Programs written in a high-level language such as C and Java, interleaved with declarative database processing and inter-service communication statements are common in Enterprise Information Systems (EIS). IT companies that offer re-engineering services for such EIS rely on manual analysis or code analysis tools to understand the flow of control and data within and across the programs during the reverse-engineering phase. Generally, the code analyzers are developed for commonly used programming languages, and lack support for analyzing database processing and inter-service communication statements. Therefore, such analysis tools cannot be readily re-used for re-engineering projects. In this paper, we share the key challenges of handling program analysis requirements for large embedded Structured Query Language (SQL) applications written in C language. We describe our approach to transform a program written in C and embedded SQL into a plain C program which can be automatically analyzed using any available C code analyzer that has no explicit support for domain specific extensions like SQL. We deployed the data dependency analysis based on our transformation approach as a feature in an industrial code analysis tool. We present the evaluation and results that show a precision improvement for slices as compared to the naïve translation provided by the standard pre-compiler.

An enterprise system operates business by providing various services that are guided by set of certain business rules (BR) and constraints. These BR are usually written using plain Natural Language in operating procedures, terms and conditions, and other documents or in source code of legacy enterprise systems. For implementing the BR in a software system, expressing them as UML use-case specifications, or preparing for Merger & Acquisition (M&A) activity, analysts manually interpret the documents or try to identify constraints from the source code, leading to potential discrepancies and ambiguities. These issues in the software system can be resolved only after testing, which is a very tedious and expensive activity. To minimize such errors and efforts, we propose BuRRiTo framework consisting of automatic extraction of BR by mining documents and source code, ability to clean them of various anomalies like inconsistency, redundancies, conflicts, etc. and able to analyze the functional gaps present and performing semantic querying and searching.