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The large number of alarms reported by static analysis tools is often recognized as one of the major obstacles to industrial adoption of such tools. We present repositioning of alarms, a novel automatic postprocessing technique intended to reduce the number of reported alarms without affecting the errors uncovered by them. The reduction in the number of alarms is achieved by moving groups of related alarms along the control flow to a program point where they can be replaced by a single alarm. In the repositioning technique, as the locations of repositioned alarms are different than locations of the errors uncovered by them, we also maintain traceability links between a repositioned alarm and its corresponding original alarm(s). The presented technique is tool-agnostic and orthogonal to many other techniques available for postprocessing alarms. To evaluate the technique, we applied it as a postprocessing step to alarms generated for 4 verification properties on 16 open source and 4 industry applications. The results indicate that the alarms repositioning technique reduces the alarms count by up to 20% over the state-of-the-art alarms grouping techniques with a median reduction of 7.25%.

Bug detection using static analysis has been found useful in practice for ensuring software quality and reliability. However, it often requires sifting through a large number of warnings. This can be handled by generating an assertion corresponding to each warning and verifying the assertion using a model checker to classify the warning as an error or a false positive. Since model checking over larger code fragments is non-scalable and expensive, it is useful to model check a given assertion with a small calling context length. For this, the variables receiving values from outside the context are initialized with arbitrary values generated by non-deterministic choice functions. The calling context length is then gradually increased on a need basis to include callers higher up in the call chains. While this aids scalability by keeping the calling context as small as possible, it requires multiple calls to model checker for the same assertion, requiring a considerable amount of time.We present a static analysis to expedite false positive elimination. It is based on the following observation: When the variables involved in an assertion are allowed to take arbitrary values at the point of assertion, the assertion is most likely to be violated by some or the other combination of values. In such cases, usage of a model checker is redundant as it does not aid in resolution of the corresponding warning. Our data flow analysis identifies (an over-approximated set of) such variables using a novel lattice so that model checking of assertions involving such variables can be avoided. Our empirical evaluation demonstrates that, on an average, the proposed static analysis avoids 49.49% of the total model checking calls, and it reduces the false positives elimination time by 39.28%. However, this gain is achieved at the cost of missing 2.78% false positives which could have been eliminated otherwise.

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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. 1 Broadly, two alarms are said to be similar if the property/condition checked in one alarm implies the property/condition checked in the other alarm (Section 2). 2 A control dependency of a program point p is a conditional edge in the control flow graph [1], that decides whether p is to be reached or not (see Section 2). 1 void HoleHMEPBCs (void){ 2 int h2d [309]; 3 4 ...

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