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# This CITATION.cff file was generated with cffinit.
# Visit https://bit.ly/cffinit to generate yours today!

cff-version: 1.2.0
title: QLStat
message: >-
  Analyze Real World Project Batch with Declarative Static
  Analysis based on CodeQL
type: software
authors:
  - given-names: Qingwei
    family-names: Li
    email: lqw332664203@ustc.edu.cn
    affiliation: University of Science and Technology of China
    orcid: 'https://orcid.org/0009-0002-3888-2435'
  - given-names: Boyao
    family-names: Ding
    email: via@mail.ustc.edu.cn
    affiliation: University of Science and Technology of China
    orcid: 'https://orcid.org/0009-0009-4208-7961'
  - orcid: 'https://orcid.org/0000-0001-6638-6442'
    affiliation: University of Science and Technology of China
    email: yuzhang@ustc.edu.cn
    given-names: Yu
    family-names: Zhang
  - orcid: 'https://orcid.org/0009-0005-7061-1178'
    given-names: Jinbao
    family-names: Chen
    email: zkd18cjb@mail.ustc.edu.cn
    affiliation: University of Science and Technology of China
identifiers:
  - type: doi
    value: 10.13328/j.cnki.jos.007464
repository-code: 'https://github.com/s4plus/QLStat'
abstract: >-
  The Go programming language (Golang), as an emerging
  programming language, achieves efficient automatic memory
  management through compile-time escape analysis and
  runtime garbage collection. It also provides built-in data
  types such as interface, slice, and map, which
  significantly enhance development efficiency and program
  performance. However, these features also introduce memory
  performance and safety challenges that differ from those
  in traditional languages like C/C++. This study uses
  static code analysis to empirically study memory
  performance and safety problems in Go programs. The
  framework PatStat, designed based on CodeQL, is employed
  to analyze open-source repositories on GitHub. This
  framework uses the declarative language QL to examine code
  patterns related to memory performance in open-source
  repositories, facilitating both manual summarization and
  automatic detection of memory safety problems. The
  research covers memory access characteristics and patterns
  of memory safety problems. An analysis of 996 Go
  open-source projects, updated within the past year,
  reveals that field accesses and dereference operations
  account for significant portions of memory access in Go
  programs, at 25.44% and 17.63%, respectively. This
  indicates the importance of field sensitivity and
  points-to analysis in Go program analysis and
  optimization. Moreover, implicit memory allocation
  resulting from Go’s unique interface type conversions is
  another key area for optimization. Through manual analysis
  of 130 Issues involving memory leaks, invalid memory
  addresses or null pointer dereferences, and dangling
  pointers, the study identifies 10 Issue patterns, noting
  that dangling pointer problems are rare in Go. These
  Issues typically require around 30 days for resolution but
  often demand only a few dozen lines of code changes. The
  findings offer insights for optimizing Go programs and
  mitigating memory safety concerns. Furthermore, a linter
  is developed to detect the Issue pattern, which involves
  the assignment of a slice expression that may lead to
  memory leaks. This tool identifies 6 Issues in real-world
  projects, one of which receives positive feedback.
keywords:
  - Go
  - memory performance
  - static code analysis
  - memory safety
  - empirical study
license: Apache-2.0