Cause Points Analysis for Effective Handling of Alarms

Muske, Tukaram; Khedker, Uday P.

doi:10.1109/issre.2016.45

Cited by 6 publications

(7 citation statements)

References 36 publications

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“…Semi-automic diagnosis [14,54,148,149,189,193] Feedback-based [114,153] Checklists [8,140] UI & navigation tools [5,21,33,70,79,138] Alarm-relevant queries [42,80,127,190] Automated repair [12,15,115,116,179] Others [6,112,119,121,133,136,144] Fig. 1.…”

Section: Overview Of the Extracted Datamentioning

confidence: 99%

Survey of Approaches for Postprocessing of Static Analysis Alarms

Muske

Serebrenik

2022

ACM Comput. Surv.

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Static analysis tools have showcased their importance and usefulness in automated detection of defects. However, the tools are known to generate a large number of alarms which are warning messages to the user. The large number of alarms and cost incurred by their manual inspection have been identified as two major reasons for underuse of the tools in practice. To address these concerns plentitude of studies propose postprocessing of alarms: processing the alarms after they are generated. These studies differ greatly in their approaches to postprocess alarms. A comprehensive overview of the postprocessing approaches is, however, missing. In this article, we review 130 primary studies that propose postprocessing of alarms. The studies are collected by combining keywords-based database search and snowballing. We categorize approaches proposed by the collected studies into six main categories: clustering, ranking, pruning, automated elimination of false positives, combination of static and dynamic analyses, and simplification of manual inspection. We provide overview of the categories and sub-categories identified for them, their merits and shortcomings, and different techniques used to implement the approaches. Furthermore, we provide (1) guidelines for selection of the postprocessing techniques by the users/designers of static analysis tools; and (2) directions that can be explored by the researchers.

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Section: Overview Of the Extracted Datamentioning

confidence: 99%

Survey of Approaches for Postprocessing of Static Analysis Alarms

Muske

Serebrenik

2022

ACM Comput. Surv.

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“…Then they use a different technique for each identified root cause to eliminate any generated alert. Authors [26] aims to reduce false alerts by reporting to the SAT user the alarm root causes to be inspected instead of the alarm itself. Also, they ask the user to answer questions related to the root causes to fix the error until no more alarm is triggered.…”

Section: B Root Causes Based Approachesmentioning

confidence: 99%

Software Security Static Analysis False Alerts Handling Approaches

Akremi¹

2021

IJACSA

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False Positive Alerts (FPA), generated by Static Analyzers Tools (SAT), reduce the effectiveness of the automatic code review, letting them be underused in practice. Researchers conduct a lot of tests to improve SAT accuracy while keeping FPA at a lower rate. They use different simulated and production datasets to validate their proposed methods. This paper surveys recent approaches dealing with FPA filtering; it compares them and discusses their usefulness. It also studies the used datasets to validate the identified methods and show their effectiveness to cover most program defects. This study focuses mainly on the security bugs covered by the datasets and handled by the existing methods.

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“…On the similar lines to alarms repositioning, Cousot et al [8] have proposed hoisting necessary preconditions for providing the preconditions required by the Design by Contract [23]. Furthermore, Muske et al [25] have proposed grouping the related/similar alarms based on similarity of modification points. In their approach [24], as the grouped alarms are inspected using values at the modification points of alarm variables, the inspection often finds spurious errors when the alarms are actually false positives solely due to their transitive control dependencies (ICDs).…”

Section: Related Workmentioning

confidence: 99%

“…In their approach [24], as the grouped alarms are inspected using values at the modification points of alarm variables, the inspection often finds spurious errors when the alarms are actually false positives solely due to their transitive control dependencies (ICDs). However, none of these techniques [8,24,25] identifies the conditional statements (control dependencies) that are non-impacting to the similar alarms.…”

Section: Related Workmentioning

confidence: 99%

Reducing Static Analysis Alarms Based on Non-impacting Control Dependencies

Muske¹,

Talluri²,

Serebrenik

2019

Programming Languages and Systems

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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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Cause Points Analysis for Effective Handling of Alarms

Cited by 6 publications

References 36 publications

Survey of Approaches for Postprocessing of Static Analysis Alarms

Survey of Approaches for Postprocessing of Static Analysis Alarms

Software Security Static Analysis False Alerts Handling Approaches

Reducing Static Analysis Alarms Based on Non-impacting Control Dependencies

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