距离5月25日的软考还有2天时间,考试前的状态尤为重要。上午题虽然很零散,但是很简单,下午题虽然就5道,但是做题时需要认真、认真再认真,答案题中找,好好读题,说不定算法都能懵对几分…… 做题的时候,要从精神上藐视它,告诉自己这题会做;要从心里重
距离5月25日的软考还有2天时间,考试前的状态尤为重要。上午题虽然很零散,但是很简单,下午题虽然就5道,但是做题时需要认真、认真再认真,答案题中找,好好读题,说不定算法都能懵对几分……
做题的时候,要从精神上藐视它,告诉自己这题会做;要从心里重视它,读题时认真、耐心……
一、DFD(数据流图)
1.从最近几年考试的情况来看,这题主要考察几个知识点:
1.1 给出外部实体的名称
1.2 给出数据存储的名称
1.3 查找错误的数据流和丢失的数据流
1.4 数据字典部分的考察(2012年下半年DFD最后一问的数据项其实就是考察的数据字典)
1.5 问答题,比如2008上DFD最后一问的:面向对象结构设计方法的基本思及其适用场合。
2.做此题的技巧
这题,一般会给出一大段文字,然后给出顶层数据流图和0层数据流图等。我一般读题的过程中,会把读到的名词(可能为外部实体的词)、某某文件之类(即数据存储)、数据流标出来,这样在做问题一、二的时候,数据流图与说明对照,快速、标准的解决知识点1.1和1.2.
查找丢失数据流时,先要做的是顶层和0层图对照,保持父图和子图平衡,即父图中某加工的输入(输出)数据流的数据必须与子图的输入(输出)数据流中的数据在数量和名字上相同。在此基础上,读文字说明,一句句的注意从..到..的字眼,这样就能解决知识点1.3。
数据字典的问题,要知道数据字典各个符号的定义。
对于简答题这样的题目,就凭借项目经验来写吧,尽量多写点,总能达到点上。
具体数据流部分需要注意的考点见博客《 软考之数据流图专题》
二、数据库分析与设计
从历年考题来看,主要有两种形式:一种是文字说明+表格,一种是只有文字说明的。
1.主要考察几个知识点
1.1 补充联系及联系类型,完善实体联系图
1.2 ER图向关系模型的转变
1.3 加个功能再次补充实体联系图
1.4 简答题
2.做此题的技巧
第一遍读题的时候,画出各实体,尽量找出实体间的对应关系。对于给表格的题,表格的标题及表格周围的文字都要认真看,比如时间有可能就是某一实体的属性。
解决1.1的技巧及注意事项:注意审题,不要漏泄联系类型(1:1,1:m,m:n),难点在于一个联系联系三个实体的。读题的时候注意这样的字眼,比如:某某老师对某某学生上某某课。
解决1.2的技巧:先从说明中凭自己的感觉从文字说明及表格中找实体的属性,找完以后,再去看ER图,遵照ER图向关系模型转转换的原则。不要漏写、多些属性值,不要忘记标主键、外键。
解决1.4的技巧:按照自己的经验来,考前先弄懂1-3范式具体的含义。
三、面向对象分析与设计
从近几年考察来看,常常给出一段说明,然后附加有用例图和类图,当然也有可能会考状态图。
1.主要考察的知识点
1.1 填写用例名称、依赖关系
1.2 填写类名称
1.3 补充多重度
1.4 对应的状态
1.5 用到的某某设计模式的内涵
2. 解决此类问题的技巧
第一遍读题的过程中,注意各名词,该标的地方标出来。
用例名称一般比较好写,还要注意一点就是:依赖关系。要明白扩展《extend》和包含《include》的用意及箭头方向。
多重度问题跟数据库中的联系类型有点相似,但不要写错,这里多个的时候只能用*表示哦。注意文中给出的数字,可能帮助你解决多重度问题。
状态图各状态的转换也算是比较好找的一类问题吧,主要考察的是细心。
考察某设计模式的内涵的这类问题,要熟悉23个设计模式的含义了。设计模式很重要啊……
四、算法题
这类题对我来说难度不小,但也不能掉以轻心,有时候算法考的还是比较简单的,懵都能懵对几分,比如时间复杂度和空间复杂度。可以看看《大话设计模式》,这里面讲的挺明确的。但是算法不是一朝一夕就能提高的,考试之前把几种常见算法看懂就好了,比如各类排序算法、分治算法、动态规划算法、贪心算法、回溯算法……
五、设计模式
这个题算是比较简单的,我选择做java版的设计模式,这个题有点java基础,能看懂类图,即使不懂设计模式也能得分。高中时老师常教育我们这么一句话:简单全做对,稳坐中档题,舍弃全不会;主要表达的是考试要心态正,乱中求稳,不要第一题做的不好,后面的都做不好了。
考试之前将HeadFirst好好瞅瞅,历年考题出的例子大多与HeadFirst上的例子极为相似。
一定要知道的几点:比如 interface、extends、implements、abstract、super等关键字的写法,注意大小写;注意委托的用法……
保持好心态,乱中求稳,稳中求胜!相信自己,应该没问题的!只能说该做的都做了,大不了重来,一定把它突破!

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Usingtemporary indicates that the need to create temporary tables in MySQL queries, which are commonly found in ORDERBY using DISTINCT, GROUPBY, or non-indexed columns. You can avoid the occurrence of indexes and rewrite queries and improve query performance. Specifically, when Usingtemporary appears in EXPLAIN output, it means that MySQL needs to create temporary tables to handle queries. This usually occurs when: 1) deduplication or grouping when using DISTINCT or GROUPBY; 2) sort when ORDERBY contains non-index columns; 3) use complex subquery or join operations. Optimization methods include: 1) ORDERBY and GROUPB

MySQL/InnoDB supports four transaction isolation levels: ReadUncommitted, ReadCommitted, RepeatableRead and Serializable. 1.ReadUncommitted allows reading of uncommitted data, which may cause dirty reading. 2. ReadCommitted avoids dirty reading, but non-repeatable reading may occur. 3.RepeatableRead is the default level, avoiding dirty reading and non-repeatable reading, but phantom reading may occur. 4. Serializable avoids all concurrency problems but reduces concurrency. Choosing the appropriate isolation level requires balancing data consistency and performance requirements.

MySQL is suitable for web applications and content management systems and is popular for its open source, high performance and ease of use. 1) Compared with PostgreSQL, MySQL performs better in simple queries and high concurrent read operations. 2) Compared with Oracle, MySQL is more popular among small and medium-sized enterprises because of its open source and low cost. 3) Compared with Microsoft SQL Server, MySQL is more suitable for cross-platform applications. 4) Unlike MongoDB, MySQL is more suitable for structured data and transaction processing.

MySQL index cardinality has a significant impact on query performance: 1. High cardinality index can more effectively narrow the data range and improve query efficiency; 2. Low cardinality index may lead to full table scanning and reduce query performance; 3. In joint index, high cardinality sequences should be placed in front to optimize query.

The MySQL learning path includes basic knowledge, core concepts, usage examples, and optimization techniques. 1) Understand basic concepts such as tables, rows, columns, and SQL queries. 2) Learn the definition, working principles and advantages of MySQL. 3) Master basic CRUD operations and advanced usage, such as indexes and stored procedures. 4) Familiar with common error debugging and performance optimization suggestions, such as rational use of indexes and optimization queries. Through these steps, you will have a full grasp of the use and optimization of MySQL.

MySQL's real-world applications include basic database design and complex query optimization. 1) Basic usage: used to store and manage user data, such as inserting, querying, updating and deleting user information. 2) Advanced usage: Handle complex business logic, such as order and inventory management of e-commerce platforms. 3) Performance optimization: Improve performance by rationally using indexes, partition tables and query caches.


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