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– Джабба сплюнул. – От взрывной волны я чуть не упал со стула. Где Стратмор. – Коммандер Стратмор погиб. – Справедливость восторжествовала, как в дешевой пьесе.
Microsoft word 2010 w pakiecie microsoft office 2010 2mb free download
Reference density is replaces the data that have been used least. For each data a reference frequency for a given reference interval. The first variant uses a data unit is accessed . The disadvantage of this reference interval which corresponds to the age of a approach is that the data units in the cache that have been page.
The second variant uses constant interval time . When the cache is used in the future at all. The LRU-K 2. It then replaces the policies result in hybrid algorithms. These algorithms data unit with the least recent penultimate reference .
The cache hit ratio. ARC algorithm dynamically balances recency and 2Q replacement policy uses two queues. The first frequency. It uses two LRU-queues. These queues queue uses the FIFO replacement policy for data units maintain the entries of recently evicted data units .
The second queue uses LRU as a replacement well across varied workloads , . ARC requires policy, and serves for so-called hot data units.
Hot data units with the same size; thus it is not suitable for units are units that have been accessed more than once. If caching whole files.
It FIFO-queue. When the same data unit is accessed for the was developed for caching data blocks during reading second time, it is moved to the LRU-queue. The 2Q data blocks from the hard disk. When hit ratio over LRU . The data units with a . CRASH works with data blocks with the same size; lower hit count are stored in a lower priority queue. If the thus CRASH is not suitable for caching blocks with number of the hit count reaches the threshold value, the different sizes.
When a replacement is needed, the data units from the queue with the lowest priority are replaced . FBR divides the cache into three segments: a new segment, a middle segment, and the old All caching algorithms mentioned were designed mainly segment. These algorithms usually their recency of usage.
When a hit occurs, the hit counter work with data blocks that have the same size. When is increased only for data units in the middle and old replacement occurs, all the statistics-based and hybrid segments.
When a replacement is needed, the policy caching policies mentioned choose the block to be chooses the data unit from the old segment with the removed from the cache based on statistics gathered smallest hit count . Moreover, all the caching policies LIRS replacement policy uses two sets of referenced have to store statistical information for all data blocks in units: the High Inter-reference Recency HIR unit set the cache.
We propose a new caching policy suitable for use in LIRS calculates the distance between the last two mobile devices.
Our first goal is to minimize costs of accesses to a data unit and also stores a timestamp of the counting the priority of data units in the cache. This goal last access to the data unit. Based on this statistical was set because mobile device are not as powerful as information, the data are divided into either LIR or HIR personal computers ant their computational capacity is blocks. When the cache is full, the least recently used limited.
The speed of data transfer from a remote server data unit from the LIR set is replaced. LIRS is suitable to the mobile device can vary.
Thus, our second goal is to for use in virtual memory management . We present an innovated LFU algorithm we call not often read. We add 1 because the user wants to read this file. We must store the read hits value as a 3. The database module of the server maintains relates to ageing files in the cache. If the file was metadata for the files stored in the DFS.
The metadata accessed many times in the past, it still remains in the records contain items for storing statistics. These cache even if the file will not be accessed in the future statistics are number of read and number of write hits per again. When the value of variable DFS. When a user wants to write the file content, the by 2.
Both of these experimentally. LFU-SS maintains metadata of upload client statistics to server files in a heap structure. If the new Using statistics from the server for gaining better file in the cache is frequently downloaded from the results in the cache read hit ratio causes a disadvantage in server, the file is then prioritized in comparison to a file updating these statistics. If the accessed files are which is not frequently read from the server.
For provided from the cache, the statistics are updated only computing the initial read hits value, we use the on the client side, and are not sent back to the server. In following formula: this case, the server does not provide correct metadata, and the policy does not work correctly. A Similar case occurs while using a cache on the server and client sides simultaneously . To prevent this phenomenon, the client application periodically sends local statistics back We first calculate the difference between read and write to the server.
The update message contains file ids and hits from the server. We prefer the files that have been number of requests per each file since the last update.
We read many times, and have not been written so often. In our approach, we need to section. As mentioned before, we use a binary min- heap for storing metadata records.
This heap is ordered the by read hits count. For cached files in LFU-SS, we use three operations: inserting a new file into the cache, As shown in the formula, we again use linear removing a file from the cache, and updating file read interpolation for calculating PLRU. We interpolate hits. All these three operations are O logN . We need to recalculate priorities increases the cache hit ratio.
For the combination of these for all cached units every time one cached unit is caching policies, we will compute the priority of LRU requested. The priority of files because of changes in these priorities. By caching LRU and LFU-SS is from the interval 0, ], where whole files, we do not have many units in the cache, so a higher value represents a higher priority.
The file with these calculations are acceptable. The pseudo-code for the lowest priority is replaced. Using LRFU-SS causes the same problem with The least recently used policy usually stores the updating access statistics on the server side. We will timestamp for last access to the file.
If a replacement is solve this problem by periodically sending update needed, the file that has not been accessed for the longest messages back to the server. Each statistics to the server in the next section. Again, we use a binary writes requests for each file. When a client demands a min-heap for storing metadata records of cached files. We also employ three operations to the cached files: Client is an entity which requests files from the inserting a new file into the cache, removing a file from server and uses the evaluated caching algorithm.
During the cache, and accessing the file. Let N be the number of the simulation, the client receives requests for file access the cached files: from the Requests generator. The client increases the The operation inserting a file entails recalculating counter of requested bytes by the size of the file and time priorities of all cached files, which takes O N time.
If the file is New priorities do not affect the heap structure because found in the cache, the number of cache read hits is the recalculation maintains the min-heap property. After increased. If the file is not in the cache, the file is recalculating new priorities, we insert a new file into the downloaded from the server and stored in the cache.
At heap, which is O logN. Then, insertion of a new file is the same time, the counter maintaining the number of O N.
The operation removing a file is O logN again. As with inserting a new file, we need to Requests generator is an entity which knows the recalculate priorities of all files taking O N time. We used a Gaussian random generator for a and min-heapify the accessed file, which is O logN. We carried main parts: server and client applications.
The System out two types of test. The first series of tests was architecture is depicted in Figure 4. This distribution is based on analysis of the log from a Authorization local AFS cell server. We monitored the AFS cell for a month.
In this period of time, users have nearly , requests to the files. Accesses to the files are simulated by using a Gaussian random generator which corresponds to the observations gained from the log. We used the cache hit ratio and data transfer 4. The client applications exist in three main versions: the standalone 4.
These modules can be run on different machines Client and Request generator. This module is an entry point Cache Policy to the system. It ensures authorization and secure Caching 8 16 32 64 communication with clients . The communication policy channel is encrypted by using OpenSSL. The synchronization Clock 1. Several clients can access the system via several nodes.
FBR 2. Every received message gets LFU 3. The VFS module statistics hides the technology used for data and metadata storage. Based on the request, the module determines whether it LIRS 1. LRDv1 1. The File system module LRDv2 1.
It LRFU 1. The FS module starts the replication of the without 0. The replication process sending statistics cooperates with the synchronization layer. Database Module. The Database module serves for LRU 1.
The database stores LRU-K 1. The synchronization of the databases is solved at the MRU 1. It ensures the RND 1. Table 1: Cache Read Hit Ratio vs. Cache Size Using Cache Simulator. The first simulation of the caching caching policies. LFU-SS with sending local statistics back to the server has the best results in terms of the cache hit ratio. The second-best is the FBR policy. Recall that we use the 4.
Hence, the policy with the We implemented all caching policies mentioned in best read hits ratio is not necessarily the best one in Section 2 in this simulation.
We chose these the variety of file size. LFU-SS has the best result in with and without sending client statistics back to the decreasing network traffic for cache sizes from 8MB to server, to demonstrate the effect of sending client MB. The cache read hit ratio is shown in Table 1. The total size in smaller cache sizes over other caching policies. The total without size of transferred files was 22,5GB. Table 4 summarizes LRU Because of high time consumption of sending client In the simulation scenario, we sending client Table 3 summarizes the cache statistics read hit ratio for each of the implemented algorithms.
While Table 4: Data Transfer Decrease vs. In our future work, we will add direct generation of the  M. Chetty, R. Banks, A. Brush, J. Donner and R. The data on a server can be modified Texas, USA, Xiao, Y. Zhao, F. Liu and Z. Froese and R. Our goals in developing new These two goals were set because of the  L. Engineering of computer based systems, Los The comparison of caching policies proved that the Alamitos, Reed and D.
Belady, R. Nelson and G. ACM, vol. This work is supported by the Ministry of Education,  P. Steven W. Jiang, F. Chen and X. Boukerche, R. Al-Shaikh and B. Marleau, Conference, Berkeley, Mattson, J. Gecsei, D. Slutz and I. Boukerche and R. Whitehead, C. Lung, A. Tapela and G. ICPP Workshops. NCA ‘ International Conference on, Columbus, Michalakis and D.
NFS-based mobile distributed file system for  H. Chou and D. ASWN Kingston Technology Corporation, Johnson and D. Zhou, J. Philbin and K. Jiang and X. Lee, J. Choi, J. Kim, S. Noh, S. Min, Y. Cho and C. Effelsberg and T. O’Neil, P. O’Neil and G. Megiddo and D. Lee, S. Park, B. Sung and C. Cormen, C. Leiserson, R. Rivest and C. Stein, Introduction To Algorithms, 3rd ed.
University, Delhi, India E-mail: arvinder70 gmail. While on the other hand the future research should focus on bridging the large gaps that were found existing in the usage of various tools and artifacts. During the course of research, preliminary literature survey indicated that to the best of our knowledge, no systematic review has been published so far on the topic of regression test prioritization.
In , they have that need to be re-executed during regression testing. The also discussed the possibility of EBSE using an analogy test cases are executed in that order so as to catch the faults with the medical practices. EBSE is important as the at the earliest within minimum time. This is an important software intensive systems are taking central place in our activity during maintenance phase as it rebuilds confidence day to day life.
EBSE can assist practitioners to adopt the in the correctness of the modified or updated system. This appropriate technologies and to avoid the inappropriate paper presents the systematic review of regression test ones. Though a few of these techniques the current best evidence from the research can be integrated have been evaluated and compared by many researchers [1, with the practical experience and human values in the 2, 3, 4, 5, 6, 7, 8, 9 etc], a generalized conclusion has not decision making process regarding the development and been drawn by any of them.
EBSE involves five basic for the advancement of future work in the field of steps : 1 Convert the problem into an answerable Regression Test Prioritization RTP , a systematic review question, 2 search the literature for the best available was conducted to collect and compare some common evidence, 3 critically appraise the evidence for its validity, parameters of the existing techniques and their empirical impact, and applicability, 4 combining the critical appraisal evidences.
Reviews are improve them for future use. The first three steps constitute the essential tools by which a researcher can keep up with a systematic review. The systematic review is a specific the new evidences in a particular area. There is a need to research methodology that is aimed at gathering and develop formal methods for systematic reviewing of the evaluating the available evidences related to a focused topic studies.
In the last decade, the medical research field has area. They evaluate and interpret the relevant research that is successfully adopted the evidence based paradigm . In available for the particular research questions or topic area , it is suggested that Evidence Based Software . Singh et al. The systematic review should consolidate the testing and conclusion drawn was that regression testing empirical studies conducted so far in the field.
This should not be researched in isolation. Though it was not a among a few of them. It makes an attempt in displaying systematic literature review, nonetheless it reported a the amount of efforts already been put in to the field. To detailed summary of the current state of art and trends in achieve the same, 65 test case prioritization papers were the field.
The number of studies included in their study identified that reported 50 experiments, 15 case studies and is almost the same as compared to the size of selected techniques of regression test prioritization.
A qualitative papers for the current research. This is reasonable as 1 analysis of the techniques was performed by comparing their’s was not an SLR, thus inclusion of every relevant them with respect to the various measures like size of the study is not necessary; 2 the current SLR has been study, type of the study, approach, input method, tool, and conducted including the studies that were published in metrics etc. An SLR should be very selective in the 2 Related Work inclusion of a study with respect to its research questions.
Thus, some of the studies included in the survey by Yoo In a systematic review, the main research questions, the and Harman for RTP area, got excluded at the study methodological steps, and the study retrieval strategies selection stage of our SLR. Also, there are a few are explicitly defined. In , the procedures for additional studies found and included in this SLR that performing a Systematic Literature Review SLR in were published during and after the time frame for the Software Engineering were first proposed by survey in .
Nonetheless, Yoo and Harman have Kitchenham . In the report , medical guidelines summed up the various approaches used for RTP, for performing systematic reviews were adapted to the regression test minimization and selection along with the requirements of software engineering. The first artifacts that have been used by these techniques. They had not reported published in . Staples and Niazi  shared the language dependency, granularity of the technique their experiences while using the guidelines given by and the type of input to the technique.
These aspects have Kitchenham . They emphasized more on the clearer been reported and used as a basis for the comparison of and narrower choice of research questions and also on various techniques in the current research. In addition to this, they  also found that 3 Difference between Literature reliability and quality assessment was difficult based on Review and Systematic Literature the given guidelines .
A systematic review in Following the recent rise in the number of empirical software engineering  presented all the systematic studies in the field, SLR is a necessity for providing a reviews conducted during Jan Jun in the field. Systematic reviews require the topic areas covered by SLR’s in software engineering are documentation of not only the search criterions but also limited and that European researchers, especially the of the different databases that are searched.
Another systematic literature survey focused research question s to be addressed and the on regression test selection techniques was presented in method to be employed in the process; while in the . SLR and evaluated quantitatively. Traditional review and Skoglund , found that due to the dependence can be accomplished only by a single reviewer; while on over varying factors no technique was clearly superior.
The survey was conducted for 15 industry participants and the This study presents a rigorous insight to various test case outcomes were validated by 32 respondents via an prioritization techniques developed and applied in online questionnaire. According to the authors , the regression testing area. After this step, 65 studies were finalized, and were rigorously These electronic sources have been mentioned in examined to find the answers to our research questions.
There was an overlapping in the papers led to their empirical ical evaluation, comparison, appraisal resulting from these sources and thus the duplicate etc.
The steps undertaken in the Systematic literature review for prioritization techniques are 4. The initial search string was reached in order to find all the possibly bly relevant matter in the area of test case prioritization. Their SLR is in a field much similar to our topic, thus the search string was reached considering nsidering the search string used by them  and the requirements for our topic.
To make sure that all potentially relate related literature could be found, the above search string was applied on full text, rather than only on the title or the abstract. The start was set to January up till February This is created problem as the numbers of items in outlook not matching with number of items in folder. Can you please help to edit the above code so that it also paste all the items even though it has same subject? User Ammar. Replace Str, “” End Function.
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Microsoft word 2010 w pakiecie microsoft office 2010 2mb free download
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