Abstract: This disclosure relates generally to the field of source code processing, and, more particularly to a method and system for identification of redundant function-level slicing calls. The method disclosed generates program dependence graphs (PDGs) based on a slicing criteria and a function corresponding to the function-level slicing call. Further the method classifies the function-level slicing call into redundant or non-redundant by traversing the PDGs and checking if a predefined condition is satisfied or not. The function-level slicing calls are classified as redundant if the check is not satisfied and are classified as non-redundant if the check is satisfied. The disclosed method can be used in identifying redundant function-level slicing calls in applications such as automated false positive elimination (AFPE), automated test case generation and so on.

Abstract: This disclosure relates generally to field of elimination of false positives during static analysis of an application code, and, more particularly, to a method and a system for identification and elimination of false positives from delta alarms. Existing static analysis tools report/generate numerous static alarms for a version and the same static alarm also gets reported for the subsequent versions, which are referred to as repeated alarms, while static alarms remaining after the suppression of the repeated alarms, are called delta alarms. In an embodiment, the disclosed method and system for identification and elimination of false positives from delta alarms, wherein the delta alarms are post-processed to identify of a set of false positives using a version aware static analysis technique based on a set of reuse computation techniques implementing conservative or an aggressive approach based on a dynamic configuration input.

Abstract: This disclosure relates generally to the field of source code processing, and, more particularly to a method and system for identification of redundant function-level slicing calls. The method disclosed generates program dependence graphs (PDGs) based on a slicing criteria and a function corresponding to the function-level slicing call. Further the method classifies the function-level slicing call into redundant or non-redundant by traversing the PDGs and checking if a predefined condition is satisfied or not. The function-level slicing calls are classified as redundant if the check is not satisfied and are classified as non-redundant if the check is satisfied. The disclosed method can be used in identifying redundant function-level slicing calls in applications such as automated false positive elimination (AFPE), automated test case generation and so on.

Abstract: This disclosure relates generally to field of elimination of false positives during static analysis of an application code, and, more particularly, to a method and a system for identification and elimination of false positives from delta alarms. Existing static analysis tools report/generate numerous static alarms for a version and the same static alarm also gets reported for the subsequent versions, which are referred to as repeated alarms, while static alarms remaining after the suppression of the repeated alarms, are called delta alarms. In an embodiment, the disclosed method and system for identification and elimination of false positives from delta alarms, wherein the delta alarms are post-processed to identify of a set of false positives using a version aware static analysis technique based on a set of reuse computation techniques implementing conservative or an aggressive approach based on a dynamic configuration input.

Abstract: Source code of any application may be edited/modified to accommodate new changes. The changes in the source code may also affect static analysis alarms that were generated for the original source code. Changes in the source code may result in newly generated alarms, some of the alarms in the original source code may repeat in the new source code. Many of the repeated alarms get suppressed using appropriate techniques. The repeated alarms that remain after the suppression, and the newly generated alarms together form the delta alarms. Each of the delta alarms may have been generated due to different reasons. Classification of the delta alarms is performed based on reasons/causes for their generation. The system further performs ranking of the classes of the delta alarms and thus ranking of the delta alarms. Further, the system groups the alarms having common cause and reports the delta alarms with their causes.

Abstract: This disclosure relates generally to static analysis of the program code, and more specifically to method and system for non-impacting control dependencies (NCDs)-based repositioning of static analysis alarms in a program code. By determining each of the transitive control dependencies (controlling conditions) of each of the original alarms either as NCD or an impacting control dependency (ICD) of the corresponding alarm, the system is able to reposition and group similar alarms even if the alarms are associated with or are under different conditional statements by considering the effect of the NCDs and ICDs of the alarms, and the repositioning further reduces number of the alarms.