Opendata, web and dolomites


AI based software platform

Total Cost €


EC-Contrib. €






 DC-IR project word cloud

Explore the words cloud of the DC-IR project. It provides you a very rough idea of what is the project "DC-IR" about.

quality    optimisation    detectable    save    data    ph2    defects    impossible    suggestions    answer    uses    compounded    fixing    google    create    machine    validating    repositories    thousands    unlimited    question    almost    fixes    road    deepcode    developer    expensive    5k    version    programmers    oacute    trained    intelligence    11    provides    ai    software    reviews    time    companies    integrates    consuming    learning    billions    tool    map    single    review    lines    offers    proportionally    savings    spending    market    versi    ml    assurance    proprietary    solutions    solution    coding    solved    guarantee    856    services    paid    see    annually    suggest    finalise    levels    language    25    artificial    big    manner    frameworks    automatically    code    20    approx    full    source    learnings    representations    gt    licenses    beta    ph1    developers    rises    programming    millions    techniques    dc    languages    powerful    errors    ir    globally    52bn    industry    performs    independent    platform    improvements    stage    close   

Project "DC-IR" data sheet

The following table provides information about the project.


Organization address
city: ZURICH
postcode: 8032
website: n.a.

contact info
title: n.a.
name: n.a.
surname: n.a.
function: n.a.
email: n.a.
telephone: n.a.
fax: n.a.

 Coordinator Country Switzerland [CH]
 Project website
 Total cost 71˙429 €
 EC max contribution 50˙000 € (70%)
 Programme 1. H2020-EU.3. (PRIORITY 'Societal challenges)
2. H2020-EU.2.3. (INDUSTRIAL LEADERSHIP - Innovation In SMEs)
3. H2020-EU.2.1. (INDUSTRIAL LEADERSHIP - Leadership in enabling and industrial technologies)
 Code Call H2020-SMEInst-2018-2020-1
 Funding Scheme SME-1
 Starting year 2019
 Duration (year-month-day) from 2019-06-01   to  2019-09-30


Take a look of project's partnership.

# participants  country  role  EC contrib. [€] 
1    DEEPCODE AG CH (ZURICH) coordinator 50˙000.00


 Project objective

Software has become very complex with time, with each software program having millions of lines of code. With so many code lines, it is close to impossible not to make errors when coding. The number of code defects rises proportionally with more code lines, (approx. 10-20 defects per 1,000 lines of code). This necessitates millions of code reviews and code fixes for a single software program. The current code review process is very expensive, time consuming (with companies like Google spending >25% of their time on code reviews) and often does not guarantee success in fixing the code. The software industry needs a cost & time-effective code analysis tool that is unlimited in detectable code errors and programming languages. Our solution is DeepCode AI Code Review (DC-IR), an Artificial Intelligence (AI) platform that automatically performs reviews on software code and provides suggestions based on Big Code learnings (how others solved similar code related problems). Our platform is trained from millions of Open Source repositories (billions of lines of code; thousands of frameworks & millions of code fixes) and uses these data sets to suggest code improvements for programmers. DC-IR integrates many levels of program code analysis into proprietary Machine Learning (ML) representations which are used by powerful ML techniques to create Data Sets that can answer almost any question about a software in a language independent manner. DC-IR offers a full set of services for code optimisation with solutions for code fixes & quality assurance. DC-IR enables developers to save 20% of development time, leading to savings of €11,856 annually per developer, which compounded globally can save the industry >€52Bn annually. DC-IR is at an advanced stage of development with a Beta version already deployed and having more than 5k users, some using paid licenses. During Ph1, we will develop a road map to finalise DC-IR and Ph2 will see us developing and validating the market versión.

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The information about "DC-IR" are provided by the European Opendata Portal: CORDIS opendata.

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