate as single indivisible steps, 174 00:09:26.010 --> 00:09:29.610 ensuring that an operation is either fully completed 175 00:09:29.610 --> 00:09:31.560 or not executed at all, 176 00:09:31.560 --> 00:09:34.770 preventing issues in concurrent operations. 177 00:09:34.770 --> 00:09:38.880 Next, memory-safe functions manage memory carefully 178 00:09:38.880 --> 00:09:40.620 to prevent vulnerabilities 179 00:09:40.620 --> 00:09:43.980 like buffer overflows and memory leaks, 180 00:09:43.980 --> 00:09:47.850 ensuring that allocated memory is used correctly 181 00:09:47.850 --> 00:09:51.810 and released back to the system when no longer needed. 182 00:09:51.810 --> 00:09:56.520 Finally, thread-safe functions handle simultaneous access 183 00:09:56.520 --> 00:09:58.080 by multiple threads 184 00:09:58.080 --> 00:10:01.680 without causing conflicts or data corruption, 185 00:10:01.680 --> 00:10:06.680 maintaining data accuracy even during concurrent operations. 186 00:10:06.750 --> 00:10:11.190 Together, these safe function types form a framework 187 00:10:11.190 --> 00:10:14.760 for developing secure stable applications 188 00:10:14.760 --> 00:10:18.093 in complex computing environments.