The major challenge faced by software industry is meeting deadlines in delivering quality product. The major reason behind delays is not only development part but basically detection and finding of bug or error. Whenever a bug is reported, developers use bug reports to reach to the code fragments that need to be modified to fix the bug. Suitable semantic information is present in bug reports and developers start exhaustive searching manually to catch the bug location. To minimize this manual effort, a framework on Information retrieval based bug localization is proposed that exploits the textual content of bug report to provide the rank relevant buggy source files ie the file having higher probability of occurrence of bug. The dataset used consists of a total of 925 bugs from 4 project categories SWT, ZXing, Eclipse and AspectJ. This framework outputs the Top N, here top (related) terms top 5 ranked sequence terms, showing the file containing these terms having higher probability of occurrence of bug.