Heap Reference Analysis Using Access Graphs

Despite significant progress in the theory and practice of program analysis, analysing properties of heap data has not reached the same level of maturity as the analysis of static and stack data. The spatial and temporal structure of stack and static data is well understood while that of heap data seems arbitrary and is unbounded. We devise bounded representations which summarize properties of the heap data. This summarization is based on the structure of the program which manipulates the heap. The resulting summary representations are certain kinds of graphs called access graphs. The boundedness of these representations and the monotonicity of the operations to manipulate them make it possible to compute them through data flow analysis. An important application which benefits from heap reference analysis is garbage collection, where currently liveness is conservatively approximated by reachability from program variables. As a consequence, current garbage collectors leave a lot of garbage uncollected, a fact which has been confirmed by several empirical studies. We propose the first ever end-to-end static analysis to distinguish live objects from reachable objects. We use this information to make dead objects unreachable by modifying the program. This application is interesting because it requires discovering data flow information representing complex semantics. In particular, we discover four properties of heap data: liveness, aliasing, availability, and anticipability. Together, they cover all combinations of directions of analysis (i.e. forward and backward) and confluence of information (i.e. union and intersection). Our analysis can also be used for plugging memory leaks in C/C++ languages.Comment: Accepted for printing by ACM TOPLAS. This version incorporates referees' comment

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of B.E Computer Engineering class have submitted their project write-up on Node Listing Based Global Data Flow Analysis. This is a result of their own efforts in collecting information from various sources, assimilating it, deriving new information from experimentation and reasoning and presenting it in this format. We certify that they have completed the project work to our satisfaction

Reducing static analysis alarms based on non-impacting control dependencies

Static analysis tools help to detect programming errors but generate a large number of alarms. Repositioning of alarms is recently proposed technique to reduce the number of alarms by replacing a group of similar alarms with a small number of newly created representative alarms. However, the technique fails to replace a group of similar alarms with a fewer representative alarms mainly when the immediately enclosing conditional statements of the alarms are different and not nested. This limitation is due to conservative assumption that a conditional statement of an alarm may prevent the alarm from being an error. To address the limitation above, we introduce the notion of non-impacting control dependencies (NCDs). An NCD of an alarm is a transitive control dependency of the alarm’s program point, that does not affect whether the alarm is an error. We approximate the computation of NCDs based on the alarms that are similar, and then reposition the similar alarms by considering the effect of their NCDs. The NCD-based repositioning allows to merge more similar alarms together and represent them by a small number of representative alarms than the state-of-the-art repositioning technique. Thus, it can be expected to further reduce the number of alarms. To measure the reduction obtained, we evaluate the NCD-based repositioning using total 105,546 alarms generated on 16 open source C applications, 11 industry C applications, and 5 industry COBOL applications. The evaluation results indicate that, compared to the state-of-the-art repositioning technique, the NCD-based repositioning reduces the number of alarms respectively by up to 23.57%, 29.77%, and 36.09%. The median reductions are 9.02%, 17.18%, and 28.61%, respectively

Disjunctive Relational Abstract Interpretation for Interprocedural Program Analysis

International audienceProgram analysis by abstract interpretation using relational abstract domains—like polyhedra or octagons—easily extends from state analysis (construction of reachable states) to relational analysis (construction of input-output relations). In this paper, we exploit this extension to enable interprocedural program analysis, by constructing relational summaries of procedures. In order to improve the accuracy of procedure summaries, we propose a method to refine them into disjunctions of relations, these disjunctions being directed by preconditions on input parameters