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Equinox P2 Resolution

Revision as of 20:17, 10 October 2008 by Unnamed Poltroon (Talk) (Current exploration)

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This document presents an abstract perspective on the data and the problem solved by p2, the new provisioning system being developed in the Equinox project.

Overall, the goal of p2 is to provide users the ability to manage the software installed on their system. Target systems are componentized such that each component expresses various dependencies, and there are multiple versions of each component available to the user. The installation of a given component is equivalent to satisfying all the constraints such that the component and all its prerequisites are installed while guaranteeing, for example, that the most recent version of each component is available.

Installable units: the software components

Installable Unit

Installable units (also referred to as IU) are unit of componentization used for software delivery in p2. An installable unit has the following attributes:

  • An identifier
  • A version
  • An enablement filter
  • A disjunction of requirement expressions
  • A set of capabilities
  • A singleton flag

Enablement filter

The enablement filter is of the form of an LDAP filter [1]. It indicates in which contexts an installable unit can be installed. The evaluation of this filter is done against a set of valued variables called an “evaluation context”.

Evaluation context

The evaluation context is a set of sets of valued variables. The following example represents an evaluation context containing two sets of valued variables: {{os=win32, ws=win32, nl=fr_FR}, {os=linux, nl=en_CA}} Such a context would evaluate to true for the following filters

  • (os=win32)
  • (& (os=linux) (nl=en_CA))

but would evaluate to false for the following filters:

  • (os=macos)
  • (& (os=win32) (ws=win32) (nl=fr_FR) (color=blue))


A capability has the three following attributes:

  • A namespace
  • A name
  • A version

We often say that an IU provides capabilities.

Requirement expression

A requirement expression is composed of two parts:

  • An enablement filter as defined previously. The absence of a filter is equivalent to a filter evaluating to true.
  • A Conjunctive Normal Form of Requirements. Note that we do not allow for negation in these CNFs, however we would be interested in understanding if this would be possible. In the examples “->” will be used to separate the filter from the CNF of requirements.


A requirement has the following attributes:

  • A namespace
  • A name
  • A version range
  • A greediness flag
  • A multiplicity flag
  • An optionality flag

Requirements are satisfied by capabilities.


  • In a given IU, there exists no relationship between the namespace/name/version of its capabilities and its identifier/version.
  • In a given IU, there exists no relationship between the namespace/name/version range of its requirements and its identifier/version.
  • In a given IU, there exists no relationship between the namespace/name/version of its capabilities and the namespace/name/version range of its requirements.
  • The same capability can be provided by multiple IUs.
  • The same requirement can be expressed by multiple IUs.
  • IUs can be involved in cyclic dependencies:
  • Example:
 IU A provides capability X and requires capability Y
 IU B provides capability Y and requires capability X
  • An IU can provide a capability it requires.
  • A capability can satisfy requirements from several IUs at the same time.


 IU org.eclipse.swt v 3.2.0
     {namespace=package, name=a, version=1.0.0}
     {namespace=foo, name=b, version=1.3.0}
     {namespace=package, name=c, version=4.1.0}
 Requirement expressions
   (true) ->
     {namespace=package, name=r1, range=[1.0.0, 2.0.0)} and
     {namespace=foo, name=r1, range=[3.2.0, 4.0.0)}
   (& (os=linux) (ws=gtk)) ->
     {namespace=package, name=r2, range=[1.0.0, 2.0.0)} or
     {namespace=foo, name=bar, range=[3.2.0, 4.0.0)}
 IU org.eclipse.jface v 3.3.0
     {namespace=package, name=a, version=1.0.0}
     {namespace=package, name=jface, version=3.1.0}
   Requirement expressions:
     (true) ->
        {namespace=package, name=a, range=[1.0.0, 2.0.0)} and
        {namespace=foo, name=b, range=[1.0.0, 4.0.0)}
  (& (os=linux) (ws=gtk)) ->
        {namespace=package, name=a, range=[1.0.0, 1.1.0)} or
        {namespace=foo, name=bar, range=[3.2.0, 4.0.0)}

Satisfaction of an installable unit

In order to be successfully installed on a user system, an installable unit’s requirement expression must be satisfied. This section defines what this means.

Satisfaction of an installable unit

An installable unit can be installed (satisfied) when one of its conjunction of requirement expression is satisfied and when each IU satisfying each requirement in this expression can also be installed.

Solution and pools of installable units

The transitive closure of the IUs satisfying the IU to install is called the Solution. The installable units added to the solution are coming from a Pool of Installable Units (IUPool).

Satisfaction of a requirement

A requirement is said to be satisfied by a capability iff the namespace and the name of the requirement and the capability are the same and the capability’s version is included into the requirement’s version range.

Satisfaction of requirement expressions

A requirement expression is satisfied iff the enablement filter evaluates to true and the CNF of requirements evaluates to true. For example, the following requirement expression

 (& (os=linux) (gtk=linux)) ->
   {namespace=package, name=a, range=[1.0.0, 1.1.0)} or
   {namespace=osfacility, name=gtk, range=[3.2.0, 4.0.0)}

will evaluate to true if the evaluation context contains at least a set such that {os=linux, gtk=linux} and one of the following requirement {namespace=package, name=a, version=1.0.0} or {namespace=osfacility, name=gtk, version=3.3.0} is satisfied.

Requirements greed

When a requirement is marked greedy (greediness flag on a requirement), installable units satisfying the requirements are added to the solution, whereas IU satisfying non greedy requirements should be added to the solution by another requirement. By default all requirements are greedy.

Requirements multiplicity

When the multiplicity flag is set to true, it indicates that all IUs carrying a capability satisfying the requirement should be considered for addition into the solution. By default this flag is false. Depending on the complexity we would like to explore whether this multiplicity flag could be changed to be a cardinality (for example: 0 or more, 1 or more, only 3, etc.).

Requirements optionality

The optionality flag on a requirement indicates that failure to satisfy the requirement does not prevent the IU from being satisfied.

IUs and singletons

IUs with the same identifier and with the singleton flag set to false can be installed simultaneously. IUs with the same identifier and where one or many have the flag singleton set to true can not be installed simultaneously.

Limiting the space: advice

In this section we present the notion of advice. Advice is a construct used as a source of information to further control which IUs will constitute the solution. We have currently 4 kinds of advice described below. They should be taken into account in the following order (the first one being the most important to respect): version control, causality, uses-clause, affinity

Version control

Version control advice is used to better control which IU could satisfy a requirement. For example, when an IU expresses a requirement on X [3.0.0, 4.0.0), the following advice: X [3.3.0, 3.4.0) would cause a more controlled version of X to be picked. Another way to look at advice is to consider it as directly overriding the requirements expressed in the IUs. The ability to narrow down the range is a must have, whereas the ability to widen/change the range is not.


Causality allows indicating additional IUs to be considered for installation when a particular IU is installed. For example one could say: When IU Word 97 is installed the IU X must be installed.

The strength of the relationship between the ‘cause’ IU and the ‘consequence’ IU could vary. Causality differs from requirements because they are not located in an IU and thus can not cause any IU to be non installable.

We would like to be able to have causes be expressions (e.g. A and B).

We would like to be able to use the availability of a capability as a cause.


Uses-clause expresses solution level consistency rules based on IUs. For example in a situation where:

   requires B [1.0, 2.0) and C [1.0, 3.0)
   requires C [1.1, 3.0)
 IU C (version 1.0, 2.0 and 3.0 available)

we need to able to express that the C used to satisfy A must be the same C that satisfied B. This construct would be highly desirable.


An affinity allows expressing favored relationships between IUs thus guiding what should be picked when trying to satisfy a requirement. Affinities can not cause the installation of the other IUs involved in the relationship, they are non-greedy. For example one could say, When the IU “Word 97 is installed and an IU “Excel” is necessary, favor IU “Excel 97” if it matches.

Dynamic Advice

As a cross-cutting concern, we are interested in understanding if advice can be discovered or changed while the solution is being built and if so under which limitations.

The question to be answered

The main question we want to ask the solver is:

Given, a set of sets of IU to install, an IUPool, a Solution and Advice, is there a solution where one IU from each set can be installed?

For example, given the following install sets {{IU A v 1, IU A v1.1}, { IU B v 2.0, IU B v 3, IU B v 3.1}, {IU C v 1}}, is there a solution where one of each of the subsets can be installed (e.g. IU A, IU B, IU C) can be installed.

Depending on the circumstances, we would like one or several of the following characteristics to also be met:

  • Ensure that it is always the highest/lowest version possible of each IU
  • Have the least number of IU in the solution
  • The least change from the existing solution

The solution returned should contain information on which IU satisfied which requirement. In the absence of a solution, an explanation must to be provided. We would also be interested in having the solver indicate if a solution existed by relaxing a few constraints.

Chained / nested solutions

Given multiple, inter-dependent systems and software to be deployed on some of them, could the solver be used to reason about the validity of all the systems at the same time. For example, if we had a client and a server in which software needed to be installed, how would we reason about the overall validity of the client and the server given that they interact and need to have compatible versions of the software on both?

Size of the problem and other relevant facts

  • Taken individually each IU from the IUPool is usually installable. It means that the

metadata of an IU has been written such that the IU is installable and it means that the IUPool usually contains all the IUs necessary to the satisfaction of an IU to be installed.

  • A typical system will likely be composed of thousands of IUs. An IU usually has around a 25 to 50 requirements and around 50 capabilities.
  • The IUPool may be composed of tens of thousands of IUs.
  • The current system at hand is composed of 1100 IUs.


A String Representation of LDAP Search Filters, RFC 1960, UMich, 1996,

Current solution

Following the ideas of [EDOS] and [OPIUM], the p2 resolver available in 1.0 (Eclipse 3.4 and greater) is based on a SAT solver approach using SAT4J ( pseudo boolean capabilities. Each IU is mapped to a set of constraints and an optimization function (more can be found in the class Projector [1]).

EDOS (W2P2) which explores ways to validate the content of a repository.

OPIUM which addresses the installation problem using a pseudo boolean solver.

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