Exception handling bug hazards in Android

Coelho, Roberta; Almeida, Lucas; Gousios, Georgios; Deursen, Arie van

doi:10.1007/s10664-016-9443-7

Cited by 38 publications

(14 citation statements)

References 47 publications

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“…The characteristics of the selected bugs, including type of exception and priority, are summarized in Table 2. These bugs cover crashes that involve the most common Java Exceptions [24], such as NullPointerException (74%), ArrayIndex-OutOfBoundsException (9%), IllegalStateException and IllegalArgumentException (3%). Furthermore, the severity of these real-world bugs varies between medium (46%), major (37%) and critical (5%) as judged by the original developers.…”

Section: Definition and Contextmentioning

confidence: 99%

Search-Based Crash Reproduction and Its Impact on Debugging

Soltani

Panichella

Deursen

2020

IIEEE Trans. Software Eng.

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Software systems fail. These failures are often reported to issue tracking systems, where they are prioritized and assigned to responsible developers to be investigated. When developers debug software, they need to reproduce the reported failure in order to verify whether their fix actually prevents the failure from happening again. Since manually reproducing each failure could be a complex task, several automated techniques have been proposed to tackle this problem. Despite showing advancements in this area, the proposed techniques showed various types of limitations. In this paper, we present EvoCrash, a new approach to automated crash reproduction based on a novel evolutionary algorithm, called Guided Genetic Algorithm (GGA). We report on our empirical study on using EvoCrash to reproduce 54 real-world crashes, as well as the results of a controlled experiment, involving human participants, to assess the impact of EvoCrash tests in debugging. Based on our results, EvoCrash outperforms state-of-the-art techniques in crash reproduction and uncovers failures that are undetected by classical coverage-based unit test generation tools. In addition, we observed that using EvoCrash helps developers provide fixes more often and take less time when debugging, compared to developers debugging and fixing code without using EvoCrash tests.

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Section: Definition and Contextmentioning

confidence: 99%

Search-Based Crash Reproduction and Its Impact on Debugging

Soltani

Panichella

Deursen

2020

IIEEE Trans. Software Eng.

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“…The developers' perception was assessed through online questionnaires [34,[36][37][38] and semi-structured interviews [5,40]. In general, the researches aimed at understanding how developers use the exception handling, what approaches are used, the differences between novices and experienced developers, what they understand about exception handling bugs and how they use exception handling in Android and Swift applications.…”

Section: Discussionmentioning

confidence: 99%

“…Finally, the authors in [37] investigated when reported stack traces may express circumstances in which there are a greater likelihood of bugs in exception handling in Android applications. Among the findings, they highlight that the majority cause of the stack trace problems were related to programming bugs (e.g., NullPointerException, IllegalArgumentException, RuntimeException), 65% of application failures were related to runtime exceptions, and only one was documented with the tag @throws.…”

Section: Hybrid Studiesmentioning

confidence: 99%

Studying the evolution of exception handling anti-patterns in a long-lived large-scale project

et al. 2020

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Exception handling is a well-known technique used to improve software robustness. However, recent studies report that developers typically neglect exception handling (mostly novice ones). We believe the quality of exception handling code in a software project is directly affected (i) by the absence, or lack of awareness, of an explicit exception handling policy and guidelines and (ii) by a silent rising of exception handling anti-patterns. In this paper, we investigate this phenomenon in a case study of a long-lived large-scale Java Web system in a Public Education Institution, trying to better understand the relationship between (i) and (ii), and the impact of developers' turnover, skills, and guidance in (ii). Our case study takes into account the technical and human aspects. As a first step, we surveyed 21 developers regarding their perception of exception handling in the system's institution. Next, we analysed the evolution of exception handling anti-patterns across 15 releases of the target system. We conducted a semi-structured interview with three senior software engineers, representatives of the development team, to present partial results of the case and raise possible causes for the found problems. The interviewed professionals and a second analysis of the code identified the high team turnover as the source of this phenomenon, since the public procurement process for hiring new developers has mostly attracted novice ones. These findings suggest that the absence of an explicit exception handling policy impacts negatively in the developers' perception and implementation of exception handling. Furthermore, the absence of such policy has been leading developers to replicate existing anti-patterns and spread them through new features added during system evolution. We also observed that most developers have low skills regarding exception handling in general and low knowledge regarding the design and implementation of exception handling in the system. The system maintainer now has a diagnosis of the major causes of the quality problems in the exception handling code and was able to lead the required measures to repair this technical debt.

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“…Those stack traces are commonly reported by users to issue tracking systems but cannot (for now) be completely reproduced by EvoCrash. Further investigation on current error handling practices in Java code (Cabral and Marques 2007;Coelho et al 2017) and how they are reported by users (Maiga et al 2015) will help us to devise efficient approaches to replicate such stack traces.…”

Section: Stack Trace Preprocessing and Target Frame Selectionmentioning

confidence: 99%

A benchmark-based evaluation of search-based crash reproduction

et al. 2019

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Crash reproduction approaches help developers during debugging by generating a test case that reproduces a given crash. Several solutions have been proposed to automate this task. However, the proposed solutions have been evaluated on a limited number of projects, making comparison difficult. In this paper, we enhance this line of research by proposing JCrashPack, an extensible benchmark for Java crash reproduction, together with ExRunner, a tool to simply and systematically run evaluations. JCrashPack contains 200 stack traces from various Java projects, including industrial open source ones, on which we run an extensive evaluation of EvoCrash, the state-of-the-art tool for search-based crash reproduction. EvoCrash successfully reproduced 43% of the crashes. Furthermore, we observed that reproducing NullPointerException, IllegalArgumentException, and IllegalStateException is relatively easier than reproducing ClassCastException, ArrayIndexOutOfBoundsException and StringIndexOutOfBoundsException. Our results include a detailed manual analysis of EvoCrash outputs, from which we derive 14 current challenges for crash reproduction, among which the generation of input data and the handling of abstract and anonymous classes are the most frequents. Finally, based on those challenges, we discuss future research directions for search-based crash reproduction for Java.

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Exception handling bug hazards in Android

Cited by 38 publications

References 47 publications

Search-Based Crash Reproduction and Its Impact on Debugging

Search-Based Crash Reproduction and Its Impact on Debugging

Studying the evolution of exception handling anti-patterns in a long-lived large-scale project

A benchmark-based evaluation of search-based crash reproduction

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