ICSE 2019 109 papers accepted. Updated on 2023-09-08. You can find the lastest information here. Learning to spot and refactor inconsistent method names. Harnessing evolution for multi-hunk program repair. On learning meaningful code changes via neural machine translation. Natural software revisited. Towards automating precision studies of clone detectors. Leopard: identifying vulnerable code for vulnerability assessment through program metrics. Smoke: scalable path-sensitive memory leak detection for millions of lines of code. Reasonably-most-general clients for JavaScript library analysis. Resource-aware program analysis via online abstraction coarsening. Automated reporting of anti-patterns and decay in continuous integration. A system identification based Oracle for control-CPS software fault localization. ReCDroid: automatically reproducing Android application crashes from bug reports. Mining historical test logs to predict bugs and localize faults in the test logs. Dlfinder: characterizing and detecting duplicate logging code smells. The seven sins: security smells in infrastructure as code scripts. DifFuzz: differential fuzzing for side-channel analysis. Automatically generating precise Oracles from structured natural language specifications. The product backlog. Easy modelling and verification of unpredictable and preemptive interrupt-driven systems. Towards understanding and reasoning about Android interoperations. Zero-overhead path prediction with progressive symbolic execution. Mimic: UI compatibility testing system for Android apps. IconIntent: automatic identification of sensitive UI widgets based on icon classification for Android apps. Practical GUI testing of Android applications via model abstraction and refinement. AutoTap: synthesizing and repairing trigger-action programs using LTL properties. Active inductive logic programming for code search. NL2Type: inferring JavaScript function types from natural language information. Analyzing and supporting adaptation of online code examples. DockerizeMe: automatic inference of environment dependencies for python code snippets. BugSwarm: mining and continuously growing a dataset of reproducible failures and fixes. ActionNet: vision-based workflow action recognition from programming screencasts. How C++ developers use immutability declarations: an empirical study. Latent patterns in activities: a field study of how developers manage context. Developer reading behavior while summarizing Java methods: size and context matters. Distilling neural representations of data structure manipulation using fMRI and fNIRS. FastLane: test minimization for rapidly deployed large-scale online services. Scalable approaches for test suite reduction. A framework for checking regression test selection tools. Supporting analysts by dynamic extraction and classification of requirements-related knowledge. Analysis and detection of information types of open source software issue discussions. Do developers discover new tools on the toilet? Tool choice matters: JavaScript quality assurance tools and usage outcomes in GitHub projects. Hunting for bugs in code coverage tools via randomized differential testing. Rotten green tests. VFix: value-flow-guided precise program repair for null pointer dereferences. On reliability of patch correctness assessment. How reliable is the crowdsourced knowledge of security implementation? Pattern-based mining of opinions in Q&A websites. Detection and repair of architectural inconsistencies in Java. Could I have a stack trace to examine the dependency conflict issue? Investigating the impact of multiple dependency structures on software defects. StoryDroid: automated generation of storyboard for Android apps. Statistical algorithmic profiling for randomized approximate programs. Safe automated refactoring for intelligent parallelization of Java 8 streams. Detecting atomicity violations for event-driven Node.js applications. Parallel refinement for multi-threaded program verification. Mining software defects: should we consider affected releases? Class imbalance evolution and verification latency in just-in-time software defect prediction. FLOSS participants' perceptions about gender and inclusiveness: a survey. Going farther together: the impact of social capital on sustained participation in open source. Investigating the effects of gender bias on GitHub. SLF: fuzzing without valid seed inputs. Superion: grammar-aware greybox fuzzing. Grey-box concolic testing on binary code. RESTler: stateful REST API fuzzing. Training binary classifiers as data structure invariants. Graph embedding based familial analysis of Android malware using unsupervised learning. A novel neural source code representation based on abstract syntax tree. A neural model for generating natural language summaries of program subroutines. The list is the process: reliable pre-integration tracking of commits on mailing lists. Graph-based mining of in-the-wild, fine-grained, semantic code change patterns. Intention-based integration of software variants. Supporting the statistical analysis of variability models. Multifaceted automated analyses for variability-intensive embedded systems. Exposing library API misuses via mutation analysis. Pivot: learning API-device correlations to facilitate Android compatibility issue detection. SafeCheck: safety enhancement of Java unsafe API. CTRAS: crowdsourced test report aggregation and summarization. iSENSE: completion-aware crowdtesting management. How practitioners perceive coding proficiency. Socio-technical work-rate increase associates with changes in work patterns in online projects. Why do episodic volunteers stay in FLOSS communities? When code completion fails: a case study on real-world completions. Interactive production performance feedback in the IDE. Redundant loads: a software inefficiency indicator. View-centric performance optimization for database-backed web applications. Adjust: runtime mitigation of resource abusing third-party online ads. Symbolic repairs for GR(1) specifications. CRADLE: cross-backend validation to detect and localize bugs in deep learning libraries. Guiding deep learning system testing using surprise adequacy. FOCUS: a recommender system for mining API function calls and usage patterns. Test-driven code review: an empirical study. Why does code review work for open source software communities? Distance-based sampling of software configuration spaces. DeepPerf: performance prediction for configurable software with deep sparse neural network. GreenBundle: an empirical study on the energy impact of bundled processing. Search-based energy testing of Android. Global optimization of numerical programs via prioritized stochastic algebraic transformations. Type migration in ultra-large-scale codebases. Dynamic slicing for Android. Recovering variable names for minified code with usage contexts. Gigahorse: thorough, declarative decompilation of smart contracts. Probabilistic disassembly. Software documentation issues unveiled. 9.6 million links in source code comments: purpose, evolution, and decay. Leveraging artifact trees to evolve and reuse safety cases. Detecting incorrect build rules. Adversarial sample detection for deep neural network through model mutation testing. Deep differential testing of JVM implementations.