Call graph construction for Java libraries

Reif, Michael; Eichberg, Michael; Hermann, Ben; Lerch, Johannes; Mezini, Mira

doi:10.1145/2950290.2950312

Cited by 35 publications

(17 citation statements)

References 29 publications

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“…Therefore, static analysis on those applications, such as taint analysis [16] and permission investigation [47], can employ ORTA for constructing the call graphs from those entry methods. Another example is the static analysis on Java libraries, such as dead method detection [15]. ORTA reduces the cost of analysing reachable methods from the public methods of the library similar to the process of constructing the one-to-one matched call graphs on ORTA-based separateRTS.…”

Section: Use Of Orta For Other Purposesmentioning

confidence: 99%

“…2. Although this approach has been used in existing studies where multiple entry points exist [11, 15, 16], this approach tends to overestimate which entry points are influenced by modified code. For example, assume that the coloured node in Fig.…”

Section: Proposed Approachmentioning

confidence: 99%

“…We used the term ‘one‐to‐one’ to indicate that each call graph presents the behaviour of a programme executed from an entry point (each entry point is a test case in the method‐level RTS). However, the applications of call graph construction, including RTS techniques, have constructed only one call graph with multiple entry points [11, 15, 16]. Such unmatched call graphs cannot recognise which test cases cause each method invocation.…”

Section: Introductionmentioning

confidence: 99%

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Overlap‐aware rapid type analysis for constructing one‐to‐one matched call graphs in regression test selection

et al. 2020

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Regression testing is an important but costly activity for verifying a programme with the changed code. Regression test selection (RTS) aims to reduce this cost by selecting only the test cases affected by the changes. Among the several ways of selecting such affected test cases, call graphs have been statically constructed to select the test cases at the method-level granularity. However, RTS techniques will reduce the cost of regression testing less than expected unless the call graphs are efficiently one-to-one matched with the test cases. In this study, the authors propose overlap-aware rapid type analysis (ORTA). ORTA is designed to minimise the redundant cost of creating the matched call graphs using rapid type analysis (RTA). The oneto-one matching and ORTA were evaluated on 1487 commits selected from 30 Java projects. RTA-based RTS with the one-toone matching selected 46.90% fewer test cases with 2.76% longer end-to-end time of regression testing than without the oneto-one matching. The time increased with the one-to-one matching was reduced by 22.58% when ORTA substituted for RTA. ORTA achieved the cost reduction while removing 82.77% of the duplicate edges that RTA created on 993 commits.

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Section: Use Of Orta For Other Purposesmentioning

confidence: 99%

Section: Proposed Approachmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Overlap‐aware rapid type analysis for constructing one‐to‐one matched call graphs in regression test selection

et al. 2020

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“…It has been shown that associating a distinct set of types with each method in a class has a significantly greater impact on precision than using a distinct set for each field in a class. Reif et al [14] study the construction of call graphs for Java libraries that abstract over all potential library usages, in a so-called open world approach. They invented two concrete call graph algorithms for libraries based on adaptations of the CHA algorithm, to be used for software quality and security issues.…”

Section: Related Workmentioning

confidence: 99%

A Relational Static Semantics for Call Graph Construction

Zhuo

Zhang

2019

Formal Methods and Software Engineering

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The problem of resolving virtual method and interface calls in object-oriented languages has been a long standing challenge to the program analysis community. The complexities are due to various reasons, such as increased levels of class inheritance and polymorphism in large programs. In this paper, we propose a new approach called type flow analysis that represent propagation of type information between program variables by a group of relations without the help of a heap abstraction. We prove that regarding the precision on reachability of class information to a variable, our method produces results equivalent to that one can derive from a points-to analysis. Moreover, in practice, our method consumes lower time and space usage, as supported by the experimental results.

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“…In total, our study compares 54 unique TCP technique instantiations. Research has shown that the studied dimensions affect TCP effectiveness and coverage precision (Rothermel et al 2001;Elbaum et al 2002;Hao et al 2014;Henard et al 2016;Luo et al 2016;Luo et al 2019;Reif et al 2016;Reif et al 2019).…”

Section: Introductionmentioning

confidence: 99%

Applying test case prioritization to software microbenchmarks

2021

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Regression testing comprises techniques which are applied during software evolution to uncover faults effectively and efficiently. While regression testing is widely studied for functional tests, performance regression testing, e.g., with software microbenchmarks, is hardly investigated. Applying test case prioritization (TCP), a regression testing technique, to software microbenchmarks may help capturing large performance regressions sooner upon new versions. This may especially be beneficial for microbenchmark suites, because they take considerably longer to execute than unit test suites. However, it is unclear whether traditional unit testing TCP techniques work equally well for software microbenchmarks. In this paper, we empirically study coverage-based TCP techniques, employing total and additional greedy strategies, applied to software microbenchmarks along multiple parameterization dimensions, leading to 54 unique technique instantiations. We find that TCP techniques have a mean APFD-P (average percentage of fault-detection on performance) effectiveness between 0.54 and 0.71 and are able to capture the three largest performance changes after executing 29% to 66% of the whole microbenchmark suite. Our efficiency analysis reveals that the runtime overhead of TCP varies considerably depending on the exact parameterization. The most effective technique has an overhead of 11% of the total microbenchmark suite execution time, making TCP a viable option for performance regression testing. The results demonstrate that the total strategy is superior to the additional strategy. Finally, dynamic-coverage techniques should be favored over static-coverage techniques due to their acceptable analysis overhead; however, in settings where the time for prioritzation is limited, static-coverage techniques provide an attractive alternative.

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Call graph construction for Java libraries

Cited by 35 publications

References 29 publications

Overlap‐aware rapid type analysis for constructing one‐to‐one matched call graphs in regression test selection

Overlap‐aware rapid type analysis for constructing one‐to‐one matched call graphs in regression test selection

A Relational Static Semantics for Call Graph Construction

Applying test case prioritization to software microbenchmarks

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