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Project Group: de.tu-darmstadt.stg

rescala

 de.tu-darmstadt.stg : rescala_sjs1_2.11

Last Version: 0.31.0

Release Date:

rescala

 de.tu-darmstadt.stg : rescala_2.11

Last Version: 0.31.0

Release Date:

rescala

 de.tu-darmstadt.stg : rescala_sjs1_2.12

Last Version: 0.31.0

Release Date:

rescala

 de.tu-darmstadt.stg : rescala_2.12

Last Version: 0.31.0

Release Date:

rescala

 de.tu-darmstadt.stg : rescala_2.13

Last Version: 0.31.0

Release Date:

rescala

 de.tu-darmstadt.stg : rescala_sjs1_2.13

Last Version: 0.31.0

Release Date:

rescala

 de.tu-darmstadt.stg : rescala_native0.4_2.11

Last Version: 0.31.0

Release Date:

rescala

 de.tu-darmstadt.stg : rescala_native0.4_2.12

Last Version: 0.31.0

Release Date:

rescala

 de.tu-darmstadt.stg : rescala_native0.4_2.13

Last Version: 0.31.0

Release Date:

rescala

 de.tu-darmstadt.stg : rescala_sjs1_3

Last Version: 0.31.0

Release Date:

rescala

 de.tu-darmstadt.stg : rescala_3

Last Version: 0.31.0

Release Date:

sootkeeper-framework

 de.tu-darmstadt.stg : sootkeeper-framework

The use of static analysis allows developers to analyze the source code of a program. On one hand, developers get accurate data representing any issues with the program. On the other hand, static analysis programs can have lengthy execution times. This results in a large amount of developer idleness, waiting for their program to execute. A developer's debug cycles can be particularly time consuming, when tweaking their analyses. They then have to wait around for long periods of time to test their minor changes. In order to avoid this needless idle time, we have looked into modularizing a static analysis program in order to cut down on time wasted.

Last Version: 1.0

Release Date:

Analysis Keeper

 de.tu-darmstadt.stg : sootkeeper-analysiskeeper

The use of static analysis allows developers to analyze the source code of a program. On one hand, developers get accurate data representing any issues with the program. On the other hand, static analysis programs can have lengthy execution times. This results in a large amount of developer idleness, waiting for their program to execute. A developer's debug cycles can be particularly time consuming, when tweaking their analyses. They then have to wait around for long periods of time to test their minor changes. In order to avoid this needless idle time, we have looked into modularizing a static analysis program in order to cut down on time wasted.

Last Version: 1.0

Release Date:

sootkeeper-container

 de.tu-darmstadt.stg : sootkeeper-container

The use of static analysis allows developers to analyze the source code of a program. On one hand, developers get accurate data representing any issues with the program. On the other hand, static analysis programs can have lengthy execution times. This results in a large amount of developer idleness, waiting for their program to execute. A developer's debug cycles can be particularly time consuming, when tweaking their analyses. They then have to wait around for long periods of time to test their minor changes. In order to avoid this needless idle time, we have looked into modularizing a static analysis program in order to cut down on time wasted.

Last Version: 1.0

Release Date:

sootkeeper-soot-bundle

 de.tu-darmstadt.stg : sootkeeper-soot-bundle

The use of static analysis allows developers to analyze the source code of a program. On one hand, developers get accurate data representing any issues with the program. On the other hand, static analysis programs can have lengthy execution times. This results in a large amount of developer idleness, waiting for their program to execute. A developer's debug cycles can be particularly time consuming, when tweaking their analyses. They then have to wait around for long periods of time to test their minor changes. In order to avoid this needless idle time, we have looked into modularizing a static analysis program in order to cut down on time wasted.

Last Version: 1.0

Release Date:

framework

 de.tu-darmstadt.stg : framework

The use of static analysis allows developers to analyze the source code of a program. On one hand, developers get accurate data representing any issues with the program. On the other hand, static analysis programs can have lengthy execution times. This results in a large amount of developer idleness, waiting for their program to execute. A developer's debug cycles can be particularly time consuming, when tweaking their analyses. They then have to wait around for long periods of time to test their minor changes. In order to avoid this needless idle time, we have looked into modularizing a static analysis program in order to cut down on time wasted.

Last Version: 1.0

Release Date:

SootKeeper

 de.tu-darmstadt.stg : sootkeeper

The use of static analysis allows developers to analyze the source code of a program. On one hand, developers get accurate data representing any issues with the program. On the other hand, static analysis programs can have lengthy execution times. This results in a large amount of developer idleness, waiting for their program to execute. A developer's debug cycles can be particularly time consuming, when tweaking their analyses. They then have to wait around for long periods of time to test their minor changes. In order to avoid this needless idle time, we have looked into modularizing a static analysis program in order to cut down on time wasted.

Last Version: 1.0

Release Date:

Analysis Keeper

 de.tu-darmstadt.stg : analysiskeeper

The use of static analysis allows developers to analyze the source code of a program. On one hand, developers get accurate data representing any issues with the program. On the other hand, static analysis programs can have lengthy execution times. This results in a large amount of developer idleness, waiting for their program to execute. A developer's debug cycles can be particularly time consuming, when tweaking their analyses. They then have to wait around for long periods of time to test their minor changes. In order to avoid this needless idle time, we have looked into modularizing a static analysis program in order to cut down on time wasted.

Last Version: 1.0

Release Date:

container

 de.tu-darmstadt.stg : container

The use of static analysis allows developers to analyze the source code of a program. On one hand, developers get accurate data representing any issues with the program. On the other hand, static analysis programs can have lengthy execution times. This results in a large amount of developer idleness, waiting for their program to execute. A developer's debug cycles can be particularly time consuming, when tweaking their analyses. They then have to wait around for long periods of time to test their minor changes. In order to avoid this needless idle time, we have looked into modularizing a static analysis program in order to cut down on time wasted.

Last Version: 1.0

Release Date:

soot-bundle

 de.tu-darmstadt.stg : soot-bundle

The use of static analysis allows developers to analyze the source code of a program. On one hand, developers get accurate data representing any issues with the program. On the other hand, static analysis programs can have lengthy execution times. This results in a large amount of developer idleness, waiting for their program to execute. A developer's debug cycles can be particularly time consuming, when tweaking their analyses. They then have to wait around for long periods of time to test their minor changes. In order to avoid this needless idle time, we have looked into modularizing a static analysis program in order to cut down on time wasted.

Last Version: 1.0

Release Date:

hello-world

 de.tu-darmstadt.stg : hello-world

The use of static analysis allows developers to analyze the source code of a program. On one hand, developers get accurate data representing any issues with the program. On the other hand, static analysis programs can have lengthy execution times. This results in a large amount of developer idleness, waiting for their program to execute. A developer's debug cycles can be particularly time consuming, when tweaking their analyses. They then have to wait around for long periods of time to test their minor changes. In order to avoid this needless idle time, we have looked into modularizing a static analysis program in order to cut down on time wasted.

Last Version: 1.0

Release Date:

SootConfig

 de.tu-darmstadt.stg : sootconfig

Fluent-interface configuration for Soot

Last Version: 1.1

Release Date:

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