| Package | Description |
|---|---|
| org.apache.cayenne |
Contains persistence APIs directly accessible by users.
|
| org.apache.cayenne.access |
Contains classes that make up Cayenne ORM stack.
|
| org.apache.cayenne.configuration | |
| org.apache.cayenne.conn | |
| org.apache.cayenne.exp |
Cayenne data expression classes.
|
| org.apache.cayenne.exp.parser |
Contains expression parser and other expression internals.
|
| org.apache.cayenne.map |
Contains O/R mapping classes that store relational database
metadata information and map it to Java classes.
|
| org.apache.cayenne.query |
Defines standard queries supported by Cayenne and extension mechanism to create
custom queries.
|
| org.apache.cayenne.util |
General utility classes.
|
| Class and Description |
|---|
| GenericQueryResult
Generic implementation of QueryResult using List as QueryResultItem storage.
|
| ObjectContextGraphAction
A base implementation of a helper class to handle
ObjectContext.propertyChanged(org.apache.cayenne.Persistent, String, Object, Object)
processing on behalf of an ObjectContext. |
| Class and Description |
|---|
| PersistentObjectCollection
Simple interface to unify PersistentObject* collections in way of
setting properties directly
|
| PersistentObjectList
A list of persistent objects lazily resolved on the first access.
|
| PersistentObjectSet |
| RelationshipFault
An abstract superclass of lazily faulted to-one and to-many relationships.
|
| Class and Description |
|---|
| XMLEncoder
A helper class to encode objects to XML.
|
| XMLSerializable
Interface for Cayenne objects that can be saved to XML.
|
| Class and Description |
|---|
| XMLEncoder
A helper class to encode objects to XML.
|
| XMLSerializable
Interface for Cayenne objects that can be saved to XML.
|
| Class and Description |
|---|
| XMLEncoder
A helper class to encode objects to XML.
|
| XMLSerializable
Interface for Cayenne objects that can be saved to XML.
|
| Class and Description |
|---|
| CayenneMapEntry
Defining a double-linked named entry in CayenneMap.
|
| XMLSerializable
Interface for Cayenne objects that can be saved to XML.
|
| Class and Description |
|---|
| CayenneMapEntry
Defining a double-linked named entry in CayenneMap.
|
| XMLEncoder
A helper class to encode objects to XML.
|
| XMLSerializable
Interface for Cayenne objects that can be saved to XML.
|
| Class and Description |
|---|
| XMLEncoder
A helper class to encode objects to XML.
|
| XMLSerializable
Interface for Cayenne objects that can be saved to XML.
|
| Class and Description |
|---|
| EntityMergeListener
EntityMergeListener interface defines API useful for listening to
EntityMergeSupport processing.
|
| EqualsBuilder
Assists in implementing
Object.equals(Object) methods. |
| HashCodeBuilder
Assists in implementing
Object.hashCode() methods. |
| ListResponse
A QueryResponse optimized to hold a single object or data row list.
|
| PersistentObjectCollection
Simple interface to unify PersistentObject* collections in way of
setting properties directly
|
| ProcedureResultBuilder |
| QueryResultBuilder |
| RelationshipFault
An abstract superclass of lazily faulted to-one and to-many relationships.
|
| ToStringBuilder
A utility class to simplify implementation of Object toString methods.
|
| XMLEncoder
A helper class to encode objects to XML.
|
| XMLSerializable
Interface for Cayenne objects that can be saved to XML.
|
Copyright © 2001–2019 Apache Cayenne. All rights reserved.


Michael Bloomberg formally announces US presidential candidacy
The move is an about-face for Bloomberg, 77, who said in March he would not make a 2020 run for the White House.
Michael Bloomberg announced on Sunday he is running for president, joining the crowded field of Democrats seeking to take on his fellow New York billionaire, President Donald Trump.
"I'm running for president to defeat Donald Trump and rebuild America," Bloomberg, 77, said on his webpage as a $30m Bloomberg ad campaign hit US airwaves.
More:
The announcement ended speculation about the intentions of Bloomberg, who for weeks has been filing paperwork to be eligible as a candidate in primary voting and registered with the Federal Election Commission.
The move was an about-face for Bloomberg who said in March he would not make a 2020 run for the White House.
"We cannot afford four more years of President Trump's reckless and unethical actions," the former New York mayor said.
"He represents an existential threat to our country and our values. If he wins another term in office, we may never recover from the damage."
With a personal fortune of $50bn, Bloomberg will shake up the open race, with 17 candidates already vying to be the Democratic nominee to take on Trump next year.
Former Vice President Joe Biden leads the race ahead of left-wingers Elizabeth Warren and Bernie Sanders, with moderate Pete Buttigieg in fourth place, according to national polls.
'Disgusted'
Even before the announcement was made, Democratic rivals such as Sanders pounced on Bloomberg's plans to rely on his personal fortune.
"I'm disgusted by the idea that Michael Bloomberg or any billionaire thinks they can circumvent the political process and spend tens of millions of dollars to buy elections," he tweeted on Friday.
Warren, another leading progressive candidate, also slammed Bloomberg on Saturday for trying to buy the presidency.
"I understand that rich people are going to have more shoes than the rest of us, they're going to have more cars than the rest of us, they're going to have more houses," she said after a campaign stop in Manchester, New Hampshire.
"But they don't get a bigger share of democracy, especially in a Democratic primary. We need to be doing the face-to-face work that lifts every voice."
Dubious record on race
Before Bloomberg's presidential announcement, the mayors of Columbia, South Carolina, and Louisville, Kentucky, endorsed him.
Despite that show of support from two local black leaders, Bloomberg may have trouble building a multiracial coalition early on given his turbulent record on race relations in New York City.
He angered many minority voters during his 12 years in the mayor’s office for embracing and defending the controversial "stop-and-frisk" police strategy, despite its disproportionate effect on people of colour.
Facing an African American congregation this month in Brooklyn, Bloomberg apologised and acknowledged it often led to the detention of minorities.
The apology was received sceptically by many prominent activists who noted it was made as he was taking steps to enter the presidential race.


☰
Shubham Nishad
About
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react
Lyrics Search React
Simple react app. Find lyrics of songs using Musixmatch api.
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MCP Notification Service Test
1. Confirm the notification service address:
:
2. Enter the number of printers for each iteration:
3. Select a notification protocol:
Hanging HTTP
Websocket
4. Enter the number of iterations:
5. Execute the test:
Show statistics
iteration
min (msec)
max (msec)
avg (msec)


It is responsible for the end to end delivery of data which means that it is responsible for the application to application. It works on the port address.
It is responsible for the source to destination delivery of data.it works on IP address or logical address.
It is responsible for the end to end delivery of data. It works on the MAC address. Flow control and error control and framing are also the responsibility of the data link layer.
Use for synchronization of the data.
1) Check the coding scheme.
2) Encript and Decript.
3) Compression.


Grid Notify
v{{ version }}
User name:
{{ user_name }}
, gender:
{{ gender }}
, membership:
{{ membership }}
, age:
{{ age }}
, faked checked:
{{ fake_checked }}
, image:
{{ image }}
, has webcam:
{{ has_webcam }}
, country:
{{ country }}
, city:
{{ city }}
Current room:
none
, Owner(s) of room:
none
ACL for this room:
Genders
Memberships
Min age
Max age
Country
City
Needs webcam?
Needs image?
Needs to be fake checked?
Update ACL
Remove room
Set invisible
Set visible
Request admin
Streaming on
Streaming off
Join by room name
Leave by room name
Room Name:
Users in current room:
All channels:
All rooms in the channel:
Leave this room
Create new room:


JQuery Trial Example
Button1
Button2
Button3
Button4
Panel-One
This is the content of panel one
Panel-Two
This is the content of panel two
Panel-Three
This is the content of panel three
Panel-Four
This is the content of panel four


city tours/ tour tickets/ tour guides
blue tshirt
add to cart
women shirt
yellow tshirt
cool lingerie


Covid19 - Notify Vaccine Availability
Developed by
Raj Mohan
FIND VACCINE AVAILABILITY
STATE
DISTRICT
DATE
Hospitals
Ages:
18+
45+
Both
SEARCH
Stop
ENABLE NOTIFICATOION


A B C D E F G H I K L M N O P R S T U V misc
| abs-method | Mathematical functions |
| abs.spam | Mathematical functions |
| acos-method | Mathematical functions |
| acos.spam | Mathematical functions |
| acosh-method | Mathematical functions |
| acosh.spam | Mathematical functions |
| adjacency | Administrative districts of Germany |
| adjacency.landkreis | Administrative districts of Germany |
| adjacency.spam | Administrative districts of Germany |
| all-method | Rounding of Numbers |
| all.equal-method | Test if Two 'spam' Objects are (Nearly) Equal |
| all.equal.spam | Test if Two 'spam' Objects are (Nearly) Equal |
| all.spam | Rounding of Numbers |
| any-method | Rounding of Numbers |
| any.spam | Rounding of Numbers |
| apply.spam | Apply Functions Over Sparse Matrix Margins |
| Arith-method | Class "spam" |
| as.dgCMatrix.spam | Transformation to other sparse formats |
| as.dgRMatrix.spam | Transformation to other sparse formats |
| as.matrix-method | Class "spam" |
| as.matrix-method | Class "spam.chol.NgPeyton" |
| as.matrix.spam | Class "spam" |
| as.spam | Sparse Matrix Class |
| as.spam-method | Sparse Matrix Class |
| as.spam-method | Class "spam.chol.NgPeyton" |
| as.spam.chol.NgPeyton | Sparse Matrix Class |
| as.spam.dgCMatrix | Transformation to other sparse formats |
| as.spam.dgRMatrix | Transformation to other sparse formats |
| as.spam.dist | Sparse Matrix Class |
| as.spam.list | Sparse Matrix Class |
| as.spam.matrix | Sparse Matrix Class |
| as.spam.matrix.csr | Transformation to other sparse formats |
| as.spam.numeric | Sparse Matrix Class |
| as.spam.spam | Sparse Matrix Class |
| as.vector | Coercion to a Vector |
| as.vector-method | Coercion to a Vector |
| as.vector.spam | Coercion to a Vector |
| asin-method | Mathematical functions |
| asin.spam | Mathematical functions |
| asinh-method | Mathematical functions |
| asinh.spam | Mathematical functions |
| assign.spam | Basic Linear Algebra for Sparse Matrices |
| atan-method | Mathematical functions |
| atan.spam | Mathematical functions |
| atanh-method | Mathematical functions |
| atanh.spam | Mathematical functions |
| backsolve | Linear Equation Solving for Sparse Matrices |
| backsolve-method | Linear Equation Solving for Sparse Matrices |
| backsolve-method | Class "spam.chol.NgPeyton" |
| backsolve-methods | Linear Equation Solving for Sparse Matrices |
| backsolve.spam | Linear Equation Solving for Sparse Matrices |
| bandwidth | Bandwidth of a Sparse Matrix |
| bdiag | Binds Arrays Corner-to-Corner |
| bdiag.spam | Binds Arrays Corner-to-Corner |
| c-method | Class "spam" |
| c-method | Class "spam.chol.NgPeyton" |
| cbind | Combine spam Matrices by Rows or Columns |
| cbind-method | Combine spam Matrices by Rows or Columns |
| cbind.spam | Combine spam Matrices by Rows or Columns |
| ceiling-method | Mathematical functions |
| ceiling.spam | Mathematical functions |
| chol | Cholesky Factorization for Sparse Matrices |
| chol-method | Cholesky Factorization for Sparse Matrices |
| chol-method | Class "spam.chol.NgPeyton" |
| chol.spam | Cholesky Factorization for Sparse Matrices |
| chol2inv | Linear Equation Solving for Sparse Matrices |
| chol2inv-method | Linear Equation Solving for Sparse Matrices |
| chol2inv.spam | Linear Equation Solving for Sparse Matrices |
| circulant.spam | Create Circulant Matrices |
| cleanup | Cleaning up sparse matrices |
| coerce-method | Force a 'spam' Object to Belong to a Class |
| coerce.spam | Force a 'spam' Object to Belong to a Class |
| colindices | Slot modification |
| colindices<- | Slot modification |
| colMeans | Form Row and Column Sums and Means |
| colMeans-method | Form Row and Column Sums and Means |
| colMeans.spam | Form Row and Column Sums and Means |
| colSums | Form Row and Column Sums and Means |
| colSums-method | Form Row and Column Sums and Means |
| colSums.spam | Form Row and Column Sums and Means |
| Compare-method | Class "spam" |
| complexities | Complexity for Sparse Matrices |
| complexity | Complexity for Sparse Matrices |
| constructors | Slot modification |
| cor.sph | Covariance functions |
| cos-method | Mathematical functions |
| cos.spam | Mathematical functions |
| cosh-method | Mathematical functions |
| cosh.spam | Mathematical functions |
| cov.exp | Covariance functions |
| cov.mat | Covariance functions |
| cov.nug | Covariance functions |
| cov.sph | Covariance functions |
| cov.wend1 | Covariance functions |
| cov.wend2 | Covariance functions |
| cov.wu1 | Covariance functions |
| cov.wu2 | Covariance functions |
| cov.wu3 | Covariance functions |
| covmat | Covariance functions |
| crossprod-method | Spam Matrix Crossproduct |
| crossprod.default | Spam Matrix Crossproduct |
| crossprod.spam | Spam Matrix Crossproduct |
| cummax-method | Mathematical functions |
| cummax.spam | Mathematical functions |
| cummin-method | Mathematical functions |
| cummin.spam | Mathematical functions |
| cumprod-method | Mathematical functions |
| cumprod.spam | Mathematical functions |
| cumsum-method | Mathematical functions |
| cumsum.spam | Mathematical functions |
| det | Calculate the determinant of a positive definite Sparse Matrix |
| det-method | Calculate the determinant of a positive definite Sparse Matrix |
| det.spam | Calculate the determinant of a positive definite Sparse Matrix |
| determinant | Calculate the determinant of a positive definite Sparse Matrix |
| determinant-method | Calculate the determinant of a positive definite Sparse Matrix |
| determinant-method | Class "spam.chol.NgPeyton" |
| determinant.spam | Calculate the determinant of a positive definite Sparse Matrix |
| determinant.spam.chol | Calculate the determinant of a positive definite Sparse Matrix |
| determinant.spam.chol.NgPeyton | Calculate the determinant of a positive definite Sparse Matrix |
| diag | Sparse Matrix diagonals |
| diag-method | Sparse Matrix diagonals |
| diag-method | Class "spam.chol.NgPeyton" |
| diag.assign-method | Sparse Matrix diagonals |
| diag.of.spam | Sparse Matrix diagonals |
| diag.spam | Sparse Matrix diagonals |
| diag.spam<- | Sparse Matrix diagonals |
| diag<- | Sparse Matrix diagonals |
| diag<--method | Sparse Matrix diagonals |
| diag<--method | Class "spam.chol.NgPeyton" |
| diag<-.spam | Sparse Matrix diagonals |
| diff | Lagged Differences |
| diff-method | Lagged Differences |
| diff.spam | Lagged Differences |
| digamma-method | Mathematical functions |
| digamma.spam | Mathematical functions |
| dim-method | Basic Linear Algebra for Sparse Matrices |
| dim-method | Class "spam.chol.NgPeyton" |
| dim.spam | Dimensions of an Object |
| dim<--method | Dimensions of an Object |
| dim<--method | Class "spam.chol.NgPeyton" |
| dim<-.spam | Dimensions of an Object |
| dimension<- | Slot modification |
| display | Graphially Represent the Nonzero Entries |
| display-method | Graphially Represent the Nonzero Entries |
| display-method | Class "spam.chol.NgPeyton" |
| display.spam | Graphially Represent the Nonzero Entries |
| dist.spam | Distance Matrix Computation |
| distance | Distance Matrix Computation |
| eigen.spam | Eigenvalues for Sparse Matrices |
| eigen_approx | Eigenvalues for Sparse Matrices |
| entries | Slot modification |
| entries<- | Slot modification |
| exp-method | Mathematical functions |
| exp.spam | Mathematical functions |
| floor-method | Mathematical functions |
| floor.spam | Mathematical functions |
| foreign | Transformation to other sparse formats |
| forwardsolve | Linear Equation Solving for Sparse Matrices |
| forwardsolve-method | Linear Equation Solving for Sparse Matrices |
| forwardsolve-method | Class "spam.chol.NgPeyton" |
| forwardsolve-methods | Linear Equation Solving for Sparse Matrices |
| forwardsolve.spam | Linear Equation Solving for Sparse Matrices |
| gamma-method | Mathematical functions |
| gamma.spam | Mathematical functions |
| germany | Meta-data about administrative districts of Germany |
| germany.data | Meta-data about administrative districts of Germany |
| germany.graph | Administrative districts of Germany |
| germany.info | Meta-data about administrative districts of Germany |
| germany.plot | Plot administrative districts of Germany |
| germany.poly | Meta-data about administrative districts of Germany |
| germany.spam | Meta-data about administrative districts of Germany |
| getOption.spam | Options Settings |
| gmult | Generalized Multiplication |
| grid_trace2 | Two trace plots and a scatter plot. |
| grid_zoom | grid_zoom |
| head-method | Return the First or Last Part of an Object |
| head.spam | Return the First or Last Part of an Object |
| image | Display a spam Object as Color Image |
| image-method | Display a spam Object as Color Image |
| image-method | Class "spam.chol.NgPeyton" |
| image.spam | Display a spam Object as Color Image |
| image.spam.chol | Display a spam Object as Color Image |
| import | Read External Matrix Formats |
| initialize-method | Sparse Matrix Class |
| is.spam | Sparse Matrix Class |
| isSymmetric-method | Test if a spam matrix is Symmetric |
| isSymmetric.spam | Test if a spam matrix is Symmetric |
| kronecker-method | Kronecker Products on Sparse Matrices |
| kronecker.default | Kronecker Products on Sparse Matrices |
| kronecker.spam | Kronecker Products on Sparse Matrices |
| large matries | Large 64-bit matrices require the R package 'spam64' |
| large matrix | Large 64-bit matrices require the R package 'spam64' |
| large_matries | Large 64-bit matrices require the R package 'spam64' |
| large_matrix | Large 64-bit matrices require the R package 'spam64' |
| length-method | Class "spam" |
| length-method | Class "spam.chol.NgPeyton" |
| length<--method | Class "spam" |
| length<--method | Class "spam.chol.NgPeyton" |
| lgamma-method | Mathematical functions |
| lgamma.spam | Mathematical functions |
| log-method | Mathematical functions |
| log.spam | Mathematical functions |
| log10-method | Mathematical functions |
| log10.spam | Mathematical functions |
| log2-method | Mathematical functions |
| log2.spam | Mathematical functions |
| long vector | Large 64-bit matrices require the R package 'spam64' |
| long vectors | Large 64-bit matrices require the R package 'spam64' |
| lower.tri | Lower and Upper Triangular Part of a Sparse Matrix |
| lower.tri-method | Class "spam" |
| lower.tri.spam | Lower and Upper Triangular Part of a Sparse Matrix |
| map.landkreis | Administrative districts of Germany |
| Math | Mathematical functions |
| Math-method | Mathematical functions |
| Math.spam | Mathematical functions |
| Math2 | Rounding of Numbers |
| Math2-method | Rounding of Numbers |
| Math2.spam | Rounding of Numbers |
| max-method | Rounding of Numbers |
| max.spam | Rounding of Numbers |
| min-method | Rounding of Numbers |
| min.spam | Rounding of Numbers |
| mle | Maximum likelihood estimates |
| mle.nomean | Maximum likelihood estimates |
| mle.nomean.spam | Maximum likelihood estimates |
| mle.spam | Maximum likelihood estimates |
| ncol-method | Basic Linear Algebra for Sparse Matrices |
| nearest.dist | Distance Matrix Computation |
| neg2loglikelihood | Maximum likelihood estimates |
| neg2loglikelihood.spam | Maximum likelihood estimates |
| norm | Basic Linear Algebra for Sparse Matrices |
| norm-method | Basic Linear Algebra for Sparse Matrices |
| norm.spam | Basic Linear Algebra for Sparse Matrices |
| nrow-method | Basic Linear Algebra for Sparse Matrices |
| Ops.spam | Basic Linear Algebra for Sparse Matrices |
| options.spam | Options Settings |
| Oral | Oral Cavity Cancer |
| Oral.spam | Oral Cavity Cancer |
| oral.spam | Oral Cavity Cancer |
| ordering | Extract the permutation |
| ordering-method | Extract the permutation |
| ordering-method | Class "spam.chol.NgPeyton" |
| ordering-methods | Extract the permutation |
| ordering.spam | Extract the permutation |
| ordering.spam.chol | Extract the permutation |
| ordering.spam.chol.NgPeyton | Extract the permutation |
| overview | SPArse Matrix Package |
| pad | Padding a (sparse) matrix |
| pad.spam | Padding a (sparse) matrix |
| pad<- | Padding a (sparse) matrix |
| pad<--method | Padding a (sparse) matrix |
| pad<-.spam | Padding a (sparse) matrix |
| permutation | Permute a matrix |
| permutation-method | Permute a matrix |
| permutation.spam | Permute a matrix |
| plot-method | Class "spam" |
| plot.spam | Basic Linear Algebra for Sparse Matrices |
| powerboost | Specific options Setting |
| precmat | IGMRF Precision Matrices |
| precmat.GMRFreglat | Create Precision Matrices |
| precmat.IGMRFirreglat | IGMRF Precision Matrices |
| precmat.IGMRFreglat | IGMRF Precision Matrices |
| precmat.RW1 | IGMRF Precision Matrices |
| precmat.RW2 | IGMRF Precision Matrices |
| precmat.RWn | IGMRF Precision Matrices |
| precmat.season | IGMRF Precision Matrices |
| Printing and summarizing sparse matrices | |
| print-method | Printing and summarizing sparse matrices |
| print-method | Class "spam.chol.NgPeyton" |
| print.spam | Printing and summarizing sparse matrices |
| print.spam.chol | Printing and summarizing sparse matrices |
| print.spam.chol.NgPeyton | Printing and summarizing sparse matrices |
| print_nnzpos | Printing and summarizing sparse matrices |
| prod-method | Rounding of Numbers |
| prod.spam | Rounding of Numbers |
| range-method | Rounding of Numbers |
| range.spam | Rounding of Numbers |
| rbind | Combine spam Matrices by Rows or Columns |
| rbind-method | Combine spam Matrices by Rows or Columns |
| rbind.spam | Combine spam Matrices by Rows or Columns |
| rdist.dist | Wrapper for Distance Matrix Computation |
| read.HB | Read External Matrix Formats |
| read.MM | Read External Matrix Formats |
| rmvnorm | Draw Multivariate Normals |
| rmvnorm.canonical | Draw Multivariate Normals |
| rmvnorm.canonical.const | Draw Constrainted Multivariate Normals |
| rmvnorm.const | Draw Constrainted Multivariate Normals |
| rmvnorm.prec | Draw Multivariate Normals |
| rmvnorm.prec.const | Draw Constrainted Multivariate Normals |
| rmvnorm.spam | Draw Multivariate Normals |
| round-method | Rounding of Numbers |
| round.spam | Rounding of Numbers |
| rowMeans | Form Row and Column Sums and Means |
| rowMeans-method | Form Row and Column Sums and Means |
| rowMeans.spam | Form Row and Column Sums and Means |
| rowpointers | Slot modification |
| rowpointers<- | Slot modification |
| rowSums | Form Row and Column Sums and Means |
| rowSums-method | Form Row and Column Sums and Means |
| rowSums.spam | Form Row and Column Sums and Means |
| show-method | Class "spam" |
| show-method | Class "spam.chol.NgPeyton" |
| signif-method | Rounding of Numbers |
| signif.spam | Rounding of Numbers |
| sin-method | Mathematical functions |
| sin.spam | Mathematical functions |
| solve | Linear Equation Solving for Sparse Matrices |
| solve-method | Linear Equation Solving for Sparse Matrices |
| solve.spam | Linear Equation Solving for Sparse Matrices |
| SPAM | SPArse Matrix Package |
| Spam | SPArse Matrix Package |
| spam | Sparse Matrix Class |
| spam-class | Class "spam" |
| spam-defunct | Defunct Objects in Package 'spam' |
| spam-method | Sparse Matrix Class |
| spam.chol.NgPeyton-class | Class "spam.chol.NgPeyton" |
| spam.class | Class "spam" |
| spam.creation | Sparse Matrix Class |
| spam.list | Sparse Matrix Class |
| spam.numeric | Sparse Matrix Class |
| spam.ops | Basic Linear Algebra for Sparse Matrices |
| spam.options | Options Settings |
| spam.Version | Spam Version Information |
| spam.version | Spam Version Information |
| spam64 | Large 64-bit matrices require the R package 'spam64' |
| spam_diag | Sparse Matrix diagonals |
| spam_random | Create Random spam Matrices |
| spam_rdist | Wrapper for Distance Matrix Computation |
| spam_rdist.earth | Wrapper for Distance Matrix Computation |
| sqrt-method | Mathematical functions |
| sqrt.spam | Mathematical functions |
| subset.spam | Basic Linear Algebra for Sparse Matrices |
| sum-method | Rounding of Numbers |
| sum.spam | Rounding of Numbers |
| Summary | Rounding of Numbers |
| Summary-method | Rounding of Numbers |
| summary-method | Printing and summarizing sparse matrices |
| summary-method | Class "spam.chol.NgPeyton" |
| Summary.spam | Rounding of Numbers |
| summary.spam | Printing and summarizing sparse matrices |
| summary.spam.chol | Printing and summarizing sparse matrices |
| summary.spam.chol.NgPeyton | Printing and summarizing sparse matrices |
| t-method | Class "spam" |
| t-method | Class "spam.chol.NgPeyton" |
| t.spam | Basic Linear Algebra for Sparse Matrices |
| tail-method | Return the First or Last Part of an Object |
| tail.spam | Return the First or Last Part of an Object |
| tan-method | Mathematical functions |
| tan.spam | Mathematical functions |
| tcrossprod-method | Spam Matrix Crossproduct |
| tcrossprod.spam | Spam Matrix Crossproduct |
| toeplitz.spam | Create Toeplitz Matrices |
| trigamma-method | Mathematical functions |
| trigamma.spam | Mathematical functions |
| triplet | Transform a spam format to triplets |
| trunc-method | Mathematical functions |
| trunc.spam | Mathematical functions |
| update-method | Cholesky Factorization for Sparse Matrices |
| update.spam | Cholesky Factorization for Sparse Matrices |
| update.spam.chol.NgPeyton | Cholesky Factorization for Sparse Matrices |
| upper.tri | Lower and Upper Triangular Part of a Sparse Matrix |
| upper.tri-method | Class "spam" |
| upper.tri.spam | Lower and Upper Triangular Part of a Sparse Matrix |
| UScounties | Adjacency structure of the counties in the contiguous United States |
| UScounties.ndorder | Adjacency structure of the counties in the contiguous United States |
| UScounties.storder | Adjacency structure of the counties in the contiguous United States |
| USprecip | Monthly total precipitation (mm) for April 1948 in the contiguous United States |
| validate_spam | Validate a spam objects |
| validspamobject | Defunct Objects in Package 'spam' |
| var.spam | Wappers for Sparse Matrices |
| version | Spam Version Information |
| !-method | Class "spam" |
| !=-method | Basic Linear Algebra for Sparse Matrices |
| %%-method | Basic Linear Algebra for Sparse Matrices |
| %*%-method | Basic Linear Algebra for Sparse Matrices |
| %*%-methods | Basic Linear Algebra for Sparse Matrices |
| %/%-method | Basic Linear Algebra for Sparse Matrices |
| %d*% | Basic Linear Algebra for Sparse Matrices |
| %d*%-method | Basic Linear Algebra for Sparse Matrices |
| %d+% | Basic Linear Algebra for Sparse Matrices |
| %d+%-method | Basic Linear Algebra for Sparse Matrices |
| &-method | Basic Linear Algebra for Sparse Matrices |
| *-method | Basic Linear Algebra for Sparse Matrices |
| +-method | Class "spam" |
| +-method | Basic Linear Algebra for Sparse Matrices |
| --method | Class "spam" |
| --method | Basic Linear Algebra for Sparse Matrices |
| . SPAM . | SPArse Matrix Package |
| /-method | Basic Linear Algebra for Sparse Matrices |
| 64bit | Large 64-bit matrices require the R package 'spam64' |
| 64bits | Large 64-bit matrices require the R package 'spam64' |
| <-method | Basic Linear Algebra for Sparse Matrices |
| <=-method | Basic Linear Algebra for Sparse Matrices |
| ==-method | Basic Linear Algebra for Sparse Matrices |
| >-method | Basic Linear Algebra for Sparse Matrices |
| >=-method | Basic Linear Algebra for Sparse Matrices |
| [-method | Class "spam" |
| [.spam | Basic Linear Algebra for Sparse Matrices |
| [<--method | Class "spam" |
| [<--method | Basic Linear Algebra for Sparse Matrices |
| [<-.spam | Basic Linear Algebra for Sparse Matrices |
| ^-method | Basic Linear Algebra for Sparse Matrices |
| |-method | Basic Linear Algebra for Sparse Matrices |


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- transition web-enabled e-commerce
- enable 24/7 e-markets
- streamline synergistic action-items
- repurpose 24/7 e-business
- cultivate cross-media portals
- target user-centric architectures


| UET kicks | Adv. web application | Asad abbas | 9am to 1pm |
| UET kicks | Adv. web applictaion | Shoaib | 9am to 1pm |
| UET kicks | Adv. web application | Shaffi ullah | 9am to 1pm |
| UET kicks | Adv. web application | Saad | 9am to 1pm |
| UET kicks | Adv. web application | zahid | 9am to 1pm |


{{ .Title }}
{{ .Description }}
read more{{ partial "html_header.html" . }}
we work remotely!
We deliver dedicated software solutions and provide consultancy to a wide variety of industries. That includes:
projects
and hybrid apps
and backend services
and manipulation
Happy Team was founded in 2015 when 5 software developers, who enjoyed working together, decided to go independent and fully unlock their potential as a team.
Happy Team supports customers from around the world in their business by providing them with smart and passionate software developers. Every one of them spent last decade expanding his skills in software development field choosing different paths and technologies.
Dev, motorcyclist, dreamer and coffee lover. He starts every day with a new idea and strives to be at least a bit better by sunset. No one told him that some things are not possible in code, so he does it all.
Michał is a passionate software developer touching everything from C# to Javascript frameworks, not afraid of F# and Objective-C. He loves meetups and conferences.
Enthusiastic JS afficionado sharing his passion for the front-end at various international conferences. He is also managing our biggest project and the clients love his deep understanding of their business model and problem domain.
Software dev, interested in functional programming and learning new programming languages in general. Dreams of having an animal shelter. Also, a tea enthusiast, runner, gamer.
Backend developer trying to understand the magic of JavaScript. The one thing that scares him is SharePoint, besides that he's afraid of nothing! In his spare time he travels across Poland on a motorcycle just to clear his mind.
A firm believer that being pragmatic in software development can make a big difference. Jack of all trades and master of none. Will code at 4 AM because he can.
Young Java, JavaScript, C# dev. He still believes that clean code and unit tests make a difference. His motivation to work is a desire to continuously develop himself. He likes challenges and solving difficult problems. After work he tries to keep in shape.
A developer that believes that optimised workflow for a user matters. Experienced in all layers but having more passion for building frontend with perfectly aligned elements. Always up for riddles and weekend travels.
Software developer. Experienced in all layers, but he likes backend, databases and networking the most. He's not afraid of JavaScript (anymore). Believes that software design and readable code do exist. After work a father and cyclist.
Software developer working with web technologies from the beginning of his professional career. Loves programming riddles and is open to learning new programming languages. Unfulfilled traveler trying to find work-life balance.
Our values define who we are. They are the fundamental beliefs of our team. They influence the way we work with each other, serve our customers and engage with communities.
Caring
Knowledge Sharing
Passion
Fun
Excellence
Our cooperation with Happy Team started when Kuba Walinski - one of the founders - gave us a helping hand on a project that
was at risk. Even though we never met in person I must admit that any work done for us by Happy Team is of great
quality and always on time. Moreover, Happy Team understands our business very well, even though we realise our
explanations are not always crystal clear ;)
I definitely recommend Happy Team!
I have been working with Happy Team for over a year and have been impressed with their talent, professionalism and problem solving abilities. They have always delivered on time without the need for oversight. They have been a true force multiplier for my business.
Riccardo Terrell{{ .Description }}
read more


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|
mbed TLS v2.16.11
|
ASN.1 buffer writing functionality. More...
Go to the source code of this file.
Macros | |
| #define | MBEDTLS_ASN1_CHK_ADD(g, f) |
Functions | |
| int | mbedtls_asn1_write_len (unsigned char **p, unsigned char *start, size_t len) |
| Write a length field in ASN.1 format. More... | |
| int | mbedtls_asn1_write_tag (unsigned char **p, unsigned char *start, unsigned char tag) |
| Write an ASN.1 tag in ASN.1 format. More... | |
| int | mbedtls_asn1_write_raw_buffer (unsigned char **p, unsigned char *start, const unsigned char *buf, size_t size) |
| Write raw buffer data. More... | |
| int | mbedtls_asn1_write_mpi (unsigned char **p, unsigned char *start, const mbedtls_mpi *X) |
| Write a arbitrary-precision number (MBEDTLS_ASN1_INTEGER) in ASN.1 format. More... | |
| int | mbedtls_asn1_write_null (unsigned char **p, unsigned char *start) |
| Write a NULL tag (MBEDTLS_ASN1_NULL) with zero data in ASN.1 format. More... | |
| int | mbedtls_asn1_write_oid (unsigned char **p, unsigned char *start, const char *oid, size_t oid_len) |
| Write an OID tag (MBEDTLS_ASN1_OID) and data in ASN.1 format. More... | |
| int | mbedtls_asn1_write_algorithm_identifier (unsigned char **p, unsigned char *start, const char *oid, size_t oid_len, size_t par_len) |
| Write an AlgorithmIdentifier sequence in ASN.1 format. More... | |
| int | mbedtls_asn1_write_bool (unsigned char **p, unsigned char *start, int boolean) |
| Write a boolean tag (MBEDTLS_ASN1_BOOLEAN) and value in ASN.1 format. More... | |
| int | mbedtls_asn1_write_int (unsigned char **p, unsigned char *start, int val) |
| Write an int tag (MBEDTLS_ASN1_INTEGER) and value in ASN.1 format. More... | |
| int | mbedtls_asn1_write_tagged_string (unsigned char **p, unsigned char *start, int tag, const char *text, size_t text_len) |
| Write a string in ASN.1 format using a specific string encoding tag. More... | |
| int | mbedtls_asn1_write_printable_string (unsigned char **p, unsigned char *start, const char *text, size_t text_len) |
| Write a string in ASN.1 format using the PrintableString string encoding tag (MBEDTLS_ASN1_PRINTABLE_STRING). More... | |
| int | mbedtls_asn1_write_utf8_string (unsigned char **p, unsigned char *start, const char *text, size_t text_len) |
| Write a UTF8 string in ASN.1 format using the UTF8String string encoding tag (MBEDTLS_ASN1_PRINTABLE_STRING). More... | |
| int | mbedtls_asn1_write_ia5_string (unsigned char **p, unsigned char *start, const char *text, size_t text_len) |
| Write a string in ASN.1 format using the IA5String string encoding tag (MBEDTLS_ASN1_IA5_STRING). More... | |
| int | mbedtls_asn1_write_bitstring (unsigned char **p, unsigned char *start, const unsigned char *buf, size_t bits) |
| Write a bitstring tag (MBEDTLS_ASN1_BIT_STRING) and value in ASN.1 format. More... | |
| int | mbedtls_asn1_write_octet_string (unsigned char **p, unsigned char *start, const unsigned char *buf, size_t size) |
| Write an octet string tag (MBEDTLS_ASN1_OCTET_STRING) and value in ASN.1 format. More... | |
| mbedtls_asn1_named_data * | mbedtls_asn1_store_named_data (mbedtls_asn1_named_data **list, const char *oid, size_t oid_len, const unsigned char *val, size_t val_len) |
| Create or find a specific named_data entry for writing in a sequence or list based on the OID. If not already in there, a new entry is added to the head of the list. Warning: Destructive behaviour for the val data! More... | |
ASN.1 buffer writing functionality.
Definition in file asn1write.h.
| #define MBEDTLS_ASN1_CHK_ADD | ( | g, | |
| f | |||
| ) |
Definition at line 60 of file asn1write.h.
| mbedtls_asn1_named_data* mbedtls_asn1_store_named_data | ( | mbedtls_asn1_named_data ** | list, |
| const char * | oid, | ||
| size_t | oid_len, | ||
| const unsigned char * | val, | ||
| size_t | val_len | ||
| ) |
Create or find a specific named_data entry for writing in a sequence or list based on the OID. If not already in there, a new entry is added to the head of the list. Warning: Destructive behaviour for the val data!
| list | The pointer to the location of the head of the list to seek through (will be updated in case of a new entry). |
| oid | The OID to look for. |
| oid_len | The size of the OID. |
| val | The data to store (can be NULL if you want to fill it by hand). |
| val_len | The minimum length of the data buffer needed. |
NULL
if if there was a memory allocation error. | int mbedtls_asn1_write_algorithm_identifier | ( | unsigned char ** | p, |
| unsigned char * | start, | ||
| const char * | oid, | ||
| size_t | oid_len, | ||
| size_t | par_len | ||
| ) |
Write an AlgorithmIdentifier sequence in ASN.1 format.
| p | The reference to the current position pointer. |
| start | The start of the buffer, for bounds-checking. |
| oid | The OID of the algorithm to write. |
| oid_len | The length of the algorithm's OID. |
| par_len | The length of the parameters, which must be already written. If 0, NULL parameters are added |
p
on success. MBEDTLS_ERR_ASN1_XXX
error code on failure. | int mbedtls_asn1_write_bitstring | ( | unsigned char ** | p, |
| unsigned char * | start, | ||
| const unsigned char * | buf, | ||
| size_t | bits | ||
| ) |
Write a bitstring tag (MBEDTLS_ASN1_BIT_STRING) and value in ASN.1 format.
| p | The reference to the current position pointer. |
| start | The start of the buffer, for bounds-checking. |
| buf | The bitstring to write. |
| bits | The total number of bits in the bitstring. |
p
on success. | int mbedtls_asn1_write_bool | ( | unsigned char ** | p, |
| unsigned char * | start, | ||
| int | boolean | ||
| ) |
Write a boolean tag (MBEDTLS_ASN1_BOOLEAN) and value in ASN.1 format.
| p | The reference to the current position pointer. |
| start | The start of the buffer, for bounds-checking. |
| boolean | The boolean value to write, either 0 or 1 . |
p
on success. MBEDTLS_ERR_ASN1_XXX
error code on failure. | int mbedtls_asn1_write_ia5_string | ( | unsigned char ** | p, |
| unsigned char * | start, | ||
| const char * | text, | ||
| size_t | text_len | ||
| ) |
Write a string in ASN.1 format using the IA5String string encoding tag (MBEDTLS_ASN1_IA5_STRING).
| p | The reference to the current position pointer. |
| start | The start of the buffer, for bounds-checking. |
| text | The string to write. |
| text_len | The length of text in bytes (which might be strictly larger than the number of characters). |
p
on success. | int mbedtls_asn1_write_int | ( | unsigned char ** | p, |
| unsigned char * | start, | ||
| int | val | ||
| ) |
Write an int tag (MBEDTLS_ASN1_INTEGER) and value in ASN.1 format.
| p | The reference to the current position pointer. |
| start | The start of the buffer, for bounds-checking. |
| val | The integer value to write. |
p
on success. MBEDTLS_ERR_ASN1_XXX
error code on failure. | int mbedtls_asn1_write_len | ( | unsigned char ** | p, |
| unsigned char * | start, | ||
| size_t | len | ||
| ) |
Write a length field in ASN.1 format.
| p | The reference to the current position pointer. |
| start | The start of the buffer, for bounds-checking. |
| len | The length value to write. |
p
on success. MBEDTLS_ERR_ASN1_XXX
error code on failure. | int mbedtls_asn1_write_mpi | ( | unsigned char ** | p, |
| unsigned char * | start, | ||
| const mbedtls_mpi * | X | ||
| ) |
Write a arbitrary-precision number (MBEDTLS_ASN1_INTEGER) in ASN.1 format.
| p | The reference to the current position pointer. |
| start | The start of the buffer, for bounds-checking. |
| X | The MPI to write. |
p
on success. MBEDTLS_ERR_ASN1_XXX
error code on failure. | int mbedtls_asn1_write_null | ( | unsigned char ** | p, |
| unsigned char * | start | ||
| ) |
Write a NULL tag (MBEDTLS_ASN1_NULL) with zero data in ASN.1 format.
| p | The reference to the current position pointer. |
| start | The start of the buffer, for bounds-checking. |
p
on success. MBEDTLS_ERR_ASN1_XXX
error code on failure. | int mbedtls_asn1_write_octet_string | ( | unsigned char ** | p, |
| unsigned char * | start, | ||
| const unsigned char * | buf, | ||
| size_t | size | ||
| ) |
Write an octet string tag (MBEDTLS_ASN1_OCTET_STRING) and value in ASN.1 format.
| p | The reference to the current position pointer. |
| start | The start of the buffer, for bounds-checking. |
| buf | The buffer holding the data to write. |
| size | The length of the data buffer buf . |
p
on success. | int mbedtls_asn1_write_oid | ( | unsigned char ** | p, |
| unsigned char * | start, | ||
| const char * | oid, | ||
| size_t | oid_len | ||
| ) |
Write an OID tag (MBEDTLS_ASN1_OID) and data in ASN.1 format.
| p | The reference to the current position pointer. |
| start | The start of the buffer, for bounds-checking. |
| oid | The OID to write. |
| oid_len | The length of the OID. |
p
on success. MBEDTLS_ERR_ASN1_XXX
error code on failure. | int mbedtls_asn1_write_printable_string | ( | unsigned char ** | p, |
| unsigned char * | start, | ||
| const char * | text, | ||
| size_t | text_len | ||
| ) |
Write a string in ASN.1 format using the PrintableString string encoding tag (MBEDTLS_ASN1_PRINTABLE_STRING).
| p | The reference to the current position pointer. |
| start | The start of the buffer, for bounds-checking. |
| text | The string to write. |
| text_len | The length of text in bytes (which might be strictly larger than the number of characters). |
p
on success. | int mbedtls_asn1_write_raw_buffer | ( | unsigned char ** | p, |
| unsigned char * | start, | ||
| const unsigned char * | buf, | ||
| size_t | size | ||
| ) |
Write raw buffer data.
| p | The reference to the current position pointer. |
| start | The start of the buffer, for bounds-checking. |
| buf | The data buffer to write. |
| size | The length of the data buffer. |
p
on success. MBEDTLS_ERR_ASN1_XXX
error code on failure. | int mbedtls_asn1_write_tag | ( | unsigned char ** | p, |
| unsigned char * | start, | ||
| unsigned char | tag | ||
| ) |
Write an ASN.1 tag in ASN.1 format.
| p | The reference to the current position pointer. |
| start | The start of the buffer, for bounds-checking. |
| tag | The tag to write. |
p
on success. MBEDTLS_ERR_ASN1_XXX
error code on failure. | int mbedtls_asn1_write_tagged_string | ( | unsigned char ** | p, |
| unsigned char * | start, | ||
| int | tag, | ||
| const char * | text, | ||
| size_t | text_len | ||
| ) |
Write a string in ASN.1 format using a specific string encoding tag.
| p | The reference to the current position pointer. |
| start | The start of the buffer, for bounds-checking. |
| tag | The string encoding tag to write, e.g. MBEDTLS_ASN1_UTF8_STRING. |
| text | The string to write. |
| text_len | The length of text in bytes (which might be strictly larger than the number of characters). |
p
on success. | int mbedtls_asn1_write_utf8_string | ( | unsigned char ** | p, |
| unsigned char * | start, | ||
| const char * | text, | ||
| size_t | text_len | ||
| ) |
Write a UTF8 string in ASN.1 format using the UTF8String string encoding tag (MBEDTLS_ASN1_PRINTABLE_STRING).
| p | The reference to the current position pointer. |
| start | The start of the buffer, for bounds-checking. |
| text | The string to write. |
| text_len | The length of text in bytes (which might be strictly larger than the number of characters). |
p
on success.


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DBG VMs
2021
This document is outdated. Tyche is now loading Linux without a relocation thus allowing a simpler debugging model where all gdb commands work natively in the main gdb session attached to qemu.
I wrote this document when we were still trying to boot Linux on top of our security monitor with a memory relocation. At that point, we didn’t have any print output from the VM, we were not yet handling I/O devices correctly, etc.
Disclaimer: This is just me playing around; the code is not usable and the goal of the project was mostly to have fun and experiment the various tools available, e.g., gdb extensions, qemu configurations, etc.
The Challenges of Debugging a Guest VM
Most (system) programmers heavily rely on debuggers to understand their program’s behaviour and fix bugs. A debugger allows to set breakpoints, print the machine’s state (e.g., registers), disassemble code, inspect the program’s memory, and many other useful things. Unfortunately, our favorite debugger, GDB, seems to get slightly confused when attaching to a qemu session running tyche running a guest VM (here Linux or a static C program).
This article lists the problems we faced when trying to use GDB as is to debug Linux running on top of tyche and the solution we adopted to get back some of debugger’s functionalities, namely:
- Nested-guest symbols.
- Setting breakpoints on nested-guest functions using guest addresses/symbols.
- Dumping arbitrary memory content using nested-guest addresses.
- Post-crash inspection of memory content.
- Dumping Linux’s kernel print buffer.
We are, however, still missing a few valuable features:
- Performing a backtrace.
- Support for arbitrary memory relocations.
A Bit of Terminology
Before diving into the instricacies of the debugger, it is important to agree on the meaning of specific terms used throughout this article.
gpa - gva ; hpa - hva: guest physical address - guest virtual address; host physical address - host virtual address.
QEMU: QEMU is a machine & userpace emulator and virtualizer capable of integrating with hypervisors.
KVM: Kernel-based Virtual Machine allows user space programs access to hardware virtualization features.
When working with nested-virtualization, it can be hard to understand what terms such as guest
and host
refer to, as they are highly context-dependent.
Generally speaking, the host
is responsible for providing a virtual environment in which the guest
executes.
This article describes issues we faced while in active development.
Thus, in this context, the host
is the OS running QEMU, the guest
is Tyche, and the nested-guest
is the Linux instance loaded by Tyche.
To Debug with QEMU
QEMU supports gdb remote-connections and allows to debug guests
(here, tyche).
Most functionalities are available and it only requires a few extra steps compared to a regular gdb debugging session.
QEMU even supports switching back and forth between virtual and physical guests addresses.
With this simple setup, we are able to debug tyche code.
Unfortunatly, things get a little more complicated once tyche starts running a nested virtual machine.
GDB is unable to understand the virtual memory mappings set via EPTs and therefore rejects any memory dump.
Getting Back Debugging Features
Symbols
Tyche embbeds, at compile, the bytes of the nested-guest’s ELF file. As a result, only the tyche symbols are available in the debugging environment.
A simple fix consists in loading the nested-guest source file along side tyche’s debug information.
add-symbol-file nested-guest-elf
Breakpoints
Software breakpoints are incompatible with nested-guests. They usually overwrite a virtual address with a special instruction that triggers an interrupt caught by the debugger. In our case, GDB considers any virtual address to be invalid and thus cannot set the breakpoint properly.
Hardware breakpoints, i.e., hb
, leverage hardware support and seem to work just fine even when the nested-guest executes.
Note that there is a limited number of available breakpoints.
For convenience (and to avoid mistakenly setting a software breakpoint) we alias b
to hb
.
GDB does not allow direct aliasing of basic commands, but allows name shadows with functions:
define b:
hb $arg0
end
With this and the symbols available, we get our breakpoints back, even within the nested-guest functions.
Dumping Memory Content
This is the trickiest part. GDB does not understand the virtual memory layout once within the guest and errors on any attempt to dump memory. Switching to physical addresses is annoying as we would need to do the address translation by hand. Even worse, while within the nested-guest, tyche’s symbols no longer correspond to valid addresses and therefore cannot be printed either.
Our solution is a (hacky) simple one that relies on QEMU’s ability to map a guest’s memory to a file on the local disk. We then leverage this and a bit of python scripting to create a remote debug server capable of dumping memory content.
File-backed Guest Memory
QEMU allows the creation of memory-backed-files that contain the guest’s memory.
To create a guest with 6G
of memory whose default RAM is back by the file /tmp/tyche
, we simply need the following arguments when invoking QEMU:
# Give 6G of RAM to the guest
-m 6G
-object memory-backend-file,id=pc.ram,share=on,mem-path=/tmp/tyche,size=6G
-machine memory-backend=pc.ram
It is important that both the sizes and id match. Furthermore, in our example, we decided to file-back the default RAM. QEMU allows you to create extra memory regions with their own identifiers, that can be splitted into separate files.
We now have the full (live) content of our guest’s memory, but it’s still just a bunch of bytes. How do we distinguish between functions and variables, or associate file offsets with symbols?
Mapping Symbols to Bytes
What can we do with just a bunch of bytes?
Dumping them directly with hexdump
is pretty useless.
Assume we are in a GDB session attached to tyche and have a nested-guest physical address we would like to dump.
We know that gpa = hpa + guest_offset
and the guest offset is known to tyche.
Furthermore, the hpa
is also the /tmp/tyche
byte offset.
As a first, we can dump a particular address (or an array of bytes) by scripting a small GDB command that given an hpa
, calls xdd
with --seek {hpa}
and -l {size}
and dumps the corresponding content from the file.
class TycheGuestMemoryDump (gdb.Command):
def __init__(self):
super (TycheGuestMemoryDump, self).__init__("tmd", gdb.COMMAND_USER)
def invoke(self, arg, from_tty):
args = arg.split(" ")
if len(args) != 2:
print("Error: expected 2 args, received ", len(args))
return
(offset, size) = args
import os
# Convert the size into an int.
b_size = 0
try:
b_size = int(size)
except ValueError:
print("Error: 'size' is not an int ", size)
return
start = str(int(offset, 16))
command = [
"xxd",
"-seek",
start,
"-l",
str(b_size),
"/tmp/tych",
]
os.system(" ".join(command))
While this works, it’s a little crude.
It still requires us to have the hpa
, while most of the time we only have access to a gpa
or gva
while debugging the nested-guest.
Can we do better? Yes!
Let’s create a simple C program that mmaps the memory file and then executes an infinite loop.
#include <errno.h>
#include <fcntl.h>
#include <stdio.h>
#include <stdlib.h>
#include <sys/mman.h>
#include <sys/stat.h>
#include <unistd.h>
void * dbg_offset = 0;
void gdb_block() {
for (;;) {}
}
int main(void) {
const char * filepath = "/tmp/tyche";
int fd = open(filepath, O_RDONLY);
if (fd < 0) {
printf("Could not open %s\n", filepath);
exit(1);
}
struct stat statbuf;
int err = fstat(fd, &statbuf);
if (err < 0) {
printf("Unable to fstat the file %s\n", filepath);
exit(2);
}
char *ptr = mmap(NULL, statbuf.st_size, PROT_READ, MAP_SHARED, fd, 0);
if (ptr == MAP_FAILED) {
printf("Mapping Failed %d\n", errno);
exit(3);
}
close(fd);
gdb_block();
return 0;
}
Once compiled, we can run this program with gdb and set a breakpoint on gdb_block
.
We then have a gdb session with tyche’s memory mmaped at dbg_offset
.
How is that better than simply reading the file?
Well, here we can load the nested-guest’s symbols!
All we need is to know the value of guest_offset
.
Assuming for a second that we have this offset, and that the nested-guest is identity mapped, all we need to do in this gdb session is:
add-symbole-file {guest_file, e.g., vmlinux} -o {guest_offset}
And we get back the symbols and memory dumps! Well, almost. This whole process is cumbersome as it requires a second terminal running a separate gdb instance. But now that we have the basic principle in mind, we can automate everything with a bunch of gdb scripts and python.
Automation
We create gdb scripts that automatically set a breakpoint within tyche right after the guest is loaded and capture into convenience variables, for the current nested-guest, its guest_offset
stored in a global variable.
This is important as tyche’s globals will not be accessible once we are in the nested-guest.
Second, the script spawns a detached process that starts a gdb session executing our C program above.
This second session is scripted to block on dbg_block
, receive the guest_file
and guest_offset
as arguments, load the guest symbols, and start a python server waiting for commands.
Back in the QEMU gdb session, we create a python command called tyche
that forwards whatever we type to the second gdb session.
Furthermore, for convenience, we associate a context with each command to interpret any address surrounded by @
symbols as either gpa
, hpa
, gva
, or hva
.
The python gdb command will attempt to translate any address into an hpa
locally.
This is possible with rawc
as it is identity mapped, while for linux we need to remove the kernel mask.
Note that this does not work with relocations or stacks.
The C program gdb session then receives the command, translates addresses surrounded by @
by adding dbg_offset
to them, executes, and returns the result of the command via the same socket.
There we go! We got back memory dump and it works with symbols too!
We can even do post-mortem debugging as the /tmp/tyche
file is persisted on disk.
Dumping the Linux printk Buffer
Now how do we print the Linux printk
buffer?
Easy, we ask the remote session to print the __log_buf
buffer.
This requires capturing its address in a convenience var and then sending the command:
x/10s @{address}@
to print the first 10 lines.
Once again, we automate all of these using convenience vars and by defining a special command:
tyche PLOG {number of lines}
Limitations
While we support enough for our current debugging needs, there are still a few features that do not work.
Backtrace
Being able to perform a backstrace or a stack dump in the nested-guest would be amazing.
Unfortunately we do not have a way to support arbitrary gva -> gpa
mappings (or gpa->hpa
for that matter).
Relocations
A generalization of the backtrace problem is the support for arbitrary relocations/mappings at both page table levels.
A possible solution would be to point the remote gdb session to the root EPTs and PTs.
A python program could then walk the pages to compute a gva -> gpa -> hpa
address.
But that’s work for later!
Conclusion
In this article we presented our hacky way to get back some of the functionalities we lose when debugging a nested-guest inside a QEMU gdb session. There must be a better way of doing this, that better integrates with QEMU. Unfortunately, we did not find it. It just seemed easier (and funnier) to just put together a few scripts and implement our own debugging pipeline.


I spent a lot of time writing this software, so if you don't understand and appreciate it, you have de facto wasted my time. My software is simple, intuitive, and delightful.
Now that I have won you over, you will be amazed by how easy my features are to use and install. Simply open your terminal and run:
$ npm install fantastic-virus
and voila! You can now use your computer as a tiny space heater while I mine bitcoin with it.
There are lots of other people just like you who will misunderstand these instructions and submit bug reports that I will close unfixed. Join the conversation on DONC, HashFlex and Rabbit.
Dial pac
Commands: S = Shortcut on, BB = Bulletin Board, ? = Help


TRIANGLE TRACKER APP
This app will tell you what type of triangle
you have from the lengths provided.
Please enter the length of side A
Please enter the length of side B
Please enter the length of side C
Copyright© 2018
nignanthomas


NIPY (Neuroimaging in
Python) is making it easier to do better brain imaging research, by designing
and implementing free and open-source algorithms and pipelines for the
analysis of data from neuroimaging experiments, and teaching neuroscientists
how to use them.
Contact:
Ariel Rokem


Woody Allen and Amazon end legal battle
by The Associated Press, StaffNEW YORK - Woody Allen and Amazon.com have ended their legal battle.
The filmmaker had sued Amazon in February after the online giant ended his 2017 contract without ever releasing a completed film, "A Rainy Day in New York." Amazon had responded that Allen, whose daughter Dylan has accused him of molesting her when she was a girl, breached the 4-movie deal by making insensitive remarks about the .MeToo movement. Allen has repeatedly denied the allegations made by his daughter.
In papers filed Friday in U.S. District Court, Allen and Amazon agreed that the case should be dismissed without prejudice. Terms were not disclosed.
"A Rainy Day in New York" was released overseas, but not in the U.S. Allen's career has slowed in recent years, with several actors who had appeared in his films saying they would not work with him again.


Bruh, dildium is the best currency ever, screw dogecoin. Dogecoin? more like bitchcoin.
bruh but the thing is like i HATE all other currencies. bitcoin sucks, dogecoin sucks, lytecoint ucks sae
but literally, but some, OH YEAH ITS FREE!!! for now. get some quick, or should i say... click?
Bruh but like maybe get some, you can save how much u have soon; the tech monkeys at D coin HQ have not figured out how to make
that work. so yeah, we will soon... see ya.


Installation
Tensorflow Installation
Tefla requires Tensorflow (version >= 0.12.0) to be installed.
Select the correct binary to install, according to your system:
# Ubuntu/Linux 64-bit, CPU only, Python 2.7
$ export TF_BINARY_URL=https://storage.googleapis.com/tensorflow/linux/cpu/tensorflow-0.12.0-cp27-none-linux_x86_64.whl
# Ubuntu/Linux 64-bit, GPU enabled, Python 2.7
# Requires CUDA toolkit 8.0 and CuDNN v5. For other versions, see "Installing from sources" below.
$ export TF_BINARY_URL=https://storage.googleapis.com/tensorflow/linux/gpu/tensorflow_gpu-0.12.0-cp27-none-linux_x86_64.whl
# Mac OS X, CPU only, Python 2.7:
$ export TF_BINARY_URL=https://storage.googleapis.com/tensorflow/mac/cpu/tensorflow-0.12.0-py2-none-any.whl
# Mac OS X, GPU enabled, Python 2.7:
$ export TF_BINARY_URL=https://storage.googleapis.com/tensorflow/mac/gpu/tensorflow_gpu-0.12.0-py2-none-any.whl
# Ubuntu/Linux 64-bit, CPU only, Python 3.4
$ export TF_BINARY_URL=https://storage.googleapis.com/tensorflow/linux/cpu/tensorflow-0.12.0-cp34-cp34m-linux_x86_64.whl
# Ubuntu/Linux 64-bit, GPU enabled, Python 3.4
# Requires CUDA toolkit 8.0 and CuDNN v5. For other versions, see "Installing from sources" below.
$ export TF_BINARY_URL=https://storage.googleapis.com/tensorflow/linux/gpu/tensorflow_gpu-0.12.0-cp34-cp34m-linux_x86_64.whl
# Ubuntu/Linux 64-bit, CPU only, Python 3.5
$ export TF_BINARY_URL=https://storage.googleapis.com/tensorflow/linux/cpu/tensorflow-0.12.0-cp35-cp35m-linux_x86_64.whl
# Ubuntu/Linux 64-bit, GPU enabled, Python 3.5
# Requires CUDA toolkit 8.0 and CuDNN v5. For other versions, see "Installing from sources" below.
$ export TF_BINARY_URL=https://storage.googleapis.com/tensorflow/linux/gpu/tensorflow_gpu-0.12.0-cp35-cp35m-linux_x86_64.whl
# Mac OS X, CPU only, Python 3.4 or 3.5:
$ export TF_BINARY_URL=https://storage.googleapis.com/tensorflow/mac/cpu/tensorflow-0.12.0-py3-none-any.whl
# Mac OS X, GPU enabled, Python 3.4 or 3.5:
$ export TF_BINARY_URL=https://storage.googleapis.com/tensorflow/mac/gpu/tensorflow_gpu-0.12.0-py3-none-any.whl
Then install TensorFlow:
# Python 2
$ sudo pip install $TF_BINARY_URL
# Python 3
$ sudo pip3 install $TF_BINARY_URL
- For more details: Tensorflow installation instructions.
Tefla Installation
To install Tefla, the easiest way is to run
For the bleeding edge version:
pip install git+https://github.com/n3011/tefla.git
Otherwise, you can also install from source by running (from source folder):
python setup.py install
Upgrade Tensorflow
If you version for Tensorflow is too old (under 0.12.0), you may upgrade Tensorflow to avoid some incompatibilities with Tefla. To upgrade Tensorflow, you first need to uninstall Tensorflow and Protobuf:
pip uninstall protobuf
pip uninstall tensorflow
Then you can re-install Tensorflow:
Using Latest Tensorflow
Tefla is compatible with master version of Tensorflow, but some warnings may appear.


time
– time related functions¶
This module implements a subset of the corresponding CPython module,
as described below. For more information, refer to the original
CPython documentation: time
.
The time
module provides functions for getting the current time and date,
measuring time intervals, and for delays.
Time Epoch: Unix port uses standard for POSIX systems epoch of
1970-01-01 00:00:00 UTC. However, some embedded ports use epoch of
2000-01-01 00:00:00 UTC. Epoch year may be determined with gmtime(0)[0]
.
Maintaining actual calendar date/time: This requires a
Real Time Clock (RTC). On systems with underlying OS (including some
RTOS), an RTC may be implicit. Setting and maintaining actual calendar
time is responsibility of OS/RTOS and is done outside of MicroPython,
it just uses OS API to query date/time. On baremetal ports however
system time depends on machine.RTC()
object. The current calendar time
may be set using machine.RTC().datetime(tuple)
function, and maintained
by following means:
By a backup battery (which may be an additional, optional component for a particular board).
Using networked time protocol (requires setup by a port/user).
Set manually by a user on each power-up (many boards then maintain RTC time across hard resets, though some may require setting it again in such case).
If actual calendar time is not maintained with a system/MicroPython RTC, functions below which require reference to current absolute time may behave not as expected.
Functions¶
- time.gmtime([secs])¶
- time.localtime([secs])¶
Convert the time secs expressed in seconds since the Epoch (see above) into an 8-tuple which contains:
(year, month, mday, hour, minute, second, weekday, yearday)
If secs is not provided or None, then the current time from the RTC is used.The
gmtime()
function returns a date-time tuple in UTC, andlocaltime()
returns a date-time tuple in local time.The format of the entries in the 8-tuple are:
year includes the century (for example 2014).
month is 1-12
mday is 1-31
hour is 0-23
minute is 0-59
second is 0-59
weekday is 0-6 for Mon-Sun
yearday is 1-366
- time.mktime()¶
This is inverse function of localtime. It’s argument is a full 8-tuple which expresses a time as per localtime. It returns an integer which is the number of seconds since Jan 1, 2000.
- time.sleep(seconds)¶
Sleep for the given number of seconds. Some boards may accept seconds as a floating-point number to sleep for a fractional number of seconds. Note that other boards may not accept a floating-point argument, for compatibility with them use
sleep_ms()
andsleep_us()
functions.
- time.sleep_ms(ms)¶
Delay for given number of milliseconds, should be positive or 0.
This function will delay for at least the given number of milliseconds, but may take longer than that if other processing must take place, for example interrupt handlers or other threads. Passing in 0 for ms will still allow this other processing to occur. Use
sleep_us()
for more precise delays.
- time.sleep_us(us)¶
Delay for given number of microseconds, should be positive or 0.
This function attempts to provide an accurate delay of at least us microseconds, but it may take longer if the system has other higher priority processing to perform.
- time.ticks_ms()¶
Returns an increasing millisecond counter with an arbitrary reference point, that wraps around after some value.
The wrap-around value is not explicitly exposed, but we will refer to it as TICKS_MAX to simplify discussion. Period of the values is TICKS_PERIOD = TICKS_MAX + 1. TICKS_PERIOD is guaranteed to be a power of two, but otherwise may differ from port to port. The same period value is used for all of
ticks_ms()
,ticks_us()
,ticks_cpu()
functions (for simplicity). Thus, these functions will return a value in range [0 .. TICKS_MAX], inclusive, total TICKS_PERIOD values. Note that only non-negative values are used. For the most part, you should treat values returned by these functions as opaque. The only operations available for them areticks_diff()
andticks_add()
functions described below.Note: Performing standard mathematical operations (+, -) or relational operators (<, <=, >, >=) directly on these value will lead to invalid result. Performing mathematical operations and then passing their results as arguments to
ticks_diff()
orticks_add()
will also lead to invalid results from the latter functions.
- time.ticks_us()¶
Just like
ticks_ms()
above, but in microseconds.
- time.ticks_cpu()¶
Similar to
ticks_ms()
andticks_us()
, but with the highest possible resolution in the system. This is usually CPU clocks, and that’s why the function is named that way. But it doesn’t have to be a CPU clock, some other timing source available in a system (e.g. high-resolution timer) can be used instead. The exact timing unit (resolution) of this function is not specified ontime
module level, but documentation for a specific port may provide more specific information. This function is intended for very fine benchmarking or very tight real-time loops. Avoid using it in portable code.Availability: Not every port implements this function.
- time.ticks_add(ticks, delta)¶
Offset ticks value by a given number, which can be either positive or negative. Given a ticks value, this function allows to calculate ticks value delta ticks before or after it, following modular-arithmetic definition of tick values (see
ticks_ms()
above). ticks parameter must be a direct result of call toticks_ms()
,ticks_us()
, orticks_cpu()
functions (or from previous call toticks_add()
). However, delta can be an arbitrary integer number or numeric expression.ticks_add()
is useful for calculating deadlines for events/tasks. (Note: you must useticks_diff()
function to work with deadlines.)Examples:
# Find out what ticks value there was 100ms ago print(ticks_add(time.ticks_ms(), -100)) # Calculate deadline for operation and test for it deadline = ticks_add(time.ticks_ms(), 200) while ticks_diff(deadline, time.ticks_ms()) > 0: do_a_little_of_something() # Find out TICKS_MAX used by this port print(ticks_add(0, -1))
- time.ticks_diff(ticks1, ticks2)¶
Measure ticks difference between values returned from
ticks_ms()
,ticks_us()
, orticks_cpu()
functions, as a signed value which may wrap around.The argument order is the same as for subtraction operator,
ticks_diff(ticks1, ticks2)
has the same meaning asticks1 - ticks2
. However, values returned byticks_ms()
, etc. functions may wrap around, so directly using subtraction on them will produce incorrect result. That is whyticks_diff()
is needed, it implements modular (or more specifically, ring) arithmetics to produce correct result even for wrap-around values (as long as they not too distant inbetween, see below). The function returns signed value in the range [-TICKS_PERIOD/2 .. TICKS_PERIOD/2-1] (that’s a typical range definition for two’s-complement signed binary integers). If the result is negative, it means that ticks1 occurred earlier in time than ticks2. Otherwise, it means that ticks1 occurred after ticks2. This holds only if ticks1 and ticks2 are apart from each other for no more than TICKS_PERIOD/2-1 ticks. If that does not hold, incorrect result will be returned. Specifically, if two tick values are apart for TICKS_PERIOD/2-1 ticks, that value will be returned by the function. However, if TICKS_PERIOD/2 of real-time ticks has passed between them, the function will return -TICKS_PERIOD/2 instead, i.e. result value will wrap around to the negative range of possible values.Informal rationale of the constraints above: Suppose you are locked in a room with no means to monitor passing of time except a standard 12-notch clock. Then if you look at dial-plate now, and don’t look again for another 13 hours (e.g., if you fall for a long sleep), then once you finally look again, it may seem to you that only 1 hour has passed. To avoid this mistake, just look at the clock regularly. Your application should do the same. “Too long sleep” metaphor also maps directly to application behaviour: don’t let your application run any single task for too long. Run tasks in steps, and do time-keeping inbetween.
ticks_diff()
is designed to accommodate various usage patterns, among them:Polling with timeout. In this case, the order of events is known, and you will deal only with positive results of
ticks_diff()
:# Wait for GPIO pin to be asserted, but at most 500us start = time.ticks_us() while pin.value() == 0: if time.ticks_diff(time.ticks_us(), start) > 500: raise TimeoutError
Scheduling events. In this case,
ticks_diff()
result may be negative if an event is overdue:# This code snippet is not optimized now = time.ticks_ms() scheduled_time = task.scheduled_time() if ticks_diff(scheduled_time, now) > 0: print("Too early, let's nap") sleep_ms(ticks_diff(scheduled_time, now)) task.run() elif ticks_diff(scheduled_time, now) == 0: print("Right at time!") task.run() elif ticks_diff(scheduled_time, now) < 0: print("Oops, running late, tell task to run faster!") task.run(run_faster=true)
Note: Do not pass
time()
values toticks_diff()
, you should use normal mathematical operations on them. But note thattime()
may (and will) also overflow. This is known as https://en.wikipedia.org/wiki/Year_2038_problem .
- time.time()¶
Returns the number of seconds, as an integer, since the Epoch, assuming that underlying RTC is set and maintained as described above. If an RTC is not set, this function returns number of seconds since a port-specific reference point in time (for embedded boards without a battery-backed RTC, usually since power up or reset). If you want to develop portable MicroPython application, you should not rely on this function to provide higher than second precision. If you need higher precision, absolute timestamps, use
time_ns()
. If relative times are acceptable then use theticks_ms()
andticks_us()
functions. If you need calendar time,gmtime()
orlocaltime()
without an argument is a better choice.Difference to CPython
In CPython, this function returns number of seconds since Unix epoch, 1970-01-01 00:00 UTC, as a floating-point, usually having microsecond precision. With MicroPython, only Unix port uses the same Epoch, and if floating-point precision allows, returns sub-second precision. Embedded hardware usually doesn’t have floating-point precision to represent both long time ranges and subsecond precision, so they use integer value with second precision. Some embedded hardware also lacks battery-powered RTC, so returns number of seconds since last power-up or from other relative, hardware-specific point (e.g. reset).
Constructors¶
- class time.clock¶
Returns a clock object.
Methods¶
- tick()¶
Starts tracking elapsed time.
- fps()¶
Stops tracking the elapsed time and returns the current FPS (frames per second).
Always call
tick
first before calling this function.
- avg()¶
Stops tracking the elapsed time and returns the current average elapsed time in milliseconds.
Always call
tick
first before calling this function.
- reset()¶
Resets the clock object.


Asking a questions is just as important as finding the answer. In order to ease the process of finding an answer and allowing others to supply correct answers, questions must be specific and easy to understand.
So what makes up a good question? Specific, concise, single focused (break the question into multiple varied questions if possible), and at least some showing of effort that you tried to a decent amount to find the answer on your own (if possible).
Lots of times, on various forums, when a question that is extremely vague, too open ended, or just way to easy too answer without outside help, others will either supply the incorrect answer (due to not understanding the question), or not even bother to answer the question (because questions are asked in order to learn something, but if no effort is put in to learn on your own, others aren't as eager/willing to help 'teach').


{% extends 'base.html'%} {% load static %} {% block content %}
Hurrah! You have sucessfully solved this Question. Back to Questions Page


Beaming Deep Learning with Ludwig
Suneel Marthi
October 30, 2019
Open Source Summit Europe, Lyon, France
TensorFlow based toolkit from Uber AI labs
Open Sourced by Uber in 2019 - Apache 2 license
“If deep learning libraries provide the building blocks for your building, Ludwig provides the buildings for your city, and you choose among the available buildings or add your own building to the set of available ones.”
ZERO coding experience needed to train a model and make predictions
My 7th grader has created a few text classification models to work on his English homeworks
Data type-based approach to Deep Learning Model Design
Makes the framework usable across different use cases
Easy to learn for Deep Learning novices
Experienced DL practitioners have extensive Model control
Easily add new model architectures and feature types.
Most Deep Learning models seem like Black Boxes
Ludwig provides Visualization tools to measure performance and understand predictions
Only CSV input format now supported
Provide training data in CSV and a Model Definition file as YAML
input_features:
-
name: text
type: text
output_features:
-
name: airline_sentiment
type: category
Encoders map raw data to Tensors
Decoders map Tensors to Outputs
Combiners combine the tensors from all input encoders, process them, and return the tensors to be used for the output decoders.
Flexible encoder-Decoder architecture allows to train sophisticated models
Eg: For a NLP task - use a Convolutional Neural Network (CNN) as text encoder,
and a Recurrent Neural Network(RNN) as decoder
Train a Ludwig Model offline
Model Inference in a Beam pipeline
pipeline_options = PipelineOptions(pipeline_args)
pipeline_options.view_as(SetupOptions).save_main_session = True
pipeline_options.view_as(StandardOptions).streaming = True
with beam.Pipeline(options=pipeline_options) as p:
filtered_tweets = (p
| beam.io.ReadFromText('tweets.txt')
|'batch into n batches' >> BatchElements(min_batch_size=1, max_batch_size=5)
| "Translate tweets" >> beam.ParDo(TranslateDoFn.TranslateDoFn()))
Ludwig presently only supports CSV inputs
Model training still needs to be done offline


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java.lang.Object ar.com.hjg.pngj.chunks.PngChunk
public abstract class PngChunk
Represents a instance of a PNG chunk.
See http://www.libpng.org/pub/png/spec/1.2/PNG-Chunks .html
Concrete classes should extend PngChunkSingle
or PngChunkMultiple
Note that some methods/fields are type-specific (getOrderingConstraint(), allowsMultiple()),
some are 'almost' type-specific (id,crit,pub,safe; the exception is PngUKNOWN),
and the rest are instance-specific
| Nested Class Summary | |
|---|---|
static class |
PngChunk.ChunkOrderingConstraint
Possible ordering constraint for a PngChunk type -only relevant for ancillary chunks. |
| Field Summary | |
|---|---|
boolean |
crit
Autocomputed at creation time |
java.lang.String |
id
Chunk-id: 4 letters |
boolean |
pub
Autocomputed at creation time |
boolean |
safe
Autocomputed at creation time |
| Method Summary | ||
|---|---|---|
abstract boolean |
allowsMultiple()
|
|
static
|
cloneChunk(T chunk,
ImageInfo info)
Makes a clone (deep copy) calling cloneDataFromRead(PngChunk) |
|
abstract void |
cloneDataFromRead(PngChunk other)
Makes a copy of the chunk. |
|
abstract ChunkRaw |
createRawChunk()
Creates the physical chunk. |
|
static PngChunk |
factory(ChunkRaw chunk,
ImageInfo info)
This factory creates the corresponding chunk and parses the raw chunk. |
|
static PngChunk |
factoryFromId(java.lang.String cid,
ImageInfo info)
Creates one new blank chunk of the corresponding type, according to factoryMap (PngChunkUNKNOWN if not known) |
|
static void |
factoryRegister(java.lang.String chunkId,
java.lang.Class<? extends PngChunk> chunkClass)
Registers a chunk-id (4 letters) to be associated with a PngChunk class This method should be called by user code that wants to add some chunks (not implmemented in this library) to the factory, so that the PngReader knows about it. |
|
int |
getChunkGroup()
In which "chunkGroup" (see ChunksList for definition) this chunks instance was read or written. |
|
int |
getLength()
|
|
long |
getOffset()
|
|
abstract PngChunk.ChunkOrderingConstraint |
getOrderingConstraint()
see PngChunk.ChunkOrderingConstraint |
|
boolean |
hasPriority()
|
|
static boolean |
isKnown(java.lang.String id)
True if the chunk-id type is known. |
|
abstract void |
parseFromRaw(ChunkRaw c)
Parses raw chunk and fill inside data. |
|
void |
setChunkGroup(int chunkGroup)
|
|
void |
setOffset(long offset)
|
|
void |
setPriority(boolean priority)
|
|
java.lang.String |
toString()
|
| Methods inherited from class java.lang.Object |
|---|
equals, getClass, hashCode, notify, notifyAll, wait, wait, wait |
| Field Detail |
|---|
public final boolean crit
public final java.lang.String id
public final boolean pub
public final boolean safe
| Method Detail |
|---|
public abstract boolean allowsMultiple()
public static <T extends PngChunk> T cloneChunk(T chunk, ImageInfo info)
cloneDataFromRead(PngChunk)
public abstract void cloneDataFromRead(PngChunk other)
This is used when copying chunks from a reader to a writer
It should normally be a deep copy, and after the cloning this.equals(other) should return true
public abstract ChunkRaw createRawChunk()
public static PngChunk factory(ChunkRaw chunk, ImageInfo info)
public static PngChunk factoryFromId(java.lang.String cid, ImageInfo info)
public static void factoryRegister(java.lang.String chunkId, java.lang.Class<? extends PngChunk> chunkClass)
This method should be called by user code that wants to add some chunks (not implmemented in this library) to the factory, so that the PngReader knows about it.
public final int getChunkGroup()
ChunksList
for definition) this chunks instance was read or written.
-1 if not read or written (eg, queued)
public int getLength()
public long getOffset()
public abstract PngChunk.ChunkOrderingConstraint getOrderingConstraint()
PngChunk.ChunkOrderingConstraint
public boolean hasPriority()
public static boolean isKnown(java.lang.String id)
A chunk is known if we recognize its class, according with factoryMap
This is not necessarily the same as being "STANDARD", or being implemented in this library
Unknown chunks will be parsed as instances of PngChunkUNKNOWN
public abstract void parseFromRaw(ChunkRaw c)
public final void setChunkGroup(int chunkGroup)
getChunkGroup()
public void setOffset(long offset)
public void setPriority(boolean priority)
public java.lang.String toString()
toString
in class java.lang.Object
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---
layout: single
title: "[CFP] ICDF2C 2014 Submissions Due"
date: '2014-05-12T16:31:00.001+09:00'
author: Joshua James
tags:
- Conferences 2014
- CFP 2014
modified_time: '2015-01-20T16:04:02.953+09:00'
thumbnail: http://4.bp.blogspot.com/-tYSeA66xYGE/VLz81SENE8I/AAAAAAAAA3A/aa8tq1v2Pas/s72-c/200.png
blogger_id: tag:blogger.com,1999:blog-2701259639305045003.single-2612479922330078961
blogger_orig_url: http://www.cybercrimetech.com/2014/05/cfp-icdf2c-2014-submissions-due.html
---
Just a quick reminder that submissions for the 6th International Conference on Digital Forensics & Cyber Crime are due THIS FRIDAY (May 16, 2014). See submission details here: http://d-forensics.org
ICDF2C 2014, 6th International Conference on Digital Forensics & Cyber Crime, will take place in New Haven, Connecticut, United States, September 18–20, 2014.


I'm a Brisbane-based web developer from Scotland. I share my thoughts and discoveries here on the blog. For everything else, check out my personal website.


My service in the Air Force fostered my enthusiasm for software development and testing. I transitioned from the military into a cleared position contracting for the Department of Defense while completing a Master's in Computer Science. After graduating this past September, I am continuing my training as a student at Code Platoon, a Chicago-based non-profit that trains veterans for full-stack web development careers.
Connect with me
GPA: 3.64
GPA: 3.7
In my work with DevOps, Agile development teams, and network administrators, I verified accuracy and operability of newly installed hardware systems and software suites. This involved creating and executing test plans and providing feedback. I was able to ensure accuracy using live data prior to deployment, commonly using black box and smoke testing techniques. I maintained and tested deployed systems, performing troubleshooting, monitoring networks, and providing user training.
As a program manager at Jovian Concepts, I led two programs, serving as the regional site lead and the primary point of contact to the programs' clients and employees. I coordinated with section managers regarding employee performance feedback. As for recruitment, interviews, and hiring, I was able to staff a newly awarded contract in a competitive environment, doubling our regional footprint.
Formally trained as an Arabic-French Cryptologic Linguist, I worked as a signals analyst in collections, geolocations, and reporting in a customer-facing role. My growing interest in technology pushed me into roles maintaining and troubleshooting hardware and software systems. I established and monitored network paths and ensured dataflow integrity.
I was selected as the SIGINT Division's senior mission manager. I was able to use the operational experience I'd gained to advise government leaders, deliver briefings, and execute customer tasks. I also used this experience to train managers and operators, and work closely with the qualification-testing cell to ensure realistic, up-to-date testing and study material. I worked as a product owner for an Agile development team to determine priorities and scheduling based on operational demands. I wrote and updated software user manuals as new versions deployed.
I enjoy being an avid tech learner. I am regularly participating in online courses for software development and network engineering. An extension of this hobby includes blogging and tweeting about open-source resources for independent learners aspiring to tech careers. You can often find me at one of the tech meetup events at the local coworking space.
When I'm offline, I really enjoy travelling, even if just to a neighboring town. If there is a festival, concert, or show, count me in. If I can't get away, I enjoy binging netflix with my dogs and reading personal development books. My most recent read was "Work Clean" by Dan Charnas.


What’s a parameter?
A parameter can also be called an argument. It’s the thing passed into a function that you do something with:
But what if a function can do something without a parameter, or what if the functionality changes based on whether or not a parameter was passed in?
In the above example, we expect that if x
“exists”, then we’ll do something; if not, we’ll do something else. But checking for existence is a little more difficult than that. It has to do with truthiness.
The truth about truthiness
In if
statements, JavaScript evaluates the statement to a boolean true
or false
, and acts accordingly. But when certain values are encountered, JavaScript “coerces” them to a boolean value. For example, these statements are all correct:
These are all true:
There are plenty of other examples. However, you’ll notice above that we’re using the ==
operator. This is called the equality operator. It checks if two values are “equal”, but to do this, JavaScript coerces the types.
These are all incorrect (they will evaluate to false):
You’ll notice a very subtle, but important, difference here: we’re using the ===
operator: also called the identity operator. 1
does not have the identity of true
, however, it is equal to true. This is confusing at first, but this is the principle of truthiness.
This brings us to a very important logical operator, the exlamation point !
(also called the “not” operator). It gives you the opposite of whatever boolean value you give.
The “not” operator in action (the following statements are all true)
You’ll notice above that we are using the strict identity operator ===
. This is okay, because the !
operator coerces the values on the left side of the equation to a boolean value. So really when we say !1 === false
, we’re actually saying false === false
. In other words, false
does have the identity of false
.
The “double not” (or just two “not” operators — these are also all true)
The double not basically coerces each value into its equal boolean form. That’s a weird way to say it. Think of it like this: 0 == false
is the same as !!0 === false
.
So how do we check for existence?
Well, it depends on how we want to define existence. Do we want to say that the parameter doesn’t exist, if it is null
,undefined
,0
,false
, or some other non-truthy value? What if we want to pass in an empty string (''
) as a value?
Bad example:
So we can combine instead combine logical statements to check for our idea of existence:
Better example:
Checking strictly for undefined values:
In the above example, a
was never declared. If a variable is never declared and you try to check for its existence, you’ll get an error. But the typeof
operator is the only operator (to my knowledge) that gets around this. If you check the type of a variable that was never declared, you won’t get an error, and your program can continue.
Declared vs. defined
Best Practice
I think in this circumstance, the best practice depends on however you define “existence” in the context of your specific function. This means that you have to take into consideration the concepts of truthiness, the use of the typeof
operator, the principle of declared vs. defined, etc.
Keep in mind, too, that there are many ways to check the types of of variables you encounter. For example:
This is a topic for another post, but it demonstrates how you can check the types of a variable based on your definition of existence in the context of your specific function.


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