Introduction Due to the excessive developmentin software industry large number ofdatabases are produces on daily basis. So, the Software Engineering become complexday by day because the SE rising on huge scale, in this regard it becomedifficult for developers how to gain worthy information.SE deals with thedevelopment of computer bases systems, their deployment, maintenance,specification and architectural design.
Software repositories continuallyproduced. These repositories need to be managed.SE facing different challenges inwhich include gathering of requirements , integration of system and development, maintenance , pattern’s discovery, detection of error , reliability and complexity of software development. InSE there are three types of data. (1) Sequence (2) Graph (3) Text. Data mining is the computing process of discovering patterns inlarge datasets involving methods at theintersection of machine learning, statistics, and database systems.
It is an essential process where intelligent methods areapplied to extract data patterns 2. Due to data mining technique valuabledata can be obtained from large numberof dataset. Data mining help the software engineers to find out thecauses of software failure , errors of software , interaction between differentclasses and their relationships , it also help to identify the patterns used inprogram source code.
The data mining result used by the researchers or practitioners to findout the problems in current system and help to produce highly qualitative productin manageable budget and time period. Data mining techniques are helpful for solving problems inthree categories of data in SE.Data mining process consists of seven steps : data integration , data cleaning , data selection ,data transformation , data mining pattern evaluation and knowledge presentation 3 .These techniques canbe applied to improve SE related generalization , characterization, classification , clustering associative tree , decision or rule induction ,frequent pattern mining etc. 4 There are different mining techniques available that can be appliedon different types of data.
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The mining techniques are classified as: Classification,Clustering, Associatedattributes Figure 1: Data Mining Process Theobjective of this review is to understand the concept of Data mining use insoftware engineering and applications of techniques on different types of dataavailable in SE.