
Registered user since Mon 21 May 2018
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Registered user since Mon 21 May 2018
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Research Papers
Wed 12 Oct 2022 11:40 - 12:00 at Banquet B - Technical Session 12 - Builds and Versions Chair(s): Yi LiDespite the benefits, continuous integration (CI) can incur high costs. One of the well-recognized costs is long build time, which greatly affects the speed of software development and increases the cost in computational resources. While there exist configuration options in the CI infrastructure to accelerate builds, the CI infrastructure is often not optimally configured, leading to CI configuration smells. Attempts have been made to detect or repair CI configuration smells. However, none of them is specifically designed to improve build performance in CI.
In this paper, we first create a catalog of 20 performance-related CI configuration smells (PCSs) in three tools (i.e., Travis CI, Maven and Gradle) of the CI infrastructure for Java projects. Then, we propose an automated approach, named BuildSonic, to detect and repair 15 types of PCSs by analyzing configuration files. We have conducted large-scale experiments to evaluate BuildSonic. We detected 20,318 PCSs in 99.0% of the 4,140 Java projects, with a precision of 0.998 and a recall of 0.991. We submitted 1,138 pull requests for sampled PCSs of each PCS type, 246 and 11 of which have been respectively merged and accepted by developers. We successfully triggered CI builds before and after merging 288 pull requests, and observed an average build performance improvement of 12.4% after repairing a PCS.
Research Papers
Wed 12 Oct 2022 10:20 - 10:40 at Banquet B - Technical Session 12 - Builds and Versions Chair(s): Yi LiTo enhance the compatibility in the version control of Java Third-party Libraries (TPLs), Maven adopts Semantic Versioning (SemVer) to standardize the underlying meaning of versions, but users could still confront abnormal execution and crash after upgrades even if compilation and linkage succeed. It is caused by semantic breaking (SemB) issues, such that APIs directly used by users have identical signatures but inconsistent semantics across upgrades. To strengthen compliance with SemVer rules, developers and users should be alerted of such issues. Unfortunately, it is challenging to detect them statically, because semantic changes in the internal methods of APIs are hard to be captured. Dynamic testing can confirmingly uncover some, but it is limited by inadequate coverage.
To detect SemB issues over compatible upgrades (Patch and Minor) by SemVer rules, we conducted an empirical study on 180 SemB issues to understand the root causes, inspired by which, we propose Sembid (Semantic Breaking Issue Detector) to statically detect such issues of TPLs for developers and users. Since APIs are directly used by users, Sembid detects and reports SemB issues based on APIs. For a pair of APIs, Sembid walks through the call chains originating from the API to locate breaking changes by measuring semantic diff. Then, Sembid checks if the breaking changes can affect API’s output along call chains. The evaluation showed Sembid achieved 90.26% recall and 81.29% precision and outperformed other API checkers on SemB API detection. We also revealed Sembid detected over 3 times more SemB APIs with better coverage than unit tests, the commonly used solution. Furthermore, we carried out an empirical study on 1, 629, 589 APIs from 546 version pairs of top Java libraries and found there were 2-4 times more SemB APIs than those with signature-based issues. Due to various version release strategies, 33.83% of Patch version pairs and 64.42% of Minor version pairs had at least one API affected by any breaking.