Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

Stability of structures

Stability of structures

In mechanical engineering, the stability of systems under various forces is critical for designing durable and efficient structures. One fundamental way to explore these concepts is by analyzing systems like two rods connected at a pivot point, O, with a torsional spring of spring constant k at the pivot point. This system is similar in appearance to a scissor jack used to change tires on a car. In this case, the arms of the linkage (equivalent to the rods in this system) are entirely vertical,...

Periodic Classification of the Elements

Periodic Classification of the Elements

The periodic table arranges atoms based on increasing atomic number so that elements with the same chemical properties recur periodically. When their electron configurations are added to the table, a periodic recurrence of similar electron configurations in the outer shells of these elements is observed. Because they are in the outer shells of an atom, valence electrons play the most important role in chemical reactions. The outer electrons have the highest energy of the electrons in an atom...

Gene Evolution - Fast or Slow?

Gene Evolution - Fast or Slow?

The genomes of eukaryotes are punctuated by long stretches of sequence which do not code for proteins or RNAs. Although some of these regions do contain crucial regulatory sequences, the vast majority of this DNA serves no known function. Typically, these regions of the genome are the ones in which the fastest change, in evolutionary terms, is observed, because there is typically little to no selection pressure acting on these regions to preserve their sequences.
In contrast, regions which code...

Gene Evolution - Fast or Slow?

Gene Evolution - Fast or Slow?

Speciation Rates

Speciation Rates

Factors Affecting Dissolution: Polymorphism, Amorphism and Pseudopolymorphism

Factors Affecting Dissolution: Polymorphism, Amorphism and Pseudopolymorphism

Polymorphism refers to the existence of a drug substance in multiple crystalline forms, known as polymorphs. Recently, this term has been expanded to include solvates (forms containing a solvent), amorphous forms (non-crystalline forms), and desolvated solvates (forms from which the solvent has been removed).
Some polymorphic crystals possess lower aqueous solubility than their amorphous counterparts, leading to incomplete absorption. For instance, the oral suspension of Chloramphenicol, which...

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by

Same author

Open reproducible scientometric research with Alexandria3k.

PloS one·2023

Same author

Conspicuous corruption: Evidence at a country level.

PloS one·2021

Same journal

DARUMA: a gateway to fast and easy prediction of intrinsically disordered regions.

PeerJ. Computer science·2026

Same journal

Alzheimer's disease detection using a quantum deep neural network with Haralick feature extraction and simulated annealing optimization.

PeerJ. Computer science·2026

Same journal

Network anomaly detection using Deep Autoencoder and parallel Artificial Bee Colony algorithm-trained neural network.

PeerJ. Computer science·2026

Same journal

An anomaly detection model for multivariate time series with anomaly perception.

PeerJ. Computer science·2026

Same journal

Retraction: A wormhole attack detection method for tactical wireless sensor networks.

PeerJ. Computer science·2026

Same journal

Evaluation of mental disorder with prioritization of its type by utilizing the bipolar complex fuzzy decision-making approach based on Schweizer-Sklar prioritized aggregation operators.

PeerJ. Computer science·2026

See all related articles

Search research articles

Related Experiment Video

Updated: Nov 10, 2025

Following the Dynamics of Structural Variants in Experimentally Evolved Populations

Following the Dynamics of Structural Variants in Experimentally Evolved Populations

Published on: February 3, 2023

Software evolution: the lifetime of fine-grained elements.

Diomidis Spinellis^1,2, Panos Louridas¹, Maria Kechagia³

¹Department of Management Science and Technology, Athens University of Economics and Business, Athens, Greece.

Peerj. Computer Science

|April 5, 2021

Summary

This summary is machine-generated.

Software source code lines are durable, with a median lifespan of 2.4 years. Young code is more prone to changes, but factors like programming language or developer experience do not significantly impact code longevity.

Keywords:

Code decay Hazard rate Repository mining Software aging Software evolution

More Related Videos

Daily Transfers, Archiving Populations, and Measuring Fitness in the Long-Term Evolution Experiment with Escherichia coli

Daily Transfers, Archiving Populations, and Measuring Fitness in the Long-Term Evolution Experiment with Escherichia coli

Published on: August 18, 2023

Designing Automated, High-throughput, Continuous Cell Growth Experiments Using eVOLVER

Designing Automated, High-throughput, Continuous Cell Growth Experiments Using eVOLVER

Published on: May 19, 2019

Related Experiment Videos

Last Updated: Nov 10, 2025

Following the Dynamics of Structural Variants in Experimentally Evolved Populations

Following the Dynamics of Structural Variants in Experimentally Evolved Populations

Published on: February 3, 2023

Daily Transfers, Archiving Populations, and Measuring Fitness in the Long-Term Evolution Experiment with Escherichia coli

Daily Transfers, Archiving Populations, and Measuring Fitness in the Long-Term Evolution Experiment with Escherichia coli

Published on: August 18, 2023

Designing Automated, High-throughput, Continuous Cell Growth Experiments Using eVOLVER

Designing Automated, High-throughput, Continuous Cell Growth Experiments Using eVOLVER

Published on: May 19, 2019

Area of Science:

Software Engineering
Computer Science
Empirical Software Analysis

Background:

Understanding software code evolution is crucial for efficient software development and maintenance.
Existing models often lack granular insights into the lifecycle of individual source code elements.

Purpose of the Study:

To develop and apply methods for tracking the lifetime of individual source code lines or tokens.
To analyze the lifespan of source code elements and identify factors influencing their longevity.

Main Methods:

Developed methods and tools to track the birth and death of each source code line/token.
Analyzed 3.3 billion source code element lifetime events across 89 revision control repositories.
Applied statistical analysis, including Weibull distribution, to model code line lifespans.

Main Results:

Code lines exhibit durability with a median lifespan of approximately 2.4 years.
Younger code lines are significantly more likely to be modified or deleted.
Code line longevity appears independent of specific line/token characteristics, programming language, developer tenure, or experience.
Project size and age showed only a slight correlation with code longevity.

Conclusions:

Software code elements have a predictable lifespan, with younger code being more volatile.
Key factors influencing software development efficiency, such as programming language and developer experience, do not significantly impact individual code line longevity.
The findings provide insights for optimizing software maintenance and development processes.